JPL PUBLICATION 86-29 

Shuttle Imaging Radar-C 

Science Plan

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National Aeronautics and 

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Jet Propulsion Laboratory 

California Institute of Technology 

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JPL PUBLICATION 86-29

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Shuttle Imaging Radar-C 

Science Plan 

September 1, 1986 

NASA 

National Aeronautics and 

Space Administration 

Jet Propulsion Laboratory 

California Institute of Technology 

Pasadena, California
The research described in this publication was carried out by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics 

and Space Administration. 

Reference herein to any specific commercial product, process, or service by trade name, 

trademark, manufacturer, or otherwise, does not constitute or imply its endorsement by 

the United States Government or the Jet Propulsion Laboratory, California Institute of 

Technology.
Abstract 

The. Shuttle Imaging Radar-C (SIR-C) mission will yield new and advanced 

scientific studies of the earth. SIR-C will be the first instrument to simultaneously 

acquire images at L-band and C-band with HH, VV, HV, or VH polarizations, as 

well as images of the phase difference between HH and VV polarizations. These data 

will be digitally encoded and recorded using onboard high-density digital tape 

recorders and will later be digitally processed into images using the JPL Advanced 

Digital SAR Processor. 

There are a large number of potential SIR-C experiments. Geologic studies include 

cold-region geomorphology, fluvial geomorphology, rock weathering and erosional processes, tectonics and geologic boundaries, geobotany, and radar stereogrammetry. 

Hydrology investigations cover arid, humid, wetland, snow-covered, and high-latitude 

regions. Additionally, SIR-C will provide the data to identify and map vegetation types, 

interpret landscape patterns and processes, assess the biophysical properties of plant 

canopies, and determine the degree of radar penetration of plant canopies. 

In the field of oceanography, SIR-C will provide the information necessary to: 

forecast ocean directional wave spectra; better understand internal wave-current interactions; study the relationship of ocean-bottom features to surface expressions and the correlation of wind signatures to radar backscatter; and detect current-system boundaries, 

oceanic fronts, and mesoscale eddies. And, as the first spaceborne SAR with multifrequency, multipolarization imaging capabilities, whole new areas of glaciology will be 

opened for study when SIR-C is flown in a polar orbit.
Preface 

This Science Plan was written before the Shuttle Challenger accident in January, 

1986. In addition to the tragic loss of lives, the accident has resulted in many 

changes in the Shuttle schedule. In particular, the resulting delay of launches from 

Vandenberg Air Force Base will preclude any U.S.-launched, polar-orbiting missions 

until its reopening. Any flights prior to that time will be restricted to 57° inclination 

orbits. In spite of these changes, the objectives and requirements presented in this 

report are still valid and serve as guidelines for the continuing National 

Aeronautics and Space Administration (NASA) Spaceborne Imaging Radar (SIR) 

program. 

The SIR program consists of an evolutionary approach in which more sophisticated technology may be incorporated into a basic sensor as the scientific requirements become increasingly stringent. The first phases of the program, consisting of 

Seasat and SIR-A, have shown that, while single parameter synthetic aperture radar 

sensors provide the capability to observe global patterns on the earth's surface, more 

detailed surface information is required to relate these patterns to processes that are 

ongoing throughout the earth system. The multi-incidence angle radar data acquired 

by SIR-B in the second phase of the SIR program provided some insight into what 

kind of capabilities are required to better characterize the earth's surface and model 

its short-term and long-term evolutionary history. Clearly, global coverage and 

multitemporal coverage are two key requirements. In addition, sensor versatility is 

essential since different investigations may require very different scales, resolutions, 

or accuracies of observations. 

The SIR-C sensor is designed to be versatile enough to meet a variety of observational requirements and will therefore require very little modification in terms of 

scientific data products before it is installed on a permanently orbiting polar platform 

as part of the Earth Observing System (EOS). However, the data handling and data 

analysis tools that will be required to utilize a continuous stream of multiparameter 

spaceborne radar data from EOS are seriously deficient; scientists need further 

experience with radar data to develop the capability to analyze it efficiently under 

high data-rate conditions. The SIR-C Science Working Group therefore recommends 

that NASA fly the SIR-C sensor in two different seasons as soon as possible to provide scientists with multitemporal data, even if the coverage is restricted to a 57° 

orbit. The Group further recommends that the basic SIR-C sensor be flown in a 

polar orbit as soon as the launch capability exists. 

iv
Executive Summary 

The Shuttle Imaging Radar-C (SIR-C) mission will provide a powerful new tool 

for scientific studies of the earth, and will be a significant step forward in the evolution of an advanced spaceborne imaging radar. It will provide 

(1) The first opportunity for simultaneous multifrequency radar imagery from 

space for geoscientific studies of the earth 

(2) The first spaceborne high-resolution imaging sensor with simultaneous multipolarization capability 

(3) The first multiparameter imaging radar, which will supply coverage during 

two different seasons 

The SIR-C mission will include two Shuttle launches, thereby permitting two 8-day 

observing periods during different seasons. One-day repeat coverage would be 

provided during an 8-day mission. 

SIR-C will allow the simultaneous acquisition of images at L-band and C-band 

with HH, VV, HV, or VH polarizations, as well as images of the phase difference 

between HH and VV polarizations. It will also be possible to electronically steer the 

antenna beam so that images may be acquired from 15 '-55 ' angles of incidence. 

Plans also include the addition of a German-developed X-band SAR (X-SAR), which 

would then allow simultaneous imaging of selected sites at 23-cm, 6-cm, and 3-cm 

wavelengths. SIR-C swath widths will vary from 15 km to 90 km (depending on the 

number of simultaneous frequencies an polarizations selected) and the resolution 

will be approximately 30 m in the low-resolution mode and 15 m in the highresolution mode. 

SIR-C data will be digitally encoded and recorded using onboard high-density 

digital tape recorders. These raw data will later be digitally processed into images 

using the JPL Advanced Digital SAR Processor. The radiometric calibration goals 

include relative radiometric stability (during a mission and at a given frequency) of 

±1 dB, absolute accuracy (for comparison between missions) of ± 3 dB, and calibration of ±1.5 dB of the L-band channel relative to the C-band channel for multiwavelength comparisons). The geometric calibration goals include absolute location 

accuracy to at least 1 km. 

This science plan provides a detailed discussion of potential SIR-C experiments 

that could be performed in the areas of geology, hydrology, vegetation science, 

glaciology, and oceanography. It-is envisioned that many of these experiments will 

make use of carefully selected test sites, i.e., "supersites," with enhanced ground 

truth instrumentation. In addition to these geoscientific experiments, a number of 

radar-technique related experiments are discussed. 

Geology experiments include investigations of cold-region geomorphology, fluvial 

geomorphology, rock weathering and erosional processes, tectonics and geologic 

boundaries, geobotany, and radar stereogrammetry. Potential cold region geomorphology studies possible with SIR-C in a high inclination orbit include the determination 

of optimum frequencies and polarizations for glacial landform mapping, the optimum 

illumination angles and frequencies for the perception of permafrost and thermokarst 

boundaries, the analysis of Antarctic dry-valley surface properties and penetration 

depths, and the observation of ice-sheet pressure ridges, fractures, etc. SIR-C data 

should be especially valuable in fluvial geomorphology investigations, principally 

because of the sensitivity of radar to open bodies of water (including rivers) in contrast
to surrounding terrain. The multipolarization capability of SIR-C may make it possible to separate rock lithologies within dendritic stream patterns, and the L-band 

channel may allow additional studies of penetration to buried drainage networks 

within hyperarid zones. The multipolarization, multifrequency capabilities of SIR-C 

should allow the discrimination of sedimentary lithologies as well as relative age dating of some arid-zone Quaternary geomorphic surfaces. SIR-C may allow the determination of recent fault offsets and other tectonic expressions by noting the contrast 

in radar backscatter in units of different lithology and age separated by fault offsets; 

it is expected that these different lithologies will have distinctive polarization- and 

wavelength-dependent signatures. A polar orbit of SIR-C would allow studies of 

Precambrian shields in all continents, and improved structural mapping, both normal 

and parallel to selected fronts. Geobotanical investigations will also be possible, 

based on the dependence of plant morphology on underlying lithologies and on 

vegetation-substrate physiological interactions. Here, the images from both SIR-C 

flights would be compared to reveal seasonal differences as well as the effects of underlying lithologies. Finally, radar stereogrammetry techniques using SIR-C should 

allow the acquisition of high spatial resolution topographic data, using either interferometnc techniques or two data takes with at least a 200 variation in incidence angle. 

A wide variety of hydrologic investigations will become possible using SIR-C data, 

covering hydrologic regimes including arid, humid, wetland, snow-covered, and 

high-latitude regions. In hyperarid regimes, SIR-C will permit further investigations 

of surface penetration capability by ratioing L-band to C-band images as well as liketo cross-polarized. In semiarid regions, as well as humid regions, SIR-C will enable 

studies of temporal and spatial variability of soil moisture. Temporal studies would 

be made of sites where observations of a rain event early in the mission could be 

followed by one-day repeat coverage, thereby permitting up to 8 days of observation 

leading to the establishment of dry-down rates, etc. Spatial variability and scale in 

hydrologic systems would also be.; investigated using SIR-C data. Experiments could •' 

be conducted leading to estimats o'f SAR sensitivity to precipitation as well as 

hydrologic characteristics. SIR-C imagery would also be useful in both semiarid and 

humid regimes for identifying groundwater recharge and discharge areas. In wetland 

regimes, the use of multifrequency, multipolarization images could lead to the identification of understory land-water boundaries, an important parameter in studying 

the trace-gas fluxes and other processes of these valuable ecosystems. In snowcovered regimes, it will be possible to use the C-band and X-band channels to measure snowpack liquid water content, snow wetness, and areal extent. In northern latitudes, SIR-C images could lead to improved discrimination of glaciers, particularly 

the distribution of morainal material, crevasse patterns and ice surface roughness. It 

may also be possible to use SAR image texture for the delineation of permafrost 

boundaries. 

SIR-C will provide unique data for vegetation science studies, including the identification and mapping of vegetation types, the interpretation of landscape patterns 

and processes, the assessment of the biophysical properties of plant canopies, and the 

determination of the degree of radar penetration of plant canopies. Multifrequency, 

multipolarization data acquired on both single dates (one flight) or in seasonal pairs 

(two flights) could be used to evaluate vegetation types by crop groups, forest types, 

physioagronomic regions, weather conditions, etc. It is expected that the shorter 

wavelengths, higher incidence angles, and full polarization data sets (including phase) 

will be most useful for these purposes. SIR-C will permit quantitative studies of the 

dependence of radar backscattering coefficients on canopy biophysical properties, including productivity and phytomass or leaf area index (LAI), canopy structure, 

vi
stress, etc. It is expected that such SIR-C experiments will lead to an evaluation of 

optimal wavelengths, polarizations, and incidence angles for these purposes. By using 

the ratios of images at L-, C-, and X- band, SIR-C will lead to a much improved 

understanding of the degree of attenuation introduced by plant canopies. 

SIR-C oceanography objectives include the forecasting of ocean directional wave 

spectra, an improved understanding of internal wave-current interactions, the detection of current-system boundaries, oceanic fronts and mesoscale eddies, the relationship of ocean-bottom features to surface expressions and the correlation of wind 

signatures to radar backscatter. SIR-C, with its variable range-to-velocity ratio (via 

angle of incidence) and multiple frequencies, represents a valuable opportunity for 

designing experiments to distinguish among the various models for SAR imaging of 

the ocean surface, and to establish the degree of uniqueness between SAR-measured 

directional wave spectra and the actual ocean directional spectra. Dual-frequency 

SAR imagery of internal waves using SIR-C will present the first opportunity to acquire spaceborne images of both L-band Bragg waves (45 to 15 cm) and C-band 

Bragg waves ranging from short gravity waves (11 cm) to near-capillary waves (4 

cm). This will lead to an improved understanding of the hydrodynamics of wavecurrent interactions over a wide range of the spectrum. SIR-C will also provide the 

means for detection of current-system boundaries, oceanic fronts, and mesoscale eddies via their influence on gravity waves as described above. It is expected that images of both cold-core and warm-core rings acquired at both L-band and C-band will 

shed additional light on the SAR imaging mechanism for these phenomena. The effect of bottom topography on SAR images of the ocean surface may be explained 

both by linear wave refraction models and by the flow of oceanic currents over bottom features. SIR-C, by virtue of its sensitivity to a wider range of Bragg waves, 

will offer the opportunity to study and quantify these phenomena further. The dependence of wind signatures on SAR wavelength, polarization, and incidence angle 

should lead to an improved understanding of the mechanism of SAR response to local wind stresses. 

The SIR-C mission is especially exciting for glaciological investigations, because 

it will be the first spaceborne SAR with multifrequency, multipolarization imaging 

capabilities. This will allow valuable quantitative investigations of sea ice, lake ice, 

ice shelves, ice sheets and glaciers, and snowpacks. It will be possible to use the 

SIR-C multifrequency data with different polarizations and angles to significantly improve our understanding of sea-ice features and scattering mechanisms, and to study 

spatial variations in pack ice and ice-margin eddies. SIR-C should also allow much 

improved sea-ice type discrimination, because of wavelength and polarization sensitivity to ice geometry and chemical structure in the ice surface layers. SIR-C observations of lake ice are likewise possible, although complicated by significant returns 

from the lower ice-water interface. However, this may lead to a means for SIR-C 

baihymetry for Arctic coastal-plain lakes, using detailed studies of strong-return, 

weak-return pairs as a measure of ice thickness. As pointed out in the above 

paragraph on hydrology, SIR-C will also be useful for ice sheet and glacier boundaries as well as snowpack properties. It is very desirable to have X-band data for 

these snow studies. 

In addition to the geoscientific experiments described in the above paragraphs, it 

is expected that a number of worthwhile radar-technique related experiments will be 

possible. These include calibration experiments (the use of passive corner reflectors, 

active radar calibrators, and ground receivers), squint experiments (e.g., for oceanographic investigations of the azimuth dependence of radar backscatter), bistatic observii
vations of backscatter in connection with an underflying aircraft radar, SCANSAR (a 

technique for doubling or tripling the swath by electronically scanning the antenna 

beam between bursts), the observation of scattering statistics, and interferometric 

topography (by measuring the phase of the echo as received by two or more spatially 

separated locations of the SIR-C sensor). It may also be possible, under the proper 

conditions, to map the location, altitude and intensity of rain cells using the C-band 

channel. The SIR-C system, operated in the proper spatial orientation and pulse 

repetition frequency (PRF), may be able to measure rainfall rates in excess of about 

1 mm/second. 

The degree to which all these experiments can be successfully conducted depends 

critically on the actual SIR-C performance, particularly its radiometric and geometric 

calibration, its dynamic range, and the timing of the mission flights. Although this 

Science Plan summarizes certain performance goals (e.g., the required degree of 

calibration, dynamic range, and timing), it is recognized that fiscal constraints may 

prevent the achievement of all of these goals. Therefore, some of these experiments 

may be difficult and a few may even be impossible. However, it is expected that the 

majority of those discussed here are achievable with SIR-C. 

The SIR-C Science Working Group 

The SIR-C Science Working Group (SWG) was cochaired by Keith Carver 

(University of Massachusetts) and Charles Elachi of the Jet Propulsion Laboratory 

(JPL). Diane Evans (JPL) served as Executive Secretary. Six discipline teams were 

formed: 

Radar Techniques Team Leader: Gordon Pettengill, Massachusetts Institute of 

Technology 

Geology Team Leader: Catherine Kitcho, * NASA Headquarters 

Hydrology Team Leader: Richard Newton, Texas A&M University 

Oceanography Team Leader: Robert Beal, The Johns Hopkins University 

Applied Physics Laboratory 

Vegetation Team Leader: Fawwaz Ulaby, University of Michigan 

Ice Team Leader: Wilford Weeks, Cold Regions Research and 

Engineering Laboratory (CRREL)

Two meetings of the SWG were held: 

April 4-5, 1984 Reston, Virginia 

February 6-7, 1985 JPL, Pasadena, California 

The first meeting was used to develop a candidate series of SIR-C experiments, and 

the second to refine the resulting draft of the SIR-C Science Plan. 

SIR-C SWG Team Members and Observers who actively participated are listed 

below: 

viii
SIR-C Science Working Group 

Team Members 

NASA Headquarters 

The Johns Hopkins University Applied Physics 

Laboratory 

University of Texas, Arlington 

U.S. Geological Survey 

Jet Propulsion Laboratory 

University of Massachusetts 

Kent State University 

Jet Propulsion Laboratory 

USDA ARS Hydrology Laboratory 

Jet Propulsion Laboratory 

Jet Propulsion Laboratory 

Jet Propulsion Laboratory 

Jet Propulsion Laboratory 

The Johns Hopkins University Applied Physics 

Laboratory 

Jet Propulsion Laboratory 

Johnson Space Center 

University of Maryland 

Jet Propulsion Laboratory 

Purdue University 

U.S. Department of Agriculture 

Kansas State University 

NASA Headquarters 

Goddard Space Flight Center 

Office of Naval Research 

Environmental Research Institute of Michigan 

Texas A&M University 

U.S. Department of Commerce 

Massachusetts Institute of Technology 

University of Kansas 

University of Hawaii 

Texas A&M University 

Massachusetts Institute of Technology 

University of Maryland 

Atmospheric Environment Service 

Jet Propulsion Laboratory 

U.S. Geological Survey 

ARCO Oil and Gas Company 

Environmental Research Institute of Michigan 

University of Massachusetts 

NASA Headquarters 

University of Michigan 

Goddard Space Flight Center 

Cold Regions Research and Engineering Laboratory 

Office of Naval Research 

Miriam Baltuck* 

Robert Beal 

Andrew Blanchard 

Carol Breed 

Frank Carsey 

Keith Carver 

Richard Craig 

Charles Elachi 

Ted Engman 

Diane Evans 

Thomas Farr 

John Ford 

Mike Freilich 

Richard Gasparovic 

Richard Goldstein 

Forrest Hall 

Robert Harger 

Daniel Held 

Roger Hoffer 

Ray Jackson 

Ed Kanemasu 

Catherine Kitcho* 

Paul Lowman 

Chuck Luther 

David Lyzenga 

Marshall McFarland 

David McGinnis 

Peter Molnar 

Richard Moore 

Peter Mouginis-Mark * 

Richard Newton 

Gordon Pettengill 

Robert Ragan 

Rene Ramseier 

Barry Rock 

Gerald Schaber 

Mark Settle 

Robert Shuchman 

Calvin Swift 

Robert Thomas 

Fawwaz Ulaby 

Jim Wang 

Wilford Weeks 

Robert Winokur

*Catherine Kitcho left NASA HQ in March, 1985. Peter Mouginis-Mark (University of Hawaii) 

subsequently became Geology Team Leader; and upon his departure from NASA in July, 1986 

Miriam Baltuck (Tulane University) became Geology Team Leader.

ix
Observers/Reviewers 

Evert Attema ESA-ESTEC 

Arthur Benton, Jr. Texas A&M University 

Bruce Blanchard Goddard Space Flight Center 

Josef Cihiar Canada Centre for Remote Sensing 

John Curlander Jet Propulsion Laboratory 

Anthony England Johnson Space Center 

Ron Gelnett MARS Associates Inc. 

Robert Gurney Goddard Space Flight Center 

Philip Hard University of Stuttgart 

James Head Brown University 

Verne Kaupp University of Arkansas 

Thuy LeToan Universite Paul Sabatier de Toulouse 

Edward Link USAE Waterways Experiment Station 

Livio Marelli European Space Agency 

Robert Murphy NASA Headquarters 

John Neiber Texas A&M University 

Herwig Oettl German Aerospace Research Establishment (DFVLR) 

Jack Paris Jet Propulsion Laboratory 

Robert Prindle Earth Quest 

Keith Raney Canada Centre for Remote Sensing 

Floyd Sabins Chevron Oil Field Research 

Thomas Schmugge Goddard Space Flight Center 

Alois Sieber University of Stuttgart 

Leo Stroosnijder Agricultural University 

Kathryn Sullivan Johnson Space Center 

James Taranik University of Nevada at Reno 

Sid Theis Texas Instruments 

Diane Wickland NASA Headquarters

X
Abbreviations

ADSP Advanced Digital SAR Processor 

AIS Airborne Imaging Spectrometer 

ARS Agricultural Research Service 

AVHRR Advanced Very High Resolution Radiometer 

AVIRIS Airborne Visible/Infrared Imaging Spectrometer 

BFPQ Block Floating Point Quantizer 

bps bits per sample 

CCT computer-compatible tape 

CIR color infrared 

CRREL Cold Regions Research Environmental Laboratory 

CZCS coastal zone color scanner 

DDHS digital data handling system 

DFQP dual-frequency quad-polarization mode 

DFVLR German Aerospace Research Establishment 

DMSP Defense Meteorology Satellite Program 

DN digital number I 

EOS Earth Observing System 

ERS-1 European Remote Sensing Satellite 

ESA European Space Agency 

EST eastern standard time 

GSFC Goddard Space Flight Center 

HCMM Heat Capacity Mapping Mission 

HDDT high-density digital tape 

HDDR high-density digital recorder 

HH horizontally polarized transmission, horizontally 

polarized reception 

HPA high-power amplifier 

HV horizontally polarized transmission, vertically 

polarized reception 

IOC initial operating configuration (of EOS) 

ISLCP International Satellite Land Climatology Project 

JPL Jet Propulsion Laboratory 

JSC Johnson Space Center 

LAI Leaf Area Index

xi 
LNA low-noise amplifier 

MSS multispectral scanner (Landsat) 

NASA National Aeronautics and Space Administration 

NOAA National Oceanic and Atmospheric Administration 

NROSS Navy Remote Ocean Satellite System 

PRF pulse repetition frequency 

RBV return beam vidicon (Landsat) 

R/V range-to-velocity ratio 

RMS root mean square 

SAR synthetic aperture radar 

SASS Seasat-A Satellite Scatterometer 

SFQ single-frequency quad-polarization mode 

SIR Shuttle Imaging Radar 

SCS Soil Conservation Service 

SLAR side-looking airborne radar 

SMMR Scanning Multichannel Microwave Radiometer 

SNR signal-to-noise ratio 

SPP special purpose processor 

SSM/I Special Sensor Microwave Imager 

STALO stable local oscillator 

STS Shuttle Transportation System 

SWG Science Working Group 

TDRSS Tracking and Data Relay Satellite System 

TIMS Thermal Infrared Multispectral Scanner 

hR Thermal Infrared Radiometer 

TM Thematic Mapper (Landsat 4,5) 

TOPEX NASA Topographic Experiment 

T/R transmit/receive units 

VH vertically polarized transmission, horizontally 

polarized reception 

VLSI very large scale integration 

VV vertically polarized transmission, vertically 

polarized reception 

WMO World Meteorological Organization

xli
Contents 

Executive Summary . v 

The SIR-C Science Working Group .......................viii 

Abbreviations ............................................. xi

Chapter 1 Introduction .................................. 1-1

1.1 NASA Shuttle Imaging Radar Missions ...................1-1 

1.2 The SIR-C Mission ....................................1-2

1.3 Science Plan Organization ..............................1-5 

Chapter 2 The Role of Spaceborne Imaging Radars in 

Studies of the Earth .........................2-1 

2.1 Background .......................................... 2-1

2.2 New Challenges to Remote Sensing: Global Studies .......2-3 

2.3 The Role of Imaging Radars ............................2-4 

2.4 Evolution to the Space Station Era ......................2-4 

Chapter 3 SIR-C Sensor Characteristics ... ............... 3-1

3.1 SIR-C Technology .....................................3-1 

3.2 Sensor Description .................................... 3-2 

3.2.1 Sensor Subsystems .............................. 3-2 

3.2.2 Operational Modes .............................. 3-4 

33 Calibration ........................................... 3-8 

3.3.1 Radiometric Calibration .......................... 3-8 

3.3.2 Geometric Calibration ............................ 3-9

Chapter 4 SIR-C Geoscientific Experiments ............4-1

4.1 Introduction .......................................... 4-1

4.2 Geology .............................................. 4-1

4.2.1 Background ..................................... 4-1

4.2.2 Role of Spaceborne Remote Sensing in Geology 4-3 

4.2.3 Role of Imaging Radar in Geology ................. 4-4

 4.2.4 Scientific Basis for SIR-C Geology Experiments .....4-5 

4.2.5 SIR-C Geology Experiments ....................... 4-6

4.2.6 Summary of SIR-C Mission Requirements 

for Geology ..................................... 4-26

xl" 
4.3 Hydrology . 4-28 

4.3.1 Background ..................................... 4-28

4.3.2 Role of Spaceborne Remote Sensing in Hydrology 4-33

4.3.3 Role of Imaging Radar in Hydrology ...............4-33 

4.3.4 Scientific Basis for SIR-C Hydrology Experiments 4-35 

4.3.5 SIR-C Hydrology Experiments .....................4-43 

4.3.6 Summary of SIR-C Mission Requirements 

for Hydrology ................................... 4-53

4.4 Vegetation Science .................................... 4-55 

4.4.1 Background ..................................... 4-55 

4.4.2 Role of Spaceborne Remote Sensing in Vegetation 

Science........................................ 4-55 

4.4.3 Role of Imaging Radar in Vegetation Science ....... 4-56 

4.4.4 Scientific Basis for SIR-C Vegetation-Science 

Experiments .................................... 4-56 

4.4.5 SIR-C Vegetation Science Experiments ............. 4-60 

4.4.6 Summary of SIR-C Mission Requirements 

for Vegetation Science ........................... 4-65

4.5 Glaciology ............................................. 4-66

4.5.1 Background ..................................... 4-66

4.5.2 Role of Spaceborne Remote Sensing in Glaciology 4-67

4.5.3 Role of Imaging Radar in Glaciology ...............4-68 

4.5.4 Scientific Basis for SIR-C Glaciology Experiments 4-69 

4.5.5 SIR-C Glaciology Experiments .....................4-71 

4.5.6 Summary of SIR-C Mission Requirements for 

Glaciology ...................................... 4-80

4.6 Oceanography ........................................ 4-83

4.6.1 Background ..................................... 4-83

 4.6.2 Role of Spaceborne Remote Sensing 

in Oceanography ................................4-84 

4.6.3 Role of Imaging Radar in Oceanography ............4-85 

4.6.4 Scientific Basis for SIR-C Oceanography 

Experiments .................................... 4-85

4-86 4.6.5 SIR-C Oceanography Experiments .................

 4.6.6 Summary of SIR-C Mission Requirements 

for Oceanography ...............................4-97 

Chapter 5 SIR-C Sensor Experiments ...................5-1 

5.1 Introduction .......................................... 5-1

5.2 SIR-C Calibration Experiments ..........................5-1 

53 Novel Sensor Experiments .............................5-2 

5.3.1 Squinting ....................................... 5-2

5.3.2 Bistatic Observations ............................5-2 

5.3.3 SCANSAR ...................................... 5-3
5.3.4 Scattering Statistics Investigations ................5-3 

5.3.5 Interferometric Topography .......................5-3 

5.3.6 Observations of Rain Cells .......................5-6 

Chapter 6 SIR.0 Data Collection and 

Image Processing ........................... 6-1 

6.1 Site Recommendations ................................ 6-1 

6.2 Mission Timing Recommendations ...................... 6-1 

6.3 Data Acquisition and Processing ......................... 6-2 

6.4 Data Products ........................................ 6-5 

6.4.1 Level 0 Products ................................ 6-6 

6.4.2 Level 1 (Survey) Products ......................... 6-6 

6.4.3 Level 2 (Standard) Products ....................... 6-8 

6.4.4 Level 3 (Special) Products ......................... 6-8 

6.5 Data Distribution ....................................... 6-9 

Chapter 7 Summary ..................................... 7-i

7.1 SIR-C Geoscientific and Sensor Experiments ............. 7-i 

7.1.1 Geology ........................................ 7-i 

7.1.2 Hydrology ...................................... 7-2 

7.1.3 Vegetation ...................................... 7-3 

7.1.4 Glaciology ...................................... 7-4 

7.1.5 Oceanography .................................. 7-4 

7.1.6 SIR-C Sensor Experiments ........................ 7-5 

7.2. Recommended Mission Parameters and Sensor 

Performance ........................................ 7-6 

7.2.1 Orbital Parameter and Mission Timing ............. 7-6 

7.2.2 Swath Widths and Resolutions .................... 7-7 

7.2.3 Frequencies, Polarizations, and Incidence Angles 7-7 

7.2.4 Radiometric Calibration .......................... 7-7 

7.2.5 Data Products ..................................... 7-7

Appendix A: Introduction to Radar Scattering ......... . A-i 

A.i Introduction .......................................... A-i

A.2 The Radar Backscattering Coefficient .................... A-i

A.3 SAR Image Intensity (Tone) ............................. A-i

A.4 SAR Image Speckle (Texture) ........................... A-2

A.5 Surface and Volume Scattering .........................A-5 

A.6 Surface Scattering Mechanisms ......................... A-6

A.7 Volume Scattering Mechanisms ......................... A-8

xv 
Appendix B: Radiometric Calibration of the SIR-C 

System .................................... B-i

Appendix C: References .................................C-i 

Figures 

1-1. Evolution of spaceborne SAR missions from Seasat 

toEOS ......................................... 1-2 

1-2. Wavelength, polarization, and angle of incidence 

SAR imaging parameters ......................... 1-3 

1-3. Potential SIR-C coverage of the earth as compared to 

Seasat, SIR-A, and SIR-B ......................... 1-4 

3-1. Block diagram of the SIR-C sensor ................ 3-3 

3-2. Schematic diagram of the distributed antenna ...... 3-4 

3-3. SIR-C operation in the dual-frequency quad-polarization 

mode.......................................... 3-5 

3-4. Dependence of swath width on angle of incidence, in both 

single- and quad-polarization modes ............... 3-6 

3-5. Dependence of swath width on angle of incidence, 

number of channels, and number of bits in the 

a) low-resolution mode, and b) high-resolution mode 3-7 

3-6. Maximum incidence angle achievable by SIR-C ...... 3-8 

4-1. Distribution of different types of permafrost 

terrain in the Northern Hemisphere ................ 4-9 

4-2. Examples of dendritic stream networks, viewed by 

SIR-A from above South America .................. 4-10 

4-3. SIR-13 image of the Ganges floodplain in 

Bangladesh ..................................... 4-12 

4-4. SIR-A image and Landsat view of the hyperarid 

region of the Libyan Desert ....................... 4-13 

4-5. Comparison of Landsat Thematic and aircraft L-band 

multiple-polarization radar images of the Wind River 

Basin in Wyoming ................................ 4-14 

4-6. Two lava flows from the Snake River Plain, Idaho .... 4-16 

4-7. Backscatter from volcanic materials, illustrating 

the differences in radar characteristics of the two 

Snake River flows shown in Fig. 4-6................ 4-17 

4-8. Recognition of variations in the surface texture of 

different geologic materials, using multi polarization 

radar images .................................... 4-18

xvi
4-9. Part of the San Andreas fault system in California, 

as detected by the Seasat SAR on the basis of 

surface-material roughness ....................... 4-19 

4-10. Diagram of a possible method by which fault 

displacements could be measured by SIR-C ........ 4-20 

4-11. SIR-B image of the Grenville front in Canada ........ 4-21 

4-12. A floodplain in the Amazon forest, Amazonas, 

Brazil.......................................... 4-23 

4-13. The role of vegetation coverage in affecting radar 

returns from the Savannah River Plant, 

South Carolina .................................. 4-24 

4-14. Examples of radar-derived topography obtained from 

SIR-A and SIR-B ................................. 4-25 

4-15. Characteristics of hydrologic regimes .............. 4-29 

4-16. Global distribution of arid and wetland environments 4-31 

4-17. a) A comparison of soil-moisture data showing an 

agricultural area about 60 km southwest of Fresno, 

California, as imaged by SIR-B, b) a0 vs. soil moisture 

in the top 5 cm as derived from this image ......... 4-32 

4-18. Average dependence of radar backscattering on soil 

moisture in the top 5 cm measured as percent of 

field capacity .................................... 4-37 

4-19. Surface reflectivity .............................. 4-39 

4-20. The re-reflection effect ........................... 4-40 

4-21. Spectral response of o0 for wet and dry snow ....... 4-42 

4-22. Calculated variation of a°HH with depth for a dry snow 

layer containing ice particles 1 mm in radius ....... 4-43 

4-23. Penetration into dry sand covering ancient 

river beds ...................................... 4-45 

4-24. SIR-B image of flooded forest in coastal Ecuador 4-48 

4-25. SIR-13 image of Florida wetlands .................. 4-50 

4-26. Microwave response to leaf area index (LAI) ........ 4-56 

4-27. Radar response to various wavelengths according to 

the size distribution of canopy scatterers ........... 4-57 

4-28. The role of frequency in canopy backscatter ........ 4-58 

4-29. Loss factor of wheat canopy ...................... 4-59 

4-30. Role of polarization in canopy penetration .......... 4-59

A!lI] 
4-31. Illustration of how multi polarization images may be 

combined to enhance discrimination among different 

target categories in a forest environment ........... 4-61 

4-32. Radar temporal signature of winter wheat .......... 4-62 

4-33. Interactions between radar and different ice types 4-70 

4-34. Seasat SAR image of pack ice in the Beaufort Sea 4-73 

4-35. Seasat SAR image of the ice island T-3 ............ 4-74 

4-36. SAR image showing the breakup of fast ice in the 

vicinity of Banks Island and Prince of Wales Strait . 4-75 

4-37. Seasat SAR images that reveal an eddy in the ice near 

the ice edge in the Beaufort Sea .................. 4-75 

4-38. X/L-band comparison of pack ice .................. 4-76 

4-39. Variations in SAR imagery of sea ice, with changes 

in polarization ................................... 4-77 

4-40. Seasat SAR image of the Alaska Range ............ 4-81 

4-41. Spatial evolution of a SAR-measured wavenumber 

over a 900-km Seasat pass ......................... 4-88 

4-42. Seasat azimuth wavenumber falloff in a high sea 

state ............................................ 4-89 

4-43. SIR-B image of the New York Bight ................ 4-90 

4-44. SAR image of an area 100 km long, taken during a pass 

over the western half of a large warm-water ring less 

than a month before the ring began to merge again 

with the Gulf Stream ............................. 4-92 

4-45. This Seasat SAR image of an area 100 km long, taken 

from above Nantucket Shoals, provides a dramatic 

example of bathymetric expressions occasionally 

evident over large areas .......................... 4-93 

4-46. Seasat SAR image of an area 100 km long, located just 

outside the entrance to Chesapeake Bay ............ 4-95 

4-47. Comparison of SAR- and scatterometer-derived wind 

magnitudes ..................................... 4-96 

4-48. Comparison of wind-direction estimates from both the 

scatterometer and the SAR ....................... 4-97 

5-1. Geometry for SAR interferometry .................. 5-4 

5-2. Composite made from two Seasat passes, separated 

by 3 days, near Baker, California .................. 5-5 

6-1. Altitude vs. orbital inclination for various orbital 

exact-repeat cycles .............................. 6-2

xviii
6-2. Potential ground tracks for an orbit with a 700 

inclination ...................................... 6-3 

6-3. Potential ground tracks for an orbit with a 921 

inclination ...................................... 6-3 

6-4. Optimum SIR-C mission times for each science 

investigation .................................... 6-4 

6-5. SIR-C data downlink path ......................... 6-4 

6-6. Block diagram of the SIR-C processing system—ADSP 

custom hardware is shown in dashed box .......... 6-5 

6-7. Functional block diagram of the image-formatting 

algorithm used by the ADSP ...................... 6-6 

6-8. Expected schedule for SIR-C image products ....... 6-7 

A-i. Correspondence of the radar backscatter coefficient 

for the (I,]) in the scene, to the (I,]) digital number 

in the processed image .......................... A-i 

A-2. Probability density functions for the mean of N 

Rayleigh-distributed variables ..................... A-i 

A-3. Surface scattering from (a) rough water surfaces 

and (b) calm water surfaces, and volume scattering from 

(C) high-loss vegetation canopies and (d) low-loss 

vegetation canopies ............................. A-i 

A-4. Penetration depth of (a) loamy soil and (b) snow as a 

function of liquid water content [A-i, Volume 11, 

Section 11-5] .................................... A-2 

A-5. Two configurations of height variations: (a) random height 

variations superimposed on a periodic surface, and 

(b) random height variations superimposed on a flat 

surface ......................................... A-6 

A-6. Surface scattering by (a) tangential facets and (b) Braggresonant sinusoidal ocean waves, where path length 

R is an integral number of half wavelengths ....... A-7 

A-7. Typical angular variations of the polarized scattering 

coefficient for a slightly rough surface ............. A-8 

A-8. Angular variation of ,° for surfaces of varying 

roughness ...................................... A-9 

A-9. An illustration of volume scattering ................ A-9 

A-b. Hypothetical size distribution of canopy scatterers .. A-b

xix 
Tables 

3-1. SIR-C sensor characteristics ......................3-1 

4-1. Examples of SIR-C research topics ................ 4-2 

4-2. Some SIR-C geology experiment classes ........... 4-6 

4-3. Some SIR-C hydrology experiment classes .......... 4-44 

4-4. Some SIR-C vegetation science experiment classes 4-62 

4-5. Some SIR-C glaciology experiment classes ......... 4-71 

4-6. Some SIR-C oceanography experiment classes ...... 4-87 

6-1. SIR-C data products ............................. 6-7 

B-i. Dominant error sources for absolute calibration of 

SIR-C .......................................... B-2 

B-2. Shuttle-pointing determination error (in roll axis) .... B-2 

B-3. Worst-case radiometric error from pointing uncertainty 

(evaluated at edge of 16-km swath for roll uncertainty 

of 0.660) B-3 

B-4. Dominant error sources for relative calibration of 

SIR-C .......................................... B-4 

B-5. Relative multichannel calibration error sources 

for SIR-C ....................................... B-4

xx
Chapter 1 

Introduction 

1.1 NASA Shuttle Imaging Radar Missions

expanded In recent years, it has become clear that one of the most important problems confrontglobal ing earth scientists is that of understanding the earth as a system, and that an integrated, 

perspectives multidisciplinary approach with new, more powerful observing techniques is needed. The 

central objective of such an approach would be to improve our understanding of those 

processes governing the biogeochemical, climatic, and hydrologic cycles of the earth. This 

would require, in turn, that we understand the atmospheric, biospheric, hydrospheric, 

cryospheric, and solid-earth components of the earth system, and that we develop new instrument systems and missions that could provide global data sets. The approach requires 

the expanded global perspective that can be obtained only through novel satellite and remote sensing systems whose performance has been much improved over current systems. 

Spaceborne microwave remote sensing offers such an expanded view of the earth for 

geoscientific research, supplementing the information obtainable in the visible and infrared 

spectrum. The Shuttle Imaging Radar (SIR) missions, which provide microwave images of 

the earth, are a vital element of NASA's earth observations program. Besides valuable 

scientific information, these missions are yielding significant advances in spaceborne imaging radar technology. 

an evolving The successful SIR-A and SIR-B missions have demonstrated that such scientific obsequence of jectives as geologic mapping, regional hydrologic studies, and radargrammetric contouring 

experiments can be accomplished using imagery collected during a one-week mission and with a single 

wavelength and polarization. These Shuttle missions have also shown that there is a significant advantage in flying, retrieving, modifying, and reflying synthetic aperture radar 

(SAR) sensors of progressively increased sophistication. In fact, the SIR missions may be 

viewed as an evolutionary sequence of experiments that, for relatively low cost, will greatly 

enhance our understanding of the role of wavelength, polarization, and angle of incidence, 

for a variety of geoscientific applications. 

optimum Two additional Shuttle Imaging Radar missions, SIR-C and SIR-D, are planned for the 

radar 1990's. These missions will use an imaging radar with new, more powerful capabilities and 

parameters will test multiparameter SAR technology as well as provide new scientific information. The 

missions will also allow geoscientists to determine which radar parameters are optimal for 

studying polar ice morphology, oceanic winds and waves, geomorphology, vegetation patterns and processes, and hydrologic environments. At the same time, SIR-C and SIR-D will 

permit new technologies to be incorporated into the design of a next-generation imaging 

radar with significantly enhanced flexibility and reliability. Because of these technological 

advances, the SIR-D radar can be reused directly on the Earth Observing System (EOS) 

polar orbiting platforms being planned for launch in the early 1990's.

1-1 
1.2 The SIR.0 Mission 

The SIR-C mission, which will provide a powerful new tool for scientific studies of the 

earth, is a significant step forward in the evolution of an advanced spaceborne imaging 

radar. It will provide 

(1) The first opportunity to use simultaneous multifrequency radar imagery from space 

for geoscientific studies of the earth as a planet 

(2) The first spaceborne high-resolution imaging sensor with a simultaneous multipolarization capability 

(3) The first multiparameter polar orbiting imaging radar, which will supply coverage 

during two different seasons 

In addition to these scientific firsts, SIR-C will also feature several significant technological innovations, a test-bed for distributed solid-state radar technology, and near realtime processing with the JPL Advanced Digital SAR Processor (ADSP). 

SIR-C is part of a series of spaceborne imaging radar missions (Fig. 1-1) that began with 

evolution of the June 1978 launch of the Seasat SAR and continued with the November 1981 SIR-A and 

SA R missions October 1984 SIR-B missions. The SIR-C and SIR-D missions will result in an instrument 

to be used on the EOS polar platform. The initial operating configuration (IOC) for the 

EOS platform is currently scheduled for a 1993 launch. SIR-C/D will be flown in the early 

1990's. During this same general period, the L-band ERS-1 SAR (Japan), the 

C-band ERS-1 (ESA), and the C-band Radarsat SAR (Canada) would also be flown. These 

latter missions are primarily focused on particular applications (geologic mapping, ocean 

wind/wave mapping, and ice mapping, respectively) and have fixed parameters. By contrast, 

the NASA instruments are multiparameter SARs for use in several geoscientific applications. 

YEAR 178179180 1811821831841851 86J87 1 88 1 89 1 90 1 91 1 92 193 

SEASAT 

SIR-A _ 

SIR-B

SIR-C 

SI R-D 

EOS 

S = START F = FLIGHT E = END 

Fig. 1 .1. Evolution of spaceborne SAR missions from Seasat to EOS 

1-2
SIR-A and Both the SIR-A and SIR-B sensors were derived from the Seasat SAR, and all three 

SIR-B were operated at L-band (1.275 GHz) with HH polarization (horizontally polarized transparameters mission, horizontally polarized reception). The Seasat SAR used a fixed 23° angle of incidence, and SIR-A used a fixed 500 angle. SIR-B provided, for the first time, the capability to mechanically tilt the antenna so that multiple angles of incidence could be obtained. 

Thus, SIR-B was the first spaceborne radar to provide flexibility in the incidence angle 

parameter. This has allowed a significant improvement in our understanding of radar backscatter models and also has permitted investigations of new radar stereo techniques for 

topographic applications. 

SIR-C In addition to multiple angles of incidence (15°-55°), the SIR-C mission will provide 

parameters multiple wavelength (L-band, C-Band, and potentially X-band through the addition of the 

German X-SAR instrument) and multipolarization capability (HH, VV, HV, and VH) for 

L-band and C-band, thereby significantly enhancing the instrument's flexibility. These 

three illumination parameters (wavelength, polarization, and angle of incidence) may be 

thought of as a three-dimensional instrument parameter space, as suggested in Fig. 1-2. As 

shown, Seasat, SIR-A, and SIR-B were limited to a fixed wavelength, although SIR-B 

allowed the angle of incidence to be varied. The range of parameters allowed by the SIR-C 

mission is as shown by the shaded box: 6- and 23-cm wavelengths (and possibly 3-cm), all 

linear polarization states (HH, VV, HV, and VH) at C- and L-bands, and 15°-55° angles 

of incidence. SIR-C will not only provide images of the magnitudes of HH, VV, and 

cross-polarized returns, it will also provide images of the phase difference between HH 

and VV returns.

ANGLE OF INCIDENCE 

60 

50t 

TRANS. REC. 

IIH — —' 

VV

T1 

HV —aHX vi- W 

HV' 23 

VH\ N 

N N L

(ci,,) 

SIR-C

SIR-8

SIR-A A 

SEASAT • 

Fig. 12. Wavelength, polarization, and angle of incidence SAR 

imaging parameters, and the range of parameters covered by 

Seasat and SIR

1-3 
15' TO 

CIR

15-1060-km 

- SWATH 

WIDTH 

Figure 1-3 illustrates the potential SIR-C mission coverage of the earth. The SIR-C mission includes two flights, thereby providing seasonal coverage of vegetation and hydrologic 

environments. The swath width varies from 15 to 90 km, and digital data will be stored onboard or relayed to the ground via the Tracking and Data Relay Satellite System (TDRSS) 

data link.

(b)

ARCTIC OCEAN

rGREENLAND 

AMERICA 

- 

ji 

/ -V.. - 

P AC IFIC 

S.

- 

OCEANSOUTH 

AMERICA OUT 

ANTARCTIC OCEAN

OCEAN 

LI LU 

0 

> 

0 U 

-J 

z 

0

ASIA 

AFRICA " 

INDIAN 

OCEAN 

AUSTRALIA

SIR-A COVERAGE - - - - SEASAT COVERAGE 

SIR-B COVERAGE 

Fig. 1-3. Potential SIR-C coverage of the earth in a 570 orbit and a 900 orbit as 

compared to Seasat, SIR-A, and SIR-B, showing the global distribution of data 

coverage 

1-4
In a polar orbit, SIR-C would thus have the potential to image virtually any area of the 

earth including the polar regions. (SIR-B was limited to ±57 0 latitude, and SIR-A to 

±380.) 

A more detailed discussion of SIR-C instrument characteristics is presented in Chapter 3 

of this Science Plan. 

1.3 Science Plan Organization 

chapter 

descriptions

This SIR-C Science Plan provides broad guidelines for the organization of the SIR-C 

mission, and a general description of geoscientific experiments that are possible with 

SIR-C. Chapter 2 of this plan discusses the role of spaceborne imaging radars in earth observations, with particular emphasis on the evolution and scientific importance of the SIR 

missions. The challenges to remote sensing posed by global system models are discussed, 

along with a delineation of how spaceborne radar imagery will be used to gather important 

global data. 

The third chapter provides a detailed description of the SIR-C instrument. 

Chapter 4, which is the heart of this plan, presents a more detailed discussion of various 

geoscientific experiments that could be conducted with SIR-C, and the types of results that 

could be expected. This chapter is divided into separate sections on geology, hydrology, 

vegetation science, glaciology, and oceanography. Each of these sections seeks to answer 

the following questions: 

(1) What are the general scientific problems for which remote sensing data are considered helpful? 

(2) What is the specific role of imaging radar? 

(3) What is the potential contribution of SIR-C and what kinds of experiments would 

be useful? 

These general experiment descriptions are intended to provide guidance in the design of 

specific experiments. The discussions here are meant to be illustrative of the type of investigations that the science community believes will yield significant advances in our understanding of the earth as a system. It is expected that meaningful SIR-C experiments may be 

conducted that are not specifically discussed in this plan. 

Chapter 5 discusses those technique-related experiments that may be conducted with 

SIR-C, including both sensor and data-processing investigations. 

The sixth chapter outlines the general mission plan for SIR-C, with particular emphasis 

on data collection and image processing. 

Chapter 7 provides a summary of the geoscientific and sensor experiments suggested for 

SIR-C and also summarizes the required mission parameters and sensor performance. 

A tutorial discussion of the fundamentals of radar scattering, with particular emphasis on the 

roles played by wavelength and polarization in both surface and volume scattering, and a 

discussion of SIR-C radiometric calibration are presented as appendices.

1-5
Chapter 2 

The Role of Spaceborne Imaging Radars 

in Studies of the Earth 

2.1 Background 

Seasat Although airborne imaging radars have been used for geologic mapping for over twenty 

years, the era of spaceborne remote sensing with imaging radars began in June 1978 with 

the launch of Seasat. This unmanned spacecraft carried five sensors, including a SAR, in a 

circular orbit with an inclination of 108 0 and an altitude of 800 km. The Seasat SAR was 

operated at 1.275 GHz (L-band), with a single HH polarization, and a fixed look angle of 

200. After only 100 days of operation, Seasat was silenced by a power-system failure. 

However, during that time, a massive amount of SAR data was obtained that is still being 

analyzed. The SAR data were relayed from Seasat to a limited number of ground stations, 

which provided partial coverage of North America, Central America and the Caribbean, 

and Western Europe. The total surface area imaged was about 108 km2 . All Seasat SAR 

images were optically correlated, and many were digitally correlated into 100- x 100-km 

scenes [2-1]. 

Seasat results Although Seasat was launched primarily for oceanographic studies, the SAR images 

have been used for both oceanic and land studies, and atlases of Seasat SAR images have 

been published [2-2, 2-3]. Seasat SAR images have confirmed that microwave imaging radars are very sensitive to the geometric patterns, forms, and shapes of the earth's surface, 

as well as to changes in dielectric properties of earth materials, particularly soil moisture 

properties and ice—water boundaries. 

Seasat SAR images of the ocean have shown a strong correlation between SAR image 

brightness and the amplitude of 30-cm surface waves, which in turn are directly responsive 

to the local wind. Moreover, analyses have suggested that SAR ocean imagery contains information at least occasionally related to the local wind direction. Seasat has provided an 

extensive series of images of the Beaufort seacoast of the Arctic Ocean, and this series has 

been used for studies of ice dynamics and icepack features. However, it should be pointed 

out that there was no ground verification of the Beaufort Sea features during the Seasat 

mission, because of the difficulty of surface operations during the Arctic summer. 

Seasat SAR images of the land surface have been used for geologic mapping, particularly 

for obtaining structural information, and for other surface morphology investigations. In 

regions of high relief, Seasat SAR images show a strong image distortion due to radar 

layover; in areas of gentle slope, on the other hand, there is a strong sensitivity to subtle 

changes in relief. The layover for mountainous regions is due to the steep (23°) angle of 

incidence chosen for accentuating oceanic surface features. These images have also been 

used for investigating soil moisture, hydrologic characteristics, urban morphology, and 

vegetation cover. 

SIR-A mission The NASA Shuttle Imaging Radar program has provided an opportunity to extend imaging radar observations through a series of brief missions of 7 to 10 days each. The Shuttle 

Imaging Radar-A (SIR-A) experiment was conducted during the 2-day flight of the Space

2-1
Shuttle Columbia in November 1981 [2-4]. The SIR-A sensor used Seasat technology and 

thereby used the same wavelength (23 cm) and polarization (HH). However, there were 

two significant instrument changes, the first being that the angle of incidence was changed 

to a fixed 50°, and the second that all data were optically recorded and correlated. The 

SIR-A mission was primarily for geologic mapping investigations, and the moderate incidence angle greatly diminished the geometric distortion of high-relief regions as encountered with Seasat. 

SIR-A results 

SIR-B mission 

SIR-B results

In addition to its use for geologic mapping, SIR-A provided other key results including the imaging of buried drainage channels in a hyperarid region of southern Egypt (a 

demonstration that many arid-region morphologic features are better depicted in radar imagery than in Landsat images), the imaging of cloud-covered tropical regions, and the 

repetitive observation of dynamic ocean phenomena. SIR-A images consisted of long photographically reproduced swaths about 50 km wide. Approximately 10 km2 of the earth's 

surface was imaged with 40-m resolution for selected passes between latitudes ranging 

from about 41° N to 36° S. 

Although SIR-A images provided new and scientifically important results, quantitative 

data analyses were difficult because of both the optically correlated images and the limited 

dynamic range imposed by the optical film. Moreover, the fixed incidence angle of 50° 

chosen by the team of geologists was not optimum for oceanic surface studies or for other 

hydrologic investigations. 

The next Shuttle Imaging Radar experiment, SIR-B, took place during Oètober 1984, 

with the launch on the Space Shuttle Challenger of a modified and extended version of the 

SIR-A sensor. SIR-B, like SIR-A, used a fixed 23-cm wavelength and a fixed HH polarization. However, SIR-B added the capability of changing the angle of incidence and also 

provided a means for digitally recording and processing the SAR images. The sensor's 

data system provided for onboard digitization of the radar echoes and for data transmission 

to the ground at 46 Mb/s through the TDRSS; the data system also provided a digital 

recording backup through a 30 Mb/s onboard tape recorder. Due to a failure of the 

Shuttle-TDRSS communications antenna system, almost all of the SIR-B data were recorded on the tape recorder, thereby leading to a greatly reduced swath. Swath widths of 

SIR-B data range typically from 10 to 50 km, depending on incidence angle. 

One of the key scientific objectives of the SIR-B experiment was to demonstrate the 

capability of stereo imaging. This was successfully achieved over a number of sites. Stereo 

images were used to generate a digital topographic data base of Mount Shasta. Further, 

computer processing allowed the generation of perspective views of the mountain from 

multiple look directions (see the upper right image on the front cover). This demonstrates 

the enormous potential of using spaceborne stereo radar data for three dimensional analyses of the surface morphology of the earth (and the planets). 

Over a number of sites, multi-incidence-angle imagery was used to classify terrain units 

by deriving their "angular signature." This technique has been used to derive vegetation 

maps of the Cordon la Grasa region in western Argentina, to classify the forest cover of a 

test site in Baker County in northern Florida, and to classify the lava-flow types near the 

Kilauea Crater in Hawaii. These results are very encouraging, opening the possibility of 

using "imaging radar angular scatterometry" in a manner similar to visible and IR imaging spectroscopy for the classification of surface units. 

2-2
2.2 New Challenges to Remote Sensing: Global Studies 

discipline-specific I Remote sensing as a science has developed over the years through instruments and techsatellites niques developed for specific geoscientific disciplinary problems. Most of the satellite remote sensing programs have been aimed toward one or two disciplinary objectives, i.e., 

Nimbus for meteorology and oceanography, Landsat for vegetation and rock type discrimination, Seasat for oceanography, GOES for meteorology, etc. The results obtained from 

these satellite remote sensing programs have provided a first global glimpse of the earth as 

a system and have been used by scientists in established disciplines in concert with data 

obtained by more conventional means. Certainly "single-discipline" satellites will be 

launched in the future, including the U.S. Upper Atmospheric Research Satellite for atmospheric studies, the Canadian Radarsat for polar ice mapping, the Japanese ERS- 1 SAR 

for geologic mapping, and the European ERS-1 for ocean applications. 

multidisciplinary As mentioned in Section 1.1, one of the most important problems confronting earth 

approach scientists is that of understanding the earth as a system. This enterprise will require not 

only an expansion of the capabilities of current remote sensing instruments (imaging spectrometers, SARs, radiometers, etc.) but also the ability to merge images acquired from 

different instruments and to deliver global data sets in a timely fashion. It is clear that 

most of these needs are best met by observations from polar-orbiting satellites, but that 

there are enormous problems in downlinking, processing, delivering, archiving, and 

analyzing such global data sets. 

We do not yet know what the optimum spectral channels are for many geoscientific 

problems of interest, although much progress has been made in recent years. In the microwave regime, for example, although we generally understand that L-band or C-band is best 

for soil moisture estimation, we do not know which frequencies or polarizations are optimum 

for ice type discrimination, we have not had an opportunity to test for optimum vegetationdiscrimination frequencies from satellite altitudes, and we do not fully understand which 

wavelengths are best for the measurement of oceanic surface features. The synoptic view 

from space is critical to improving our understanding, since there is uniform illumination 

(a constant angle of incidence) across the swath, and much better long-term instrument 

calibration is maintained, thereby permitting quantitative studies of surface morphology. 

multisensor Remote sensing of the earth becomes most effective when observations are made in all 

approach portions of the electromagnetic spectrum and over long periods of time. Terrain and 

oceanic surface features have distinctive signatures in the visible, infrared, and microwave 

portions of the spectrum and usually have strong temporal characteristics that vary over 

periods ranging from hours to years. The history of satellite remote sensing is composed 

largely of missions primarily aimed at specific geoscientific problems for which sensors 

operating in a single portion of the spectrum were used. Broadly speaking, visible and 

shortwave infrared wavelengths are used when sensitivity to surface chemistry is required 

(e.g., the Landsat Thematic Mapper), the thermal infrared is used for sensitivity to surface 

temperature (e.g., the Heat Capacity Mapping Mission), and the microwave spectrum is 

used for sensitivity to surface morphology (e.g., Seasat).

2-3 
2.3 The Role of Imaging Radars 

sensitivity to Synthetic aperture radars operating at satellite altitudes provide high-resolution images 

surface that are sensitive to surface geometry or morphology and to the presence of water in its 

morphology liquid or frozen states. Since the atmosphere introduces essentially no attenuation at the 

and water longer microwave frequencies (L-, C-, or X-bands), a spaceborne SAR provides an allweather imaging capability that is independent of sun angle. 

geologic Imaging radars have been shown to be very useful for geologic mapping and are espemapping cially sensitive to structural features and changes in lithology. Radar images also have 

been used to study very subtle geologic features related to tectonic activity and to find 

buried drainage systems in the Eastern Sahara. 

canopy SAR imagery is also useful for vegetation studies and is sensitive particularly to canopy 

morphology morphology and biomass. Moreover, when SAR imagery is combined with visible imagery 

(e.g., Seasat with Landsat), vegetation classification accuracy is greatly increased. 

soil moisture Because of the high dielectric constant of water (approximately 80) and low dielectric 

constant of dry soil (approximately 3), SAR imagery of terrain is responsive to changes in 

soil moisture. For this reason, SAR has enormous potential for use in various aspects of 

hydrology research where soil moisture is of importance. The sensitivity of SAR imagery 

to surface relief is also of interest to hydrologists studying watershed characteristics, 

runoff, percolation, etc. 

ice dynamics The Seasat SAR showed that radar imagery is very useful for studies of polar-ice dynamics, and it is expected that multiwavelength and multipolarization SAR imagery will 

also provide valuable information on sea-ice types as well. SAR imagery is also useful for 

studying freshwater ice and glaciers. 

ocean surface SAR imagery acquired at L-band and C-band is sensitive to the short gravity waves 

features (e.g., 30-cm wavelength) on the ocean surface, which are in turn modulated by the longer 

gravity waves and surface winds. SAR imagery of the ocean is in fact quite sensitive to 

changes in the surface geometry, which may be related to winds, waves, bathymetry, internal waves, or eddies.

2.4 Evolution to the Space Station Era 

EQS SIR-C is a logical step toward active microwave observations of the earth from the 

Earth Observation System (EOS), a series of satellite platforms and related information 

systems associated with the Space Station. As currently conceived, EOS would consist of 

several polar-orbiting unmanned platforms to be launched in the 1990s, each carrying various combinations of remote sensing instruments. These sensors would provide nearsimultaneous observations of the earth in the visible, the shortwave infrared, the thermal 

infrared, and the microwave portions of the spectrum. The major scientific objective of 

EOS is to provide global data sets for geoscientific studies of the earth as a system. 

2-4
SIR-C will provide the first opportunity to understand the optimum wavelengths, polarizations, and illumination geometries for SAR imagery of the earth and will also provide a 

technology test-bed leading directly to a multiparameter SAR design for use on one or 

more of the EOS platforms. It is expected that SIR-C will be followed by SIR-D, a 

Shuttle-borne multiparameter SAR that would be virtually identical to the EOS SAR.

2-5
Chapter 3 

SIR-C Sensor Characteristics 

3.1 SIR-C Technology 

SIR-C 

improvements

The baseline design characteristics of the SIR-C sensor as compared to Seasat, SIR-A, 

and SIR-B, are described in Table 3-1. The principal improvements in the SIR-C sensor 

over SIR-B are: an additional wavelength band (C-band), multiple polarization capability 

(HH, VV, HV, VH) including the phase difference between HH and VV, dual bandwidth 

capability, electronic beam steering, and the capability to maximize the swath width at 

various look angles by exciting different segments of the antenna. In addition, an X-band 

VV-polarized SAR will be added to this mission by DFVLR (German Aerospace Research 

Establishment, Federal Republic of Germany). 

Table 3-1. SIR-C sensor characteristics 

Parameters Seasat SIR-A SIR-B SIR-C

Mission date 1978 1981 1984 1990 

Orbital altitude 800 km 259 km 225 km 225 km 

Orbital inclination 108° 38° 57° ^57° 

Frequency 1.28 0hz 1.28 GHz 1.28 GHz 1.25 GHz' 

5.3 GHzC 

9.6 GHZb 

Polarization HH HH HH HH (L C) 

VV (L C X)b 

VH (L C) 

HV (L C) 

Incidence angle 23° 50° 15°-55° 15°-55° 

Swath width 100 km 50 km 20-50 km 15-90 kmc 

Azimuth resolution 25 m (4 look) 40 m (6 look) 30 m (4 look) 30 m (4 look)c 

Range resolution 25 m 40 m 58-17 m 60-10 mc 

Peak power 1 kW 1 kW 1 kW 3.8 kW (L) 

2.1 kW (C) 

3.3 kW (X)b 

Bandwidth 19 MHz 6 MHz 12 MHz 10 or 20 MHz 

Optical data collection 42 hours 8 hours 8 hours N/A 

Digital data collection 42 hours N/A 8 hours 50 h/channel, 

5 channels 

aApproximate 

b Xband VV-polarized SAR to be added by DFVLR 

cBased on preliminary design parameters

3-1 
distributed 

SAR

Because the SIR-C Science Working Group has recommended a cross-polarized capability 

at large angles of incidence (discussed later in this plan), a distributed radar approach will 

be implemented for SIR-C. A distributed SAR has an advantage over a conventional SAR 

because numerous low-power (solid-state) transmitters, distributed across the antenna aperture, 

are used instead of a single high-power transmitter. Since large power losses typically occur 

in the corporate feed of a conventional antenna, as much as an eight-fold improvement in 

efficiency can be obtained using a distributed SAR. In addition, a solid-state distributed system 

has a high inherent redundancy and potentially extended lifetime compared to a conventional 

single-source approach. Another advantage of a distributed antenna is that electronic scanning 

in both range and azimuth is more easily implemented than with a conventional antenna. 

The power, redundancy, and scanning requirements for SIR-C are similar to those for the 

proposed EOS SAR. 

3.2 Sensor Description 

3.2.1 Sensor Subsystems 

block diagram Figure 3-1 is a block diagram of the SIR-C instrument. The sensor will be composed 

of several subsystems: the antenna array, the exciter, the receivers, the data-handling network, and the ground SAR processor. The SIR-C design will allow a very flexible selection of operating modes and is further described below. 

antenna The antenna is composed of two planar arrays, one for L-band dual-polarized operation 

and the other for C-band dual-polarized operation. Each array is composed of a uniform 

grid of dual-polarized microstrip antenna radiators, each polarization port of which is fed 

by a separate corporate feed network. The overall size of the antenna is 12.0 x 4.0 m, 

with the L-band aperture being 12.0 x 2.9 m and the C-band aperture 12.0 x 0.7 m. 

distributed Amplification of the radar pulses (both transmitted and received) will be accomplished in 

TIR units distributed fashion, with solid-state high-power amplifiers (HPA), low-noise amplifiers 

(LNA), and 4-bit phase shifters distributed across the array as shown in Figure 3-2. A 

transmit/receive (T/R) unit is assigned to 18 microstrip elements distributed along the long 

dimension of the antenna. This will allow the antenna beam to be electronically steered, 

thereby eliminating the need for mechanical steering and providing much more flexibility 

during the mission for imaging at various incidence angles. 

To achieve even more flexibility, SIR-C will provide a choice of partial aperture or full 

aperture. This choice involves either exciting a portion of the antenna's short dimension or 

exciting the entire aperture. The use of a portion of the aperture increases the antenna 

beamwidth and increases the swath width at near-nadir incidence angles. 

transmitter The transmitter peak power is 3.8 kW at L-band and 2.1 kW at C-band. As previously 

performance pointed out, this peak will be achieved by combining in a coherent fashion the output from 

18-element subarrays of microstrip elements on the antenna surface. Each solid-state 

amplifier is driven through a corporate feed network by a central radar exciter, one exciter 

for each frequency. The exciter output is a train of chirped pulses with a 33-is pulse width 

and a pulse repetition frequency (PRF) that varies from approximately 1200 to 1800 Hz.

3-2
ARRAY L—BAN D 

QQQ H QcQQQ 1—BAND H RECEIVER 

Qc 

QQQQ 

V C

1—BAND V RECEIVER QQQQ RADAR RECEIVER IDDHS C—BAND EXCITER SWITCHING ARRAY H C-BAND H RECEIVER F___________ 

u a F V QQOC RECEIVER —BAND V DATA STEERING 

I HDRR I I HDRR 2 11 TDRS J SHUTTLE HDDT GROUND TAPE DATA ON FILM AGES PROCESSOR SAR EPHEMERIS TAPE DIMAGES I Q_ ONCCTs CCI 

Fig. 3-1. Block diagram of the SIR-C sensor

receiver and 

data handling

depending on Shuttle altitude and system configuration. The bandwidths of the chirp modulator are 10 and 20 MHz at both L-band and C-band. The C-band exciter signal carrier will 

be derived from the L-band signal by frequency synthesis techniques. 

Four solid-state receivers (back ends) are planned, two for L-band and two for C-band. 

The radar echoes from each receiver are routed through a receiver switching network to 

four digital data handling system (DDHS) networks, as shown in Figure 3-1. These will 

then be directed to onboard 100-Mb/s tape recorders or through the Shuttle-TDRSS 

Ku-band 50-Mb/s data link. This combination of real-time (TDRSS) or delayed-time (taperecorder) data steering allows coverage of virtually any location on the earth over which the 

Shuttle flies. 

ground 

processor

Data tapes either brought back with the Shuttle or recorded through TDRSS will be 

processed at JPL using the ADSP, leading to processed SAR images in both computercompatible tape (CCT) and film formats.

3-3 
PORTION OF 9 PANEL ARRAY,SHOWING ONE OF THE SUBPANELS 

TOTAL 

OF 

18 ROWS

NOTE THERE ARE 2 SUBPANELS PER FREQUENCY PER PANEL 

T/R MODULE SCHEMATIC

Fig. 3.2. Schematic diagram of the distributed antenna 

3.2.2 Operational Modes 

As mentioned above, the SIR-C sensor will be capable of operating in a number of different modes. Two of these modes are of particular interest, as they represent a novel way 

of acquiring simultaneous multipolarization data. These modes are the single-frequency 

quad-polarization mode (SFQP) and the dual-frequency quad-polarization (DFQP) mode. 

3-4
SFQP mode 

DFQP mode 

swath width 

limitations

The single-frequency quad-polarization mode operates as follows. First, the antenna is 

excited so that one polarization (H for example) is transmitted. The resulting echoes are 

received by both receivers (H and V), resulting in HH and HV data. A second pulse 

excites the other polarization (V for example) so that it is transmitted, and again the echo 

is received by both receivers, resulting in VH and VV data. The process is then repeated 

one pulse repetition period (l/PRF) later. This process provides coherent and fully 

registered 4-polarization imagery. The disadvantage of this procedure is that the radar 

must operate at twice the normal PRF, thus limiting operation to lower look angles than 

would be indicated by the antenna-imposed range-azimuth ambiguity limit (see discussion 

below). 

The dual-frequency quad-polarization mode, which is shown schematically in Figure 3-3, 

is similar, with the exception that both L- and C-band H transmitters are activated simultaneously, followed by the V transmitters. The resulting data rate is, of course, twice that 

of the single-frequency quad-polarization data, which results in a narrower swath width 

(see below).

TRANSMIT PULSES 

LH- I • / LHH\ I LVH\I /LHH\ fLVH\ I L-H 

DATA WINDOWS 

Lv-_ /\I/\ nHV I/\ L-V 

uJ

_

U 

> 

CH- I/\ (\I/\ C-He 

LU

CV- I /CHV\ I/cw\ /CHV\ I/Cvv\ I C-V 

Fig. 3-3. SIR-C operation in the dual-frequency quad-polarization 

mode 

3.2.2.1 Swath Width 

The ability of SIR-C to acquire data simultaneously at multiple frequencies and polarizations will substantially increase its flexibility for conducting geoscientific research. 

However, as more simultaneous channels (frequencies and polarizations) and increased 

dynamic range are sought, the swath width decreases. 

At near-nadir incidence angles, the swath width is limited by the beamwidth in the crosstrack plane of the antenna pattern. At large incidence angles, the swath width can be limited 

by the data rate that can be accommodated by the Shuttle-TDRSS digital link or the Shuttle tape recorders. The data-rate-limited swath for a given range resolution is inversely 

proportional to the product of the number of channels, the number of bits per sample 

(bps), the PRF, and the sine of the incidence angle. Figure 34 illustrates the dependence 

of the swath width on incidence angle for the SFQP and DFQP modes with varying numbers of bits per sample, and for both high and low resolutions.

3-5 
100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

SINGLE FREQUENCY 

DUAL POLARIZATION' 

JR-f I

I i1 

LOW RESOLUT ION I 

-HIGH RESOLUTION1 

4 bps 

bps 

10 20 30 40 50 60

INCIDENCE ANGLE

SINGLE FREQUENCY 

QUAD POLARIZATION2 

Ui1lLIMJ 

LVKNnEMMMMMM 

MEWSOMMENE EMENSWENEM 

10

MENEMENEEM

20 30 40 50 60

INCIDENCE ANGLE

DUAL FREQUENCY

QUAD POLARIZATION 

USE

•uvuui• 'EMEM

ONFEENE on 

10 20 30 40 50 60

INCIDENCE ANGLE 

100 

ff 90 

80

2 70

60

c40 

IJJ

30 

20 

10 

0

1 SAME FOR DUAL FREQUENCY, SINGLE POLARIZATION 

2 SAME FOR DUAL FREQUENCY, DUAL POLARIZATION 

Fig. 3-4. Dependence of swath width on angle of incidence, in both single- and quad-polarization modes. 

At near-nadir angles, the swath width is antenna-beamwidth limited, and at large angles of incidence the 

swath width is data-rate limited 

Figure 3-5 is a more graphic representation of the dependence of swath width on the 

number of channels, the number of bits, resolution (bandwidth), and the incidence angle. 

The number of bits per sample determines the dynamic range of the radiometric intensity 

of the recorded echo. The 8-bit dynamic range of the SIR-C images is expected to be 

about 40 dB, with a 10 dB signal-to-noise ratio (SNR). A 4-bit quantization level would 

reduce the dynamic range to approximately 17 dB. Because of the data-rate limitation, increasing the dynamic range (number of bits) results in a decreased swath width at moderate 

to high incidence angles. For example, in the SFQP mode at a 55° incidence angle, 8-bps 

sampling will result in a 26-km swath width whereas 4-bps sampling will increase the 

swath width to about 56 km at low resolution. 

BFPQ Based on recommendations of the SIR-C Science Working Group, a Block Floating 

Point Quantizer (BFPQ) will be implemented on SIR-C. This technique offers a means for 

increasing the swath and also obtaining an effectively larger dynamic range. As the radar 

echoes are received, a determination is made periodically (every few milliseconds) as to 

which portion within the total dynamic range most needs to be sampled. This portion is 

then digitized with a relatively small rate (e.g., 4 bps) and recorded. For weak radar 

echoes from a smooth surface, for example, the 4-bps sampling window would be applied 

to the lower portion of the total dynamic range; for strong radar echoes from a rough surface, the 4-bps sampling window would be applied to the upper portion of the total dynamic range. In this way, an effective sampling rate of 8 bps or more is achieved, while 

maintaining the capability to adequately sample the entire dynamic range within the datarate limitations. The only possible disadvantage of the BFPQ technique is for rare cases 

where there is an abrupt change from a weak target to a strong one, as for example with 

the boundary from water to land; in this case, the 4-bps sampling window may be set for 

low returns from the water surface, so that strong onshore returns may be saturated. Practical experience with simulated BFPQ images acquired by aircraft SAR data suggests, 

however, that this effect is minimal. 

3-6
INCIDENCE 

ANGLE 

fti^=== 

Iiijiaiii '"I1IIL1tI 4 bits 8 bits 4 bits 8 bits 

S INGLE

 

QUAD-POL (2) N, IN' INEEMI NIN

47km 30k. 

4 bits 8 bits 4 bits 8 bits 4 bits

'it, 

DUAL 

FREQUENCY

- 6iI1IU a . -. 

4 bits 8 bits 4 bits 8 bits 

DUAL 

FREQUENCY 

SINGLE

POLARIZATION I M\ 

IN

4 bits 8 bits 4 bits 8 bits 

SINGLE 

ENCY 

QUAD-POIL (2)

4 bits 8 bits 4 bits 8 bits 4 bits 8 bits 

DUAL 0 

FREQUENCY

(IT SAME FOR SINGLE FREQUENCY, DUAL POLARIZATION MODE 

(2) SAME FOR DUAL FREQUENCY, DUAL POLARIZATION MODE 

Fig. 3-5. Dependence of swath width on angle of Incidence, number of 

channels, and number of bits In the a) low-resolution mode, and b) high. 

resolution mode

3-7 
C-BAND

OCEAN TARGETS 

V

I

VEGETATION 

TARGETS 

}

GEOLOGIC 

TARGETS

L-BAND

3.2.2.2 Maximum Incidence Angle 

backscatter 

assumptions

The maximum look angle achievable for single- and quad-polarization data takes for 

various natural targets is shown in Fig. 3-6. Most of the backscatter models used to assess 

SIR-C system performance were based on scatterometer data. The ocean models were 

based on computed maximum and minimum radar backscattering coefficients from the 

ocean for wind speeds of 2 m/s and 24 m/s and look directions (azimuth) of 90° and 1800 

relative to the wind vector [3-1]. The C-band geology models were based on maximum 

and minimum radar backscattering coefficients from over 50 data sets acquired for many 

types of bare rock surfaces [3-2]. The L-band geology models were based on maximum 

and minimum radar backscattering coefficients from 50 airborne scatterometer data sets 

acquired from many geological surfaces. The vegetation models were based on maximum 

and minimum radar backscatter coefficients from over 160 truck-mounted scatterometer 

data sets.

10 20 30 40 

INCIDENCE ANGLE, de

OCEAN TARGETS 

VEGETATION 

TARGETS 

GEOLOGIC 

TARGETS 

50 60 70 

V AMBIGUITY LIMIT FOR QUAD-POLARIZATION MODE 

MEMO AMBIGUITY LIMIT FOR DUAL-POLARIZATION MODE 

JI!ffIIIHhII LIKE-POLARIZED 

I••I III III! CROSS-POLARIZED 

Fig. 3.6. Maximum incidence angle achievable by SIR.0 

3.3 Calibration

3.3.1 Radiometric Calibration 

relative vs. 

absolute 

calibration

The radiometric calibration of a SAR establishes a relationship between SAR image 

intensity and the radar backscattering coefficient, a', of the imaged surface. (For a discussion of 00, see Appendix A, Section 2). Both relative and absolute calibration are important. The relative calibration of the SAR establishes how precisely one measurement can 

be related to another, while absolute calibration establishes the accuracy of the measurement of 00. The relative calibration of a system accounts for changes or instabilities in its 

subsystem parameters, such as gain drifts in amplifiers. Absolute calibration takes into account biases and the absolute gain of the antenna and receiver. It establishes the constant K 

in the relationship I = Ka', where I is the SAR image intensity of an extended target. 

3-8
Absolute calibration leading to accurate measurements is required for comparing results 

from different radar systems such as the Seasat SAR and the SIR-C SAR. However, for 

many geoscientific studies, good relative calibration of the SAR is much more important 

than its absolute calibration. Relative calibration allows quantitative comparative studies of 

the radar backscattering coefficients of vegetation, ice, geomorphic surfaces, etc., over 

widely dispersed geographic regions, or of the same surface on different days. 

Many of the SIR-C experiments described in Chapter 4 will require good relative 

calibration (to 1 dB or better), and some experiments will also require good absolute 

calibration (to 3 dB or better). The calibration requirements for these experiments are discussed in greater detail in Chapter 4. 

calibration A discussion of the contributors to errors in the accuracy of SIR-C is presented in 

approaches Appendix B. Basically, achievement of good radiometric calibration will require two

approaches: 

(1) Calibration of individual radar components (antenna, T/R units, establishment of 

exact range to target, etc.) 

(2) The use of corner reflectors and active calibrators at some of the test sites 

Although it is likely that several test sites will have a set of corner reflectors and active 

calibrators, it is impractical from both a logistic and economic point of view to expect that 

each test site will be so instrumented. This, then, requires that the SIR-C subsystems be as 

accurately calibrated as possible and that the exact in situ antenna pattern, peak gain, and 

antenna pointing be accurately known. It also requires that the transfer characteristics in 

both the receive and the transmit modes for all T/R units be known for the cold-space environment, where large temperature excursions may be encountered as the Shuttle executes 

various roll maneuvers from earth-pointing to cold-space pointing. 

These are difficult engineering design and test problems. However, if maximum scientific 

returns from SIR-C are to be achieved, the instrument must exhibit good stability over the 

life of the mission, images must have good radiometric fidelity across the swath, and it 

must be possible to relate digital number (DN) values in the image to the absolute radar 

backscattering coefficient, a°. 

3.3.2 Geometric Calibration 

The geometric calibration of a SAR image establishes the relative geometric fidelity of 

surface features (e.g., agricultural fields or ice floes), and the absolute location accuracy 

of these features on a cartographic grid. The establishment of good relative geometric fidelity in a SAR image involves various routine image-processing steps such as correcting 

for image skew generated by the data-taking geometry and correcting for the variation of 

ground range resolution as a function of the angle of incidence. Good absolute geometric 

calibration requires accurate knowledge of the Shuttle position (ephemeris data) and/or the 

use of known ground control points found in the SAR image. 

requirements Radargrammetry experiments require knowledge of the slant range to the target, and the 

Shuttle position to within one resolution cell. Although other experiments do not require this 

degree of geometric accuracy, images acquired at multiple frequencies and polarizations 

must be co-registered to within one pixel. Since the pixel size will be identical for the 

L- and C-band systems, this should be achievable with SIR-C.

3-9
Chapter 4 

SIR-C Geoscientific Experiments 

4.1 Introduction

This section presents a discussion of some geoscientific experiments that could be conducted using SIR-C, and is organized by discipline: geology, hydrology, vegetation 

science, glaciology, and oceanography. The motivation for conducting these experiments is 

described in Sections 4.2-4.6. Each of these sections enumerates several geoscientific objectives and seeks to place SIR-C in context by addressing the following questions: 

fundamental (1) What are the scientific motivations for the research objectives, and what are the 

questions backgrounds of these objectives? 

(2) What role does remote sensing in general play in conducting these research 

investigations? 

(3) What is the specific role of imaging radar? 

(4) What is the scientific basis for the use of SIR-C? 

(5) What specific experiments could be conducted using SIR-C? 

(6) What are the recommended parameters (orbit, mission timing, swath widths, 

frequencies, data products, etc.) for SIR-C? 

Some of these specific research topics and experiments are summarized in Table 4-1. 

4.2 Geology

4.2.1 Background

global geologic The primary objective of the SIR-C geology experiments is to improve our understanding 

processes of geologic processes worldwide through time. The key experiments that can be pursued 

with SIR-C include investigations of cold-region geomorphology, fluvial geomorphology, 

rock weathering, erosional processes and geochronology, lithologic mapping and stratigraphy, regional tectonics, geobotany, and radar stereo/topography. Also, topographic data 

can be derived from SIR-C and used to conduct geomorphic analyses in a diverse range of 

study areas. 

spaceborne Many of the geologic problems for which we are seeking answers today are complex 

remote sensing and reach beyond those that can be solved by ground-based mapping techniques. Investigaand the tions of these problems often require a multidisciplinary approaáh and are likely to involve 

multidisciplinary related fields such as hydrology, botany, oceanography, and geophysics. Some investigations 

approach require the ability to penetrate beneath surficial cover such as vegetation, soil, or alluvium. 

Still others are currently not possible simply because research cannot be conducted in particular remote regions. The scale at which geologic investigations are conducted varies 

from tens of meters to hundreds of kilometers. Coastal-sedimentation and delta-formation 

studies, for example, may require information covering a few kilometers of coastline, 

while comparative regional tectonic studies may require data for continent-sized areas. 

Spaceborne imaging radars can provide valuable data for many such investigations.

4-1 
Table 4. 1. Examples of SIR-C research topics 

Geology 

Cold-region geomorphology 

Fluvial geomorphology 

Lithologic, rock-weathering, and 

geochronology studies 

Regional tectonic studies 

Geobotanic studies 

Radar stereo/topography studies 

Hydrology 

Delineation of subsurface hydrologic 

features in hyperarid regions 

Delineation of geohydrologic 

characteristics 

Watershed runoff modeling 

Groundwater resource analysis 

Delineation of wetland boundaries 

Estimation of snow cover and 

water equivalent 

Mapping of permafrost areas and 

determination of permafrost's distance 

beneath surface

Vegetation science 

Identification and mapping of vegetation and 

crop types 

Interpretation of landscape patterns and processes 

Assessment of biophysical properties of plant canopies 

Determination of canopy penetration 

Modeling of vegetation structure and canopy processes 

Glaciology 

Sea-ice feature verification 

Ice drift and deformation experiments 

Spatial variations in pack-ice characteristics 

Lake-ice feature verification 

Bathymetry of lakes 

Ice-shelf and glacier boundaries 

Snow return characteristics 

Oceanography 

Ocean-wave forecasting 

Internal waves 

Currents, fronts, and eddies 

Bottom signatures 

Wind signatures 

Incorporating selected test-site field measurements with SIR-C imagery would greatly 

enhance geologic investigations by indirectly providing quantitative results. This approach 

would aid the interpretation of radar data and would help develop more refined quantitative models of microwave/surface interaction characteristics. Data sets from other remote 

sensors could also enhance the geologic interpretation of SIR-C imagery, particularly highresolution imagery acquired in the visible, near-infrared, and thermal infrared wavelength 

regions. 

specific 

objectives

Several specific objectives have been identified as warranting a concerted investigation 

using spaceborne instruments such as SIR-C and advanced multispectral sensors. For these 

objectives, it is recommended that investigators should formulate their studies in such a 

manner as to extrapolate geologic/geomorphic investigations from the local scale to a scale 

that is either regional or global in extent, thereby taking advantage of the near-global 

coverage of the radar. A focus on the interpretation of geologic processes and the testing 

of geologic models is emphasized. 

An example of such a study is the analysis of local tectonic features as a way of providing information on continental or global deformational processes associated with plate tectonics. The tectonic evolution of continent-sized areas can often be addressed by the analysis 

of specific structural features associated with plate boundary zones. Other investigations 

could concentrate on weathering processes (such as those associated with the erosion of 

lava flows or alluvial fans), with the primary objective of quantifying temporal changes in 

the morphological characteristics of Quaternary deposits. In turn, these studies could provide an insight into recent climatic change. 

4-2
Testing the hypothesis that the land surface carries the record of geologically recent tectonic and climatic processes is a second key focus. In this context, the identification of the 

time-scale over which a landscape has evolved (from tens of years to millions of years), 

and the implications for life (in terms of climate, ecology, hydrology, and waste disposal) 

are stated goals. Specific problems that could be addressed might be the 

(1) Determination of the age scales of geomorphic development 

(2) Response of landforms to climatic change 

(3) Response of landforms to tectonic perturbations 

(4) Weathering rates of different lithologic units 

(5) Connections between the lithology and ecology of a region 

The investigation of ancient drainage channels in hyperarid deserts is an example of this 

form of analysis, wherein observed features are used to interpret geologic processes and 

climatic changes that have operated over the last few thousand years. 

utility of Spaceborne radars have proven to be very useful for geologic investigations. The Seasat 

Seasat, SIR-A, SAR, SIR-A, and SIR-B all provided high-quality imagery that has been used for structuraland SIR-B geology studies, lithologic discrimination, topographic mapping, subsurface hydrology, 

data etc., over angles of incidence ranging from 200 to 55°. Geologic analysesand interpretations of the image data acquired by each of these missions have demonstrated the effects 

of incidence angle on SAR imagery. At the low angle of incidence used with the Seasat 

SAR (23°), the radar backscatter is very sensitive to topography. At the higher angle of 

incidence used with SIR-A (500 ), the backscatter is dominated by surface roughness, 

which in turn provides lithologic-discrimination capabilities. As mentioned in Chapter 2, 

the multiple look angle capability of SIR-B (15 '-55 ') has shown the relationship between 

angle of incidence and radar backscatter for different geologic surfaces and has, in addition, provided the means of stereo radar mapping. 

two SIR-C Most geologic remote sensing has the common objective of producing a map upon 

flights needed which subsequent interpretations can be based. In view of the great diversity of rock types, 

weathering environments, and vegetation cover, the selection of optimum SIR-C radar 

parameters for each specific target remains to be determined prior to regional mapping. 

This means that two SIR-C flights will be required. The first SIR-C flight would test as 

many radar parameters as possible in order to identify an optimum set of parameters for 

specific sites. The second SIR-C flight would then employ these optimum parameters in a 

mapping mode to acquire SAR data over larger contiguous regions. Two SIR-C flights 

would also allow temporal or seasonal coverage of geologic targets. The capability for 

viewing cold-region geomorphic features at different times of the annual freeze-thaw cycle, 

and river delta flooding bef6re and during maximum river discharge, would supply data 

for two of several possible experiments. -

4.2.2 Role of Spaceborne Remote Sensing in Geology 

Landsat Geologic applications of remote sensing data really began with the interpretation of 

black-and-white aerial photographs. Such photographs were of tremendous use to geologists 

in conducting field mapping, not only for logistical purposes, but also for focusing on

4-3 
imaging 

spectrometers

structures, outcrops, or geologic anomalies that required detailed field investigation. Geologists were among the first to use satellite multispectral images provided by ERTS (later 

Landsat) in 1972. These early Landsat investigations provided the first visible/near-infrared 

views of large or regional structural features such as faults and folds, geologic contacts 

expressed as vegetation contrasts or moisture differences, and areas of geochemical alteration affecting vegetation and soil. The multispectral data provided by Landsat have been 

augmented in recent years by imaging spectrometers such as the Airborne Imaging Spectrometer (AIS) and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). These 

instruments enable scientists to identify, as well as discriminate, among rock types. 

More recent Landsats (4 and 5) have included a 100-m-resolution thermal band, and the 

Heat Capacity Mapping Mission (HCMM) free-flyer included a 600-m-resolution thermal 

band. Thermal infrared images are useful for mapping variations in surface emissivity and 

for the derivation of thermal inertia [4-1]. Data acquired by the thermal band of the 

Thematic Mapper (10.42-11.66 m) and by the airborne Thermal-Infrared MultispecTIMS tral Scanner (TIMS) [4-2] have been used for identifying certain rock mineralogies and 

thermal plumes associated with water discharge in coastal and lacustrine environments. 

Thermal measurements made by these instruments may be of value for volcanology, for 

the detection of ground water seeps, and for geothermal exploration. However, as with 

visible detectors, thermal data can only be acquired during cloud-free conditions. 

4.2.3 Role of Imaging Radar in Geology 

independence 

from weather, 

sun angle 

penetration

Imaging radars are used for geologic investigations mainly because of the enhanced sensitivity of such radars to topography, surface roughness, and material dielectric properties 

that are related to lithology, structure, geologic age, geobotanic phenomena, and geomorphology. Radar imagery's independence from weather and sun angle allows geologists to 

study many remote and inaccessible regions. Seasat, SIR-A, and SIR-B have already 

demonstrated the utility of SAR imagery for investigating previously unmapped regions or 

humid areas that are obscured by cloud cover. In a study of a hyperarid region of the 

Eastern Sahara, SIR-A demonstrated the capability of an L-band SAR to penetrate through a 

meter or more of dry sand and alluvium and reveal previously unmapped bedrock features 

as well as regionally extensive but buried fluvial topography [4-31. The SIR-C mission 

offers an opportunity to further exploit for geologic mapping the penetration capability of 

imaging radar and to test the usefulness of various combinations of wavelength, incidence 

angle, and polarization for identifying rock types and structures, geomorphologic and 

geobotanic relationships, and the ages of geologic surfaces. 

Geologic experiments will require specific combinations of swath width, resolution, polarization, wavelength, and perhaps seasonal considerations, depending upon the type and 

scale of work proposed. For example, a mapping project requiring large swath widths with 

a uniform look angle and no gaps in coverage will not be compatible with experimental 

objectives requiring varying combinations of wavelength, polarization, and look angle. 

However, with the two flights of SIR-C, it may be possible to plan experiments to fulfill 

both types of objectives. 

4-4
4.2.4 Scientific Basis for SIR-C Geology Experiments

basis for The scientific basis for the use of SIR-C data in geology experiments is founded upon 

SIR-C geology several essential points: 

experiments

(1) The dual-wavelength capability will allow studies of the roughness of geomorphic surfaces, as well as of the wavelength dependence of vegetation cover. 

(2) The inclusion of full polarization capability will allow studies of surface and 

volume scatter for the discrimination of rock and ice types and for 

geochronology studies. 

(3) The capability to image a given area with several angles permits stereo 

radargrammetry and therefore topographic studies. 

(4) The high-latitude orbit will allow some studies of cold-region geomorphology. 

models of Because of the extreme complexity of most geomorphic surfaces, it is very difficult to 

backscatter construct mathematical radar backscatter models that have any real exactitude. However, a 

number of models of simpler geometries will offer guidance in the quantitative interpretation of SIR-C imagery. For example, we know that certain surfaces that appear to be 

smooth at L-band will appear to be rough at C-band, if the surface roughness falls within 

a certain range. Surface roughness has both a small-scale and a large-scale component. 

Rayleigh A surface with small-scale random height excursions about a reference flat datum will 

criterion appear to be smooth to a radar system if its root mean square (rms) height, hrms, satisfies 

the modified Rayleigh criterion:

X 

hrms< 32 cos O 

where X is the electromagnetic wavelength and 0 is the angle of incidence. Assume that 

SIR-C is operating at a 500 angle of incidence. This means that at C-band (X = 6 cm), 

any surfaces with an rms roughness greater than about 3 mm will appear to be rough. At 

L-band (X = 23 cm), any surface with an rrns roughness greater than about 1 cm will 

appear to be rough. If now the angle of incidence is changed to 20°, these upper limits for 

smooth surfaces will change to 4 mm at C-band and 1.5 cm at L-band. This would seem 

to imply that virtually all geomorphic surfaces are rough at L-band and C-band. 

geometrical However, this simple modified Rayleigh criterion does not consider the larger-scale 

optics roughness of datum undulations, tilts, bumps, and slopes that a radar images. In fact, most 

of the scattering accounting for texture in SAR images of geomorphic surfaces can be accounted for by geometric optic reflection and scattering from rocks, boulders, slopes, etc. 

The radiometric brightness of a 30- X 30-rn pixel within a SAR image is the result of the 

coherent addition of the contributions from many individual scatterers within the pixel. 

Thus, the image texture or appearance of smoothness (assuming negligible speckle) over, 

say, a 1-km2 area would be a measure of the spatial homogeneity of the scatterers within 

each of the image's pixels. At some level of large-scale surface roughness, the image will 

appear to be smooth at L-band and rough at C-band. One of the objectives of some of the 

SIR-C geology experiments might be to establish what that level of large-scale roughness 

is, and how it can be used to discriminate levels of rock weathering, volcanic flow blockiness, etc.

4-5 
depolarization When radar energy is incident upon terrain containing multiple scatterers, the resulting 

backscattered energy tends to be depolarized, i.e., it has both a like-polarized and crosspolarized component. In fact, the ratio of cross to like polarization can be used as a measure of the degree of multiple scattering, and from that a measure of the surface roughness 

can be obtained. This multiple scattering is more often associated with volume scattering 

from leaves, branches, etc., in a vegetation canopy, or with brine inclusions or air bubbles 

in multiyear ice, and is thus useful as an indicator of vegetation or ice morphology. 

However, depolarization also is associated with certain rough surfaces, although the exact 

relationship has not yet been determined. SIR-C will offer an opportunity to study this effect and to determine its utility for the classification of geomorphic surfaces. 

experiment 

classes

4.2.5 SIR.0 Geology Experiments 

This section describes six different classes of geology experiments that could be conducted 

with SIR-C. This list, summarized in Table 4-2, is not meant to be all-inclusive, but is 

provided simply to give a general description of the nature of geology experiments and 

how SIR-C data might be used in these investigations. The examples build on experience 

gained in past or current studies performed with airborne SAR and with Seasat, SIR-A, 

and SIR-B. SIR-C will be more flexible than previous imaging radar systems and will 

offer many new opportunities to study new geologic problems that are not included in this 

document.

Table 4-2. Some SIR-C geology experiment classes 

Experiment class Scientific objectives 

Cold-region geomorphology Glacial landforms, permafrost 

Fluvial geomorphology Stream networks, hydraulic properties of stream flow, flood 

mapping, buried ancient drainage networks 

Rock weathering, erosional processes Weathering properties of sedimentary rocks, rates of erosion 

and deposition, studies of Quaternary fluvial deposits, relative 

age dating of Quaternary geomorphic surfaces, characterization 

of lava-flow types, discrimination of sedimentary lithologies 

Tectonics and geologic boundaries Structural mapping of large-scale geologic features, such as 

terrains, Precambrian shields, fold mountain belts, faults, 

and rates of fault slip 

Geobotany Discrimination of geologic units in extensive vegetated areas, 

using image texture and multifrequency and multipolarization 

radars 

Radar stereo/ topography experiments Topographic mapping, studies of slope evolution, structural 

deformation and volcano and ice-sheet volumes

supersites The "supersite" concept has been developed to help focus investigators' attention on a 

limited number of key geologic targets that could form the basis of several different 

studies. The exact location of these supersites will be chosen to suit the scientific objectives of the SIR-C Science Team. As a general rule, however, it is recommended that 

4-6
(1) At least two of the sites include young, relatively vegetation-free areas, of which 

one might be for geochronological studies (e.g., the U.S. Southwest), and the other 

a young volcanic region (e.g., Hawaii or the Snake River Plain) for processrelated investigations 

(2) A polar region (most likely within Alaska) be selected for the study of periglacial 

features 

(3) A geobotanic supersite might be selected in conjunction with other vegetation 

studies, but that forests within the U.S. Northeast and Europe should be suitable for 

investigating vegetation stress due to acid rain and effects on community composition due to rock lithology 

4.2.5.1 Cold Region Geomorphology 

As exploratory and exploitative activities extend further into the polar regions, there is 

an increasing need to understand the natural processes peculiar to these environments and 

to assess the impact of human activities on these processes. Polar environments are commonly cloud-covered during the time of the year when thawing occurs. Abrupt changes in 

geomorphic processes accompany this transition period from freeze to thaw. Some of the more 

notable changes are in the flow regime of rivers and glaciers, in the rate of shoreline erosion, 

and in solifluxion. Satellite imaging radars provide imagery that is weather-independent, 

unconstrained by sun angle, and has partially controllable illumination angles. Such radars 

are therefore ideal for observing and monitoring polar surfaces and surface processes, 

especially during critical periods of seasonal change. Studies are needed to 

glacial land form (1) Evaluate the use of SAR images for glacial landform mapping and interpretation 

studies needed (2) Determine the optimum radar frequency, polarization, and illumination angle for 

glacial landform mapping 

(3) Assess the advantages of variable or multiple look angles and frequencies, 

especially for the perception of landforms of low relief such as thermokarst, 

permafrost, patterned ground, etc. 

(4) Evaluate the synergism of SAR (e.g., Seasat, airborne, SIR-C) and optical/JR 

images of comparable resolution (e.g., Landsat TM) 

(5) Compare the potential uses of SAR and other forms of remotely sensed images for 

monitoring glacier movements, coastal erosion, floodplain development, etc. 

Penetration of glacial ice by radar depends critically on the amount of liquid water in 

the ice and on the salinity of the ice (or the nature of the snow, in upper levels), and 

probably on included rock material such as medial moraines in flowing ice. It is expected 

that in areas of low moisture content there may be some penetration if the ice is very thin, 

permitting study of underlying bedrock structure. 

In a polar orbit, SIR-C would be the first multiparameter radar system available with 

which to investigate the Antarctic. Due to the adverse climate, long periods of darkness, and 

the extreme physical difficulty of working on the Antarctic continent, a radar system could provide extensive baseline information on a number of geologic and glaciologic problems. For example: 

Antarctic (1) Some areas receive virtually no rain or snow fall, and are free from glacial ice. 

soils The very low temperatures in Antarctica have permitted a soil structure to form that 

is totally unlike that found in more temperate climates. Both the radar signature of

4-7
glacier 

dynamics 

mapping 

permafrost

this material, and the potential for penetration by the radar signal are important to 

pedologists for studying cold-climate soils, and important to planetary geologists 

who use these areas as analogs for Mars. It is not known whether radar penetration 

could be achieved in these areas because as yet there have been no data acquired of 

these regions; however, the concept lends itself to a SIR-C experiment. 

(2) Many of the structures found in ice sheets are too small to be observed on Landsat 

MSS or TM and yet provide important constraints on glacier dynamics and are 

controlled by underlying topography. Pressure ridges, fractures, and the amount of 

rock debris at or near the surface of the ice may all be detected by SIR-C, providing the first synoptic view of the ice sheet from its source regions to its eventual 

demise at its snout or as a series of icebergs at the coastline. 

(3) The extent of continuous and discontinuous permafrost is of special interest to 

geomorphologists. The transition from one type of permafrost to another may be 

temperature dependent, thus permitting a radar system to provide an indirect measure of annual temperature by obtaining data at a single instant in time. Study of 

the process and the rate of formation of permafrost would also be of great value to 

the geomorphic sciences if SIR-C data were used to establish a time baseline for the 

distribution of permafrost features. In order to provide more complete estimates of 

periglacial processes, it is important to develop an understanding of permafrost 

relief patterns and how they relate to subsurface lithology and structure in these 

regions. By analyzing relief and topographic patterns evident from SIR-C data, and 

comparing them with ancillary geologic data compiled from mapping and drilling, 

it may be possible to study this geomorphic relationship. 

Figure 4-1 illustrates the distribution of several permafrost environments in the Northern 

Hemisphere. Comparable geomorphic features exist in the Antarctic, but their distribution 

across the continent has not yet been fully investigated. It is not yet known what relationship there is between zones of continuous and discontinuous permafrost, and underlying 

geologic structure, if any. Radar coverage of an area with cold-climate landforms may allow 

geologists to study this relationship, and also to identify the effects of a multifrequency, 

multipolarization system on mapping in such regions. The basis for radar sensitivity to 

permafrost is discussed further in Section 4.3.5.5. 

watershed 

stream 

networks

4.2.5.2 Fluvial Geomorphology 

The potential for applying, spaceborne radar data to the analysis of fluvial processes lies 

in the radar's ability to easily distinguish open bodies of water (including rivers) from surrounding terrain, to display subtle relief features associated with the boundaries of 

watersheds, and to allow textural analysis of landforms produced by downslope movement. 

Potential experiments that can be performed with SIR-C data from diverse geologic environments include the following: 

(1) Dendritic streams and tributary patterns have been found to be readily identifiable 

on spaceborne radar images (Fig. 4-2). In the case where stream and river beds are 

active, the roughness of the bed (which, in youthful streams, should possess many 

exposed boulders) and an increase in the amount of vegetation along the banks 

makes the channel appear brighter than the surrounding areas. Alternatively, where 

the streams are ephemeral, the dry floors are topographic depressions that trap sediments and therefore tend to appear dark on radar images (due to their smoothness 

4-8
OF POOR QUALITY

200 80° 20° 

20° 

120° 

30° 

40° 

1400 

130°

Pm^ll INE

20° 

140° 50° 

40° 

30° 30° 

140° 60° 

300 100° 30° 

ZONE OF CONTINUOUS ZONE OF

PERMAFROST DISCONTINUOUS 

PERMAFROST 

ZONE OF SUB-SEA ZONE OF ALPINE 

PERMAFROST PERMAFROST 

Fig. 4-1. Distribution of different types of permafrost terrain in the Nort hern Hemisphere (4-41

4-9
ORIGINAL PAGE ! 

OF POOR QUALITY

o 10km 

ILLUMINATION 

15'N 

0.

90°W 45°W 

Fig. 4-2. Examples of dendritic stream networks, viewed by SIR-A from above South America. The drainage pattern is 

strongly enhanced in this image by the bright returns from the forested stream channels 

4-10
and low dielectric properties). Recognition of areas of convergence of stream lines 

in valley heads, and divergence on hill spurs, permits drainage basins and 

watersheds to be accurately delineated. Analysis of stream order (the ranking of 

streams along the length of a drainage system) permits the runoff potential to be assessed. Detailed models have been developed for certain catchment areas in the 

U.S., incorporating channel length and width and the total area of the catchment. 

Thus, some SIR-C experiments could attempt to calibrate radar-derived measures of 

runoff potential with actual field measurements (obtained from historical records developed over a number of years) of discharge volumes for the same river system. 

Furthermore, once the detailed morphological properties of a drainage system (e.g., 

stream order and junction angle characteristics) are known for fluvial systems on 

specific rock lithologies, it may be possible to extrapolate these observations to 

other drainage networks, thereby providing some insight into drainage basin history 

and/or rock lithology. Multipolarized data from SIR-C would be potentially useful 

for separating out specific rock lithologies. 

analyzing (2) SIR-C's multiple-look-angle capability may provide data with the potential to aid 

stream-flow studies of slope effects on river outwash plains, and those studies may in turn 

hydraulic permit the analysis of hydraulic properties of stream flow. A SIR-B image of a 

properties region in Bangladesh illustrates this concept (Fig. 4-3). This type of data may be 

particularly helpful in the description of tropical river systems. Such rivers cannot 

be easily mapped by conventional ground or air techniques, but the change in vegetation canopy as a function of age of channel abandonment may permit the chronology of former river channels to be identified, in addition to the current course of 

the river. In areas where water flow is not confined to discrete channels, the type 

of erosion on slopes may be determinable using the SIR-C radar operating at a 

steep look angle: slump features and gullying are both characteristics of sheet wash, 

and the low topographic features that this process creates could well be identifiable 

on radar images. 

monitoring (3) It may be possible to monitor the distribution of flood-water coverage during 

flood-water the SIR-C mission. While there is no certainty that a major episode of coastal incoverage undation or river flooding will occur during the course of the SIR-C mission, SIR-C 

may be able to detect sedimentary deposits left after historically recent floods on the 

basis of the texture of those deposits. River terraces and levees could also be 

mapped, to further define the extent of water inundation and sediment deposition. 

detecting (4) In addition to the use of SIR-C for defining present-day fluvial geometry, the 

ancient penetration capability on the L-band signal in and regions can be used to define the 

drainage nature and extent of ancient drainage networks buried beneath a thin (up to 2 

networks meters) cover of loose, dry, surficial debris. This capability was first recognized in 

SIR-A images of Egypt and Sudan (Fig. 4-4) and later tested in SIR-B images of 

the Sahara and other desert regions. The potential exists for using SIR-C images to 

provide the basis for systematic mapping of ancient drainages in areas that have undergone significant climatic change in the late Quaternary. See Section 4.3.5.1 for a 

further discussion. 

It is anticipated that investigations of fluvial processes could be conducted in vegetated, 

arid, or tropical supersites.

4-11 
/N i

i

10 km ______________ 

30'N 

5'N

6OE I OO'L 

Fig. 4.3. SIR.B image of the Ganges floodplain in Bangladesh. The mottled gray and black areas are cultivated fields 

connected by extensive irrigation and drainage channels. The more uniform gray area is an area of the Ganges floodplain 

subject to flooding and major reworking during the monsoon season 

4.2.5.3 Lithology, Rock Weathering, and Geochronology 

discriminating The increased ability to discriminate sedimentary lithologies using multiple-polarization 

sedimentary SAR in conjunction with Thematic Mapper data has been demonstrated in the Wind River 

lithologies Basin of Wyoming (Fig. 4-5) [4-5]. It is expected that SAR data from other sedimentary 

rock sequences would produce similar results. Calibrated images from SIR-C should assist 

in the remote characterization of lithologies by surface roughness, dielectric constant, and 

bulk properties, and will allow the extension of derived multiparameter radar signatures 

from known sedimentary basins to remote basins throughout the world. Investigations like 

these could be conducted in semiarid, arid, or vegetated supersites so long as some rock 

exposures were present. 

rock One area in which the combination of different wavelengths and polarizations could be 

weathering applied is the investigation of the weathering properties of sedimentary rocks. Different 

properties types of sandstones and limestones will erode in a manner consistent with their composition, structure, and particle size. Therefore, in the case of the multiple-polarization radar 

data provided by SIR-C, the structure of different weathered surfaces may enable different 

horizons of the same material to be distinguished from orbit. Desert sandstones and karst 

topography are two of many potential test targets for this kind of experiment.

4-12 
IN •s: 

-':• 

-

- •-

MT 

lb

- . 

•.:

SIR-A 

CRGAL PAGE !3 

OF POOR OUALIIY

/ 0 20 km 

N I 

Fig. 4-4. SIR-A image and Landsat view of the hyperarid region of the Lybian Desert. Drainage features seen in the 

radar image are blanketed by surface deposits of windblown sand and are not readily apparent in Landsat or 

photographic images. Radar penetration of surface deposits in this area extends to depths of several meters

4-13
-

dw

- 1⁄2 

ORIGINAL PAGE 

OF POOR QUALITY

• 

THEMATIC MAPPER 0 3 km AIRCRAFT L-BAND SAR 

RED = TM4 I RED = VH 

GREEN = TM3 GREEN HH 

BLUE TM2 BLUE = VV 

N 

Fig. 4-5. Comparison of Landsat Thematic Mapper and aircraft L-band multiple-polarization radar images of the Wind 

River Basin in Wyoming 

slope wash In the past, rates for slope wash have been estimated almost solely from field investigamorphology tions conducted over long periods of time. A great deal of spatial and temporal variability 

in surface cover has been observed in imagery from the visible portions of the spectrum, 

but only for short-term events. As a result, the need exists to determine quantitative measures of morphology on a scale from 1 to 20 km, that can be input for available processrelated models. Slope-area textural studies using SIR-C in its mapping mode, with multiple 

polarization and wavelength, may provide data pertinent to this problem. 

penetration A major problem in geologic investigations of arid regions is determining rates of erosion 

of hyperarid and deposition by wind and running water under climatic conditions ranging from semiarid to 

sand sheets hyperarid. One approach to this problem is to study sequences of surficial deposits such as 

aeolian sand sheets, dunes, and fluvial sediments in areas where measured sections can be 

radiometrically dated or dated from established archaeological ages of artifacts that can be 

used as index fossils. In the presently hyperarid Eastern Desert of Egypt, such sequences 

were discovered in valleys seen for the first time in SIR-A radar images, and were studied 

as a comprehensive field experiment after the SIR-A mission [4-3]. In these valleys, the 

radar allowed detection of zones of calcium carbonate accumulation in buried horizons. 

Such datable horizons are overlain in many areas by a sequence of alluvial and colluvial 

deposits, sand sheets, and sediments of mixed origin that records the interplay of geologic 

processes under variable climatic conditions culminating in the present hyperaridity. Many 

of these deposits can be correlated with known episodes of human occupation and were 

dated by archaeological means, yielding evidence for rates of accumulation and erosion. 

Potential areas of investigation include most of the great deserts of Asia, Africa, and central Australia. See Section 4.3.5.1 for a further discussion.

4-14
The ability to map Quaternary geomorphic surfaces over large areas on the basis of surface textures would be valuable for paleoclimatic, tectonic, volcanic, and arid-zone erosion 

studies. With age, some types of geologic surfaces in and areas exhibit a decrease in 

roughness, caused by physical weathering processes that break down small-scale rock 

projections and fill in low areas. 

backscatter A case study of the Snake River Plain of Idaho demonstrates this relationship. Figure 4-6 

dependence shows photographs of two flows that were field-mapped, and absolute age dates were 

on flow age determined from samples. Aircraft scatterometer measurements at two different frequencies 

(L-band and C-band) and at several angles of incidence were taken over both flows. The 

backscatter response, expressed as a ratio of polarizations for a 450 angle of incidence, is 

shown in Fig. 4-7. At both frequencies, the rougher, younger flow (North Crater) has a 

different backscatter curve than the smoother, older flow (Echo). 

These curves suggest that both flows are smooth at L-band and rougher at C-band. The 

cross-polarized component of the radar backscatter is expected to be greater for the 

rougher (blockier) flows, due to multiple scatter and depolarization. This is indeed the case 

at C-band (6-cm wavelength) for the younger blockier North Crater flow, where the likepolarized channel (HH) is only about half the intensity of the cross-polarized channel 

(MV). For the older and smoother Echo flow, the cross-polarized intensity diminishes and 

the ratio increases to about 0.7. At L-band, the surface is smoother by a factor of about 4 

(a ratio of 23-cm wavelength to 6-cm wavelength), so that depolarization due to multiple 

scatter from the basaltic blocks is decreased. This means that the dashed curve in Fig. 4-7. 

shows a slight rolloff with increasing geologic age (an increased smoothness), due to simple Lambertian like-polarized scatter behavior. 

potential for SIR-C offers the potential for simultaneously collecting such multiparameter data for an 

relative individual site to help define the relative importance of the wavelength, angle of incidence, 

age dating and polarization signatures of surfaces of varying age. In regions where the chronology of 

flows is known, it might also be the case that several different climatic environments exist 

or that different pristine lava morphologies can be identified. In these instances, the potential advantages of distinguishing surface texture by using multifrequency, multipolarization 

radars could be investigated as an aid to interpreting erosional processes or eruptive style. 

An example of this approach is shown in Fig. 4-8, which illustrates the differences among 

the radar signatures of lava flows in the Medicine Lake area of Northern California, as 

viewed by a multipolarized aircraft radar system. 

4.2.5.4 Tectonics and Geologic Boundaries 

Landsat Landsat imagery has been used very successfully to map the extremely broad tectonihampered by cally active zones in Africa and Eurasia and is being applied to studies of the North 

forest and American—Pacific-plate boundary in California. However, in many areas, use of Landsat 

cloud cover data is hampered by forest or cloud cover, or the difficulty of getting low-sun-elevation 

imagery at low latitudes. Continuing earlier airborne- and spaceborne-radar investigations, 

but with the additional advantage of a polar orbit, the SIR-C radar, by providing a good 

rendition of structure in such areas, should permit structural analysis of active faults and 

folds not easily recognized through Landsat or other visible/ infrared sensors. 

SIR-C potential It is possible that imaging from SIR-C could provide unique data for determining recent 

for mapping offsets on faults. Such offsets (from ten to hundreds of meters) are generally measured 

fault offsets from large-scale maps, aerial photos, or ground-based field work. Attempts are then made

to determine the ages of the offset features in order to estimate rates of slip. For example, 

a part of the San Andreas fault is detectable on the Seasat image, but not on that of Landsat

4-15 
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ORIGINAL PAGE 1.3 

OF POOR QUALITY 

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-

7 

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2100-2300 years BP 

-'-- .- -- -- --

- -' - 

- - - 

-AM It 

-: -. L -----• --

' 

AMNb%

ECHO FLU

5800-6200 years BP 

Fig. 4.6. Two lava flows from the Snake River Plain, Idaho. Relative age dating of lava 

flows may be possible using dual-polarization, multifrequency SIR-C data. According to 

radiocarbon dating, these flows have ages of 2100-2300 years (top) and 5800-6200 

years (bottom). These same flows can be distinguished based on their backscatter 

characteristics (see Fig. 4.7) 

4-16
0.8 

U-, 

Iu-J v,Q

o 

UI

z > I I 

<ti

0 

b 

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FLOW I C—BAND 

ROUGHER SMOOTHER 

FLOWI FLOW I 

I I 

I I I I 

Precambrian 

shields

10 12 14 

GEOLOGIC AGE, Kyr - 

Fig. 4.7. Backscatter from volcanic materials, illustrating the 

differences in radar characteristics of the two Snake River 

flows shown in Fig. 4.6 

(Fig. 4-9). This is due to the contrast in radar backscatter between units of different lithology and age, and the fault that separates them. Figure 4-10 is a hypothetical representation 

of an approach to measuring fault displacements. Depicted are two alluvial fans of different ages with a fault cutting the older, smoother fan but not the younger, rougher fan. 

Multifrequency, multipolarized data should allow detection of differing lithologies/ages because of their different polarization and frequency signatures. 

All Precambrian shields for which there is sufficient information appear to be divided 

into natural provinces characterized by specific ages and delineated by fronts. The classic 

example is the Grenville front of Canada, whose origin and nature is still debated after 

many decades of study. Figure 4-11 shows the complexity of this tectonic region in Canada, 

as imaged by SIR-B. The Laxford front of Scotland is another well-known but poorly understood example. These and other fronts appear to be both metamorphic and structural in 

nature, but there is no agreement as to their origin. A model of their formation, when developed, will have major implications for the origin of the continental crust and the role, if 

any, of plate-tectonic processes in the Precambrian. SIR-C data, obtained from polar orbit 

and thus covering shields in all continents, will permit improved structural mapping along 

extensive traverses, both normal and parallel to selected fronts. It should be possible to 

identify the structural characteristics of the fronts themselves, and changes in tectonic style 

across the fronts by comparing the structures of the adjoining shield provinces. 

Iceland represents one of the few areas of the world where a major spreading center (a 

point where new oceanic crust is created) is found on land. Thus, Iceland may be an important 

test area for volcanic/tectonic studies of the earth. A polar orbit of SIR-C would permit the regional 

geologic structure and the diverse volcanic landforms of the island to be investigated. Because 

many of the structural features associated with the spreading axis are frequently faults that are 

located in areas with high relief, a radar system with a multiple-look-angle capability such as 

that of SIR-C has to be employed. In addition, if multiple-look-angle/multipolarization data were 

acquired, many of the individual lava-flow units could also be distinguished and mapped by using 

data from other volcanic regions as ground truth.

4-17
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Fig. 48. Recognition of variations in the surface texture of different geologic materials, using multi polarization radar 

images, as demonstrated here for lava flows in the Medicine Lake area of Northern California. Aircraft radar images 

were acquired at HH (top left), HV (top right), VH (bottom left), and VV (bottom right) polarizations 

4-18
SEASAT SAR

ORG1NAL PAGE 3 

OF POOR OLJALITY 

I4

T. 

- - - 

LANOSAT MSS 5 

Opk:—\\ \ 

N

- 

Salton Sea 0 40km 

::::

[ I 

ALLUVIAL FAN SALT CRUST LAKE COAHUILA BORR EGO FORMATION 

DEPOSITS OF DEPOSITS OF OUTCROPS 

SAND AND GRAVEL SAND AND SILT

SKETCH MAP

(FROM SABINS, et al 1980) 

Fig. 4.

9. Part of the San Andreas fault system in California, as detected by the Seasat SAR on the basis of surface.material 

roughness. This same offset was undetected on Landsat MSS images, illustrating the potential of SIR•C for mapping 

structural features over extensive areas of the world. [4.6]

4-19 
FAULT 

R HH 

R HV 

S HH 

---S HV 

9 350 

RADAR

B AC K SCATTE R

COEFFICIENT

, 

/ 

/ 

/ 

, 

/ 

/ 

(L) (C) (X) 

1 5 10

FREQUENCY, GHz - 

Fig. 4-10. Diagram of a possible method by which fault displacements could be measured by SIR-C, using the back. 

scatter properties of different alluvial fans as measured at 

three frequencies and with two polarizations 

4.2.5.5 Geobotany 

Geobotany represents an evolving field in the geological sciences, but it is clear that the 

potential exists for conducting important vegetation studies with SIR-C, studies that will 

better characterize the underlying soils and bedrock. Three questions pertaining to geobotany that can be addressed by SIR-C have been identified: 

4-20
cR:cr.. ivi: :.3 

OF POOR QUALITY 

ILLUMINATION 0 10 km 

4/

..

..A

.$ 

* •1 . L 

4 ¶

..f\ /j '1 -; 

It •1 , , fpr 4t - 

t't.._ ; 4? i

)

•-. 

80°W 50°N 60°w 

40 0 N 

Fig. 4.11. SIR.B image of the Grenville front in Canada, showing the ability of the radar to aid in interpreting regional 

structural features 

geobo tan/cal 

issues

(1) To what extent do variations in the lithology of crustal materials govern the distribution, areal density, morphology, and condition of natural vegetation in different 

climatic environments? Are certain plant species direct indicators of rock lithology 

in specific environments? 

(2) Is it possible to differentiate geologic stress conditions affecting natural vegetation 

canopies from other forms of stress related to variations in plant water supply, thermal conditions, and nutrient availability? (The former question serves to define the 

"normal" conditions within a natural vegetation canopy, which, in turn, enables us 

to detect departures from normality that may be stress related.) 

(3) What are the interactions between vegetation and substrate physiology? Can the 

microwave properties of plants be combined with their spectral characteristics to 

help identify stress conditions? 

Of key interest to geologists is the ability to recognize vegetation stress or community 

associations that may be produced by abnormal concentrations of metallic ions in surficial 

soils or the local seepage of hydrocarbon gases from a substrate oil reserve. Frequently. 

plant stress results in anomalous patterns in deciduous forests at the onset of budding in 

spring or senescence in the fall. Potential SIR-C experiments could therefore be developed 

to investigate these temporal variations in canopy morphology. The determination of the 

polarization signatures and frequency-dependent signatures of both typical and stressed 

vegetation may provide insight into the capabilities of radar for distinguishing characteristics of plant communities, particularly when SIR-C data from both flights are compared to 

identify variations in plant growth.

4-21
dependence Previous radar analyses of heavily vegetated areas have emphasized the discrimination 

of plant of geologic units on the basis of their topographic and structural associations. In these 

populations analyses, the morphology of the vegetation canopy, particularly in tropical areas, has been 

on bedrock employed to make inferences about the bedrock geology. Single-frequency, singletype polarization data acquired by aircraft, by Seasat SAR, and by SIR-A have shown the capability of SAR for discriminating broad associations of vegetation types. Comparisons between airborne X-band and spaceborne Lband images of flooded alluvial forests in Brazil 

indicate a strong contrast between radar penetration capabilities at different frequencies 

(Fig. 4-12). Because radar-signal penetration in vegetated areas depends on wavelength, 

multifrequency SIR-C data could be employed to study the canopy structure in order to 

help discriminate variations in the plant population, since the population might be influenced by bedrock types. 

Six different classes of SIR-C vegetation experiments are discussed in Section 4.4.5, but 

it is also of value for the geological community to realize that the radar signatures of 

different plant types might be useful indicators of the geomorphological characteristics of 

an area. The type and degree of vigor of vegetation cover will vary depending upon the 

local aspect of a vegetated slope, the stability and age of the soil cover, the ability of the 

soil to retain water, and the altitude of the study area. Studies of airborne multi polarization 

SAR images of the forest-covered coastal lowlands of South Carolina show that distinct 

polarization signatures can be correlated with tree size (basal area) and with the distribution and density of the vegetation cover (Fig. 4-13). In the more and environment of central Wyoming, different lithologic units support varying vegetation densities that are 

identifiable on radar images (Fig. 4-5). 

The capability of SIR-C to obtain simultaneous multifrequency, multipolarization data 

may also be useful for investigating differences in canopy morphology or the degree of 

vegetation cover in an area that is partially composed of exposed rock and/or soil. Thus, it 

may be possible to develop analytical methods by which the amount of vegetation covering 

pixel-sized areas could be estimated from the strength of the like- and cross-polarized 

returns. Synergism between the multifrequency, multipolarization radar and optical/JR data 

(such as from Landsat and AVIRIS) will therefore provide a greater capability not only for 

identifying vegetation types and levels of stress, but also for aiding in the interpretation of 

geologic targets that are partially covered with plants.

4.2.5.6 Radar Stereo/Topographic Experiments 

topographic The potential to acquire high-spatial-resolution topographic data, derived either by interexperiments ferometry or from SIR-C data takes that have at least 200 variation in angle of incidence, opens a completely new realm of investigations of the earth's geology. Figure 4-14 

presents examples of this radar-derived topography from SIR-A and SIR-B, and additional 

investigations using digital terrain models from SIR-C are envisioned. 

For much of the earth, the topography is only poorly known, so that reconstructions of 

continental evolution, gravity modeling, geomorphic process, and the response of the landscape to recent climatic change can at best only be estimated. Adding radar-derived topography for local- (- 100 km2), regional- (-- 103-106 km2) or continental-sized areas could 

permit many such geologic investigations, with sufficient resolution to establish quantitative 

4-22
}

:. 

ORIGINAL PACE I 

OF POOR QUALITY 

"-'

V

5V 

•-. - -r

X-BAN D 

\ N 0 10km 

I I 

ILLUMINATION 

Fig. 4-12. A floodplain in the Amazon forest, Amazonas, Brazil (top image). Data were acquired at X.band 

by commercial airborne SAR in 1973. The bottom image, obtained by SIR .A (L.band) in 1981, shows the 

same area. Differences in the radar penetration of the tree canopy for the two systems is apparent. In the 

SIR•A image, the bright radar response in the upper reaches corresponds to points where forest cover is 

underlain by standing water. Such a feature is not seen at X-band, probably due to the shorter penetration 

length of the radar signal 

models of landscape evolution. These models can potentially be inverted to infer the length 

of time that a particular area has been subjected to a specific set of weathering conditions, 

and to identify broad-scale (>1 km) low-relief landforms with greater accuracy than has 

previously been obtained. 

The SIR-C Geology Science Working Group (SWG) has identified several potential 

topographic experiments, but it is clear that the following list is incomplete and is useful 

for illustrative purposes only: 

(1) One experiment might be the determination of volcano volume and the rheological 

properties of the erupted magmas. In many parts of the world, but particularly the 

circum-Pacific "Ring of Fire," the volume of volcanic cones and their morphologic

4-23
Jl 

A

.;•

y

ILLUMINATION \N

RED =HH 

L-BAND GREEN = VV 

BLUE VH 

Phu 

..

- . V( •-• 

0 1 k 

(AZIMUTH)

;C; PINE STAND 

ORC.INAL :p: r: 

OF POOR QUALITY 

4V47 

Fig. 4-13. The role of vegetation coverage in affecting radar returns from the Savannah 

River Plant, South Carolina. Shown is a three-color composite image obtained from an 

airborne multipolarization radar system, together with representative examples of 

vegetation types (courtesy of John Ford, JPL), 

4-24
(b)

- 

100-rn CONTOUR 

INTERVAL 

TOPOGRAPH 

GENERATED

ORGINAL PI4G.Z 3 

OF POOR QUALITY 

ED 33 

0 25 km 

TOPOGRAPHIC MAP 100-rn CONTOUR INTERVAL

GENERATED FROM PAIR 

DATA TAKE 87.4 

& = 29°)

\k /

DATA TAKE 39.4 

8 = 60°) 

0 6.5 km 

tN 

Fig. 4.14. Examples of radar-derived topography obtained from (a) SIR-A and (b) 

SIR-B. The difference between these two techniques lies in the orientation of the 

original radar data takes (courtesty of Mike Kobrick, JPL).

4-25
shape are poorly known. Using improved topographic data from SIR-C, these 

parameters and the eruptive style (explosive vs. effusive) of the volcano could be 

estimated. Furthermore, rheological models for the emplaced lava flows could then 

be utilized to estimate magma chemistry and diversity at given volcanic centers. 

(2) Hydrologic models of river basins, and the evolution of stream networks, depend 

critically on the knowledge of local topography at the lOO-m to 1-km scale. A comparison of drainage networks for regions of known lithology or age could be performed more completely if local stream gradients could be determined. In this 

manner, a topographic analysis could be correlated with the hydrology investigations outlined in Section 4.3. 

(3) In geobotanic studies, the different plant communities will be affected by local 

slopes, both in terms of the amount of sunlight the plants receive and the drainage 

characteristics of the soils. Radar-derived topography could permit plant-growth 

differences due to the landscape to be distinguished from characteristics due to 

mineralization or hydrocarbon stress. 

(4) Geomorphologists have long studied the slopes and regional relief of an area as 

potential indicators of surficial process and climatic change over geologic time. 

Erosion surfaces, mass-wasting products, hanging valleys, and regional slopes have 

all been utilized to correlate the existing land surface with present-day and former 

environmental conditions. Such studies have in the past been focused on North 

America and Western Europe due to availability of the required topographic data; in 

order to more fully investigate temporal changes in the erosion of the continents 

due to such events as ice ages and eustatic changes, these topographic investigations should 

be made global in extent and correlated with specific landforms and processes. 

(5) While the short time interval between the two flights of SIR-C precludes any long-term 

investigations of the changes in ice-sheet volumes, it is recognized that a baseline data 

set has to be derived that will permit future spaceborne experiments to detect climaterelated changes in the volume of polar and alpine glaciers. 

4.2.6 Summary of SIR-C Mission Requirements for Geology 

4.2.6.1 Orbital Parameters 

high-latitude Several of the geology experiment classes described above require a high-inclination 

coverage orbit. These classes include studies of glacial landforms, permafrost, and polar-region tectonics. 

4.2.6.2 Mission Timing 

two flights At least two flights are required, one in the May-June period and the other in the 

required November-December period. This would allow seasonal vegetation and glacial-landform studies 

and would also allow a determination, during the first flight, of the optimum radar parameters 

for testing in mapping mode on the second flight. 

4-26
4.2.6.3 Swaths and Resolutions 

recommended For the dual-frequency (L- and C- band) quad-polarization (DFQP) mode, using a 4-bps 

modes BFPQ, swath widths are expected to be about 40 km for a 35° look angle, and 30 km for

a 500 angle. Even though the swaths are narrow, this mode offers the maximum potential 

for investigating how dependent images are on wavelength and polarization. It is recommended that this mode be used principally for studies of rock weathering rates, lithologic 

mapping, age dating, and geobotany. The single-frequency quad-polarization (SFQP) mode 

offers an increased swath (45 to 47 km at 4 bps) and is preferred for mapping experiments 

involving tectonics, topography, certain aspects of cold-region geomorphology, and ancient 

drainage systems. These swath widths assume a resolution of 30 m, which corresponds to 

bandwidth of 9.5 MHz. This resolution is desirable for most of the mapping applications 

mentioned above since a higher resolution mode would result in a narrower swath width. 

4.2.6.4 Frequencies, Polarizations, and Incidence Angles 

300..550 Control of the angle of incidence is important for landform enhancement, for geometric 

incidence angles fidelity, and for the discrimination of scattering units. The preferred range for angles of 

preferred incidence for most geologic applications is 30° to 550 At lower angles of incidence, distortion due to layover is objectionable for regions of high relief. Control of the illumination angle is also important for experiments in stereo radargrammetry. A pair of stereo 

images can be obtained by imaging a particular swath at two (or more) angles of incidence 

that differ by at least 20°. It is recommended that several image pair sets be acquired 

combining various angles of incidence, with the combinations depending on the relief of 

the test site—e.g., a 15°-45° pair for high-relief regions and a 30°-60° pair for moderaterelief regions. 

simultaneous A number of geology experiments will require simultaneous acquisition of L-band and 

L-band and C-band data for like (HH and VV) polarizations; these experiments include certain coldC-band region geomorphology studies, surface-roughness effects in river outwash plains, and surface roughness (texture) of slopes for wash-rate estimation. Other studies will also require 

cross-polarized (HV or VH) data—e.g., age dating of Quaternary surfaces and geobotany 

investigations. 

wide-swath However, a number of experiments will require simply a single frequency and polarizamode tion, with as much swath as possible. These experiments include radar topographic studies, 

certain investigations in fluvial geomorphology, and studies of tectonic features. Those experiments seeking maximum penetration of dry soils will prefer L-band to C-band.

4.2.6.5 Data Products 

BFPQ Radar returns from geomorphic surfaces extend over a very wide dynamic range, at 

desired times 20 dB or so. This means that either a very large number of quantization bits must be used, 

or the BFPQ scheme must be used. For most geology experiments being contemplated, a 4-bps 

BFPQ is adequate; however, for scenes where calibrated data and absolute values are important, 

an 8-bps choice can be made, although the swath width will be cut by half.

4-27 
calibration It is important that the radiometric fidelity across the swath be as uniform as possible 

to ± 1.5 dB (better than 0.2 dB), particularly for mapping-mode experiments. Calibration to ± 1.5 dB 

or better of C-band relative to L-band is essential for geochronology and stratigraphy experiments, where the ratioing of a° (L-band) to a° (C-band) will be used as a measure of 

how dependent rock unit signatures are on wavelength. 

Level 3 For maximum utility in these geology experiments, SIR-C images should be specially 

data products processed to Level 3—i.e., they should be geocoded to standard map projection, radiometrically calibrated, and corrected for foreshortening. However, some experiments will 

also require some 4-look-survey and standard-image products that are not radiometrically 

calibrated. 

4.3 Hydrology

4.3.1 Background 

the hydrologic Hydrology is the science that studies the waters of the earth—their properties, distribucycle tion, and circulation on the surface, in the soil, and beneath the surface, and their relationship to the environment, including living things. Factors that affect the hydrologic cycle 

include precipitation, infiltration, percolation, surface runoff, groundwater flow, evaporation, and transpiration. Hydrologic models that assist scientists in understanding the hydrologic cycle require knowledge of, among other things, vegetation, surface features, land 

use, soil conditions, and meteorological information, over extended regions that have 

diverse physical and environmental characteristics. In addition, these data are required at 

frequent intervals in order to track critical parameters that control the cycle. 

The flux magnitudes in the hydrologic and energy cycles provide the major constraints 

in the evolution of ecological systems on the earth. Surface hydrology is integrally related 

to climatology in that evapotranspiration is the only source of atmospheric water, and latent and sensible heat fluxes provide much of the energy to drive climate dynamics. This 

existing link between the earth's water cycle and its surface, the atmosphere and plant biochemical cycles, provides the primary justification for more detailed studies of the hydrologic cycle. 

The energy and moisture components of the hydrologic cycle are interrelated and highly 

complex. Most of the earth's water (97%) is stored in areas with an extremely long residence time (>4000 years). Some of the water storage components such as plants, soil, 

and the atmosphere are comparatively small, but changes in these account for the major 

fluxes in the hydrologic cycle and are of primary importance for energy exchanges in the 

atmosphere and for biological resources. 

Theoretical and simulation studies have been used to study the hydrologic cycle and its 

response to changes in the variable storage terms. The process which drives the changes in 

the hydrology of the land surface can best be expressed in terms of the energy balance and 

the water-mass balance at the surface. These processes can be expressed as follows: 

RN - G = L.E + H (4-1) 

P — E=Q — S 

4-28
CHARACTERISTICS

VEGETATION MOISTURE ROUGHNESS RELIEF SURFACE OVERLAY 

REGIME 

ARID

SEMIARID SPARSE LOW VARIABLE VARIABLE NONE 

HYPERARID NONE VERY LOW SMOOTH LOW NONE 

HEAVY WITH VARIABLE: HIGHLY LOW TO 

HUMID VARIABLE MODERATE VARIABLE HIGH NONE

STRUCTURE TO HIGH 

WETLANDS SINGLE COASTAL STRUCTURE SATURATED SMOOTH LOW NONE 

UPLAND VARIABLE TEMPORALLY VARIABLE VARIABLE NONE STRUCTURE SATURATED 

SNOW-COVERED VARIABLE

VARIABLE: 

FROZEN/ VARIABLE LOW TO SNOW

WATERSHEDS UNFROZEN HIGH 

HIGH-LATITUDE VARIABLE PERMAFROST VARIABLE LOW TO 

HIGH

SNOW, ICE, 

WATERSHEDS GLACIERS 

Fig. 4. 15. Characteristics of hydrologic regimes 

where RN is net radiation, G is the soil heat flux, L.E. is the latent heat flux, H is the 

sensible heat flux, P is the precipitation, E is the evaporative flux, Q is the runoff, and S 

is the change in storage as snow, ice, or soil moisture. 

The relative magnitude of the energy fluxes input in equation (4-1) shows the importance of some of the terms which radar can help to measure. The value of G is typically a 

small fraction of RN (10 to 30%), so 70 to 90% of the radiation budget gets expended as 

latent and sensible heat input to the atmosphere. These two inputs vary in their proportion 

with time of day and climate, but on the average, are about the same size. Since the latent 

heat flux carries about 40% of the radiation budget, it is important to be able to estimate 

L.E + H for its energy content and L.E alone for its water content. Modeling these, in 

turn, depends on surface measurements such as soil moisture, temperature, albedo, and 

ground cover. Several measurements which may be made using surface-viewing radars are 

helpful in estimating these fluxes. In order to estimate fluxes, it is necessary to have time 

series of several state variables, such as surface temperature and surface moisture. 

As is described later, radar may be useful in making estimates of soil moisture status and 

snowpack properties, and certainly may be related to vegetation properties, such as stomatal water content, which are in turn related to transpiration rates. In addition, radars are 

useful for hydrological mapping, such as of topography, which are used then in runoff estimation. During a short Shuttle experiment, it is difficult to estimate fluxes directly by 

getting a time series of measurements. It is anticipated more that the SIR-C experiment 

will show the feasibility of making state measurements such as those related to surface soil 

moisture and snowpack and vegetation properties. The results can be used later, together 

with those using other sensors, to design algorithms that estimate hydrological fluxes 

globally and routinely using synoptic radar data that should be available in the next decade. This ties closely with the objectives of other parts of NASA's program, and to the 

aims of such related programs as the International Satellite Land Surface Climatology 

Project.

4-29 
Radar data can make different scientific contributions in different hydrologic regimes. 

Five categories of hydrologic regimes can be identified based on their unique distinguishing characteristics and the contributions radar data can make in them: 

(1) Arid regiohs 

(2) Humid regions 

(3) Wetlands 

(4) Snow-covered watersheds 

(5) High-latitude regions 

Each hydrologic regime has distinguishing physical characteristics, as summarized in 

Fig. 4-15. Not only are these physical characteristics distinctive for each hydrologic 

regime, they also have a strong influence on the formation of a radar image. With each 

hydrologic regime, there are associated specific research objectives. 

and regions Arid regions, the global distribution of which is shown in Fig. 4-16, have little soil 

moisture and receive average precipitation amounts ranging from about 20 cm per year 

(semiarid) to only a few mm in several years (hyperarid). As a result, vegetation is sparse 

or nonexistent and human population densities are low, except for irrigated regions. The 

surfaces of hyperarid regions are generally smooth with small slopes. 

Research issues for these hyperarid regions include the mapping of subsurface relict 

riverbeds and channels that provide indications of the hydrologic development of the region. 

Specific research issues for semi-arid areas include monitoring the spatial distribution and amount 

of rainfall, soil moisture status, evaporation, and vegetation. 

humid The humid regime is the most complex regime in terms of application of radar data to 

regimes scientific problems. It is highly vegetated, containing a wide variety of vegetation geometries and sizes. The soils are mostly moist, and there is a wide range of surface roughness 

and topographic relief. The high-priority research objectives for this regime include 

(1) Direct measurement of watershed characteristics and runoff model parameters and 

mapping areas of high soil moisture within watersheds to calibrate these models 

(2) Measurement of the areal extent of precipitation over land 

(3) Delineation of surface water, especially under vegetation canopies 

(4) Measurement of vegetation characteristics which relate to transpiration 

wetland Wetlands are important because they are the main chemical-reducing environments and, 

regimes thus, key controls on global chemistry. They are also ecologically unique. The two basic 

wetland regimes are estuarine and nonestuarine. Figure 4-16 indicates tropical rainforest 

regimes, where a preponderance of the earth's wetlands exist. The existing wetland global 

maps are inadequate, which indicates the necessity of improved information about these 

areas. The soil moisture of the lower-lying estuarine wetlands tends to be constant with 

time because the surface of the freshwater table remains essentially at the same elevation 

in low coastal areas of normal groundwater recharge. Compared to nonestuarine wetlands, 

estuarine vegetation systems have relatively dense associations of lower-growing, finerstructured species. The soils of estuarine wetlands tend toward constant saturation. Riveri, palustrine, and lacustrine wetlands, on the other hand, are subject to the vagaries of 

rainfall or to seasonal variability in the depth of the water table. Such wetlands are also 

characterized by a wider variation in the size, type, and density of vegetation classes.

4-30
1/9 

EXTREMELY ARID 

ARID 

SEMIARID 

IN

^% ^141

(b) 

MIGINAL PACz is 

OF POOR QUALITY 

() .u1 IC - 

J01

D. 

snow-covered 

watersheds

• ' U 

TROPICAL/HUMID / 

Fig. 4.16. Global distribution of (a) and and (b) tropicallhumid environments 

Two important research objectives for wetland hydrology are wetland boundary delineation (the discrimination of the land-water boundary, especially when it is vegetationcovered) and the discrimination of vegetation classes as an indicator of wetland characteristics, classification, and chemistry. 

Watersheds at mid-to-high latitudes are distinguished particularly by the seasonal 

presence of snow and ice. These regions are typically vegetated, but the vegetation varies 

widely, ranging from rangeland to forest. Also, such snow-covered watersheds occur often

4-31
a" N

ILLUMINATION 0 10 km 

400 N 

Om00" p.el a 

OF POOR QUALM 

(b)

-5 

-10 

b 

z

-15 

L) 

U-

-I 

0 

LI 

(3 

z

-20

I I 

O BARE 

A COTTON 

• LETTUCE 

+ ALFALFA

0

0 

= -24.4 +22.8W 

2 =0.81 

d = ±0.8 dB 

o

30°N 1 10°W 

130'W 

-25 

-30

0 0.1 0.2 0.3 

SOIL MOISTURE IN TOP 5cm, 9/cm3 

Fig. 4.17. A comparison of soil-moisture data showing (a) an agricultural area about 60 km southwest of Fresno, California, 

as imaged by SIR-B, and (b) a° vs. soil moisture in the top 5 cm as derived (solid line) from this image and compared to 

scatterometer and Seasat data 

4-32
in mountainous regions with considerable topographic relief. Key hydrologic research objectives for these watersheds include the measurement of snow-pack extent, the snow-cover 

water equivalent, and the ripeness (wetness) of the snow pack. 

high-latitude 

regions

Characteristics of high-latitude regions are essentially the same as for snow-covered 

watersheds except that additional problems related to permanent, rather than ephemeral ice 

and snow, related to ice sheets, glaciers, and permafrost are included. From a hydrological 

point of view, glacier parameters such as glacier slope and contours and the volume of 

meltwater are important for estimating glacier dynamics. Also, the areal extent of permafrost, the depth of permafrost, and the conditions of overlying soil are of considerable 

interest for runoff modeling. 

4.3.2 The Role of Spaceborne Remote Sensing in Hydrology 

from point data 

to area-extensive 

data

Historically, hydrologic information has been obtained utilizing point data sources (e.g., 

rain gauges) from which area-extensive information is estimated through mathematical and 

statistical techniques. Typically, the area density of point data sources is too low for 

statistical validity. By contrast, satellite-borne imaging sensors inherently provide continuous area-extensive information on a synoptic scale. Optical, infrared, and microwave imaging and nonimaging sensors all provide useful information since vegetation, soil types, 

meteorological conditions, etc., all affect the hydrologic cycle. The Landsat Multispectral 

Scanner (MSS), the return-beam vidicon (RBV), the Thematic Mapper (TM), and the Advanced Very High Resolution Radiometer (AVHRR) have been used to acquire information 

on surface and vegetation features. Measurements from NOAA/TIROS-N (atmospheric 

water vapor and temperature profiles), NIMBUS-7 (surface temperature), and HCMM 

(albedo) have provided thermal IR and passive microwave data that have been used for 

evapotranspiration estimates. Microwave sensors operating at wavelengths from L-band to 

X-band have also been used to provide information, such as soil moisture, more directly. 

In addition, these longer wavelengths have proved to be extremely beneficial in very dry 

regions for probing subsurface features. SIR-C will provide a sensor capability beyond that 

of Seasat, SIR-A, and SIR-B. In addition, passive microwave systems operating at these 

frequencies can provide unique information, although at reduced spatial resolution. This 

section of the science plan identifies hydrologic issues that can be addressed utilizing the 

SIR-C system either alone or with complementary passive microwave systems or visible/ 

near-IR sensors. 

4.3.3 Role of Imaging Radar in Hydrology 

radars vs. 

radiometers

The principal role of imaging radar in hydrology is to provide information on soil 

moisture, vegetation cover, glacier, and snowpack characteristics. A secondary benefit of 

radar relates to its ability to penetrate hyperarid sand sheets to a meter or more, thus 

providing valuable data on subsurface relict riverbed channels in the Sahara and similar 

very dry regions. 

Both imaging radars and passive microwave radiometers operating at L-band and C-band 

have been shown to be useful for estimating soil moisture in the top few centimeters of the 

soil. From a space platform, an L-band radiometer would have a spatial resolution of 

several kilometers, while an L-band SAR would provide much finer resolution, typically

4-33
on the order of 30 meters. The microwave brightness temperature can be converted to an 

emissivity value by normalizing with the physical surface temperature, and subsequently 

related to soil moisture through a series of physically based models. The active radar 

backscattering coefficient, o°, also can be related to soil moisture through physically based 

models, although surface roughness, slope, and vegetation can also strongly modulate the 

radar return. The radar backscattering coefficient is closely related to vegetation characteristics such as biomass, geometry, and plant moisture, which in turn are closely coupled 

to the hydrologic cycle. Ultimately, an operational system for hydrology is likely to be 

composed of both active and passive microwave systems giving complementary information. It is necessary first to understand, test, and refine radiative transfer models that relate 

radar backscatter to hydrological state variables, such as soil moisture, before we can use 

time series of data from both active and passive sensors, and then to look at changes in 

these state variables and estimate hydrologic fluxes. 

Nonetheless, it is evident from phenomenological studies that there is a strong relationship between radar backscatter and various hydrologic variables. Figure 4-17(a) shows an 

image taken by SIR-B from above an agricultural area in the San Joaquin Valley, about 60 

km southwest of Fresno, California. Individual agricultural fields are clearly separated. 

Figure 4-17(b) shows a° vs. soil moisture for the top 5 cm, as derived (solid line) from 

this image and compared to results on similar fields, obtained earlier by aircraft scatterometer data and Seasat data. 

other 

imaging 

radar 

capabilities

Radar data may also be used for hydrologic mapping of less dynamic hydrologic variables. For instance, the capability of an imaging radar to map topographic relief in detail 

can help determine parameters related to watershed runoff hydrology. Other examples of 

using an imaging radar for hydrologic studies are flood and coastal-area mappings, especially under cloudy conditions. 

The SIR-C data requirements for scientific investigations in hydrology will call for 

differing sensor parameters, depending on the objective. For example, maximum swath 

widths and longer wavelengths are generally significant for the study of sand-mantled, 

buried riverine channels and alluvial deposits, such as those discovered by SIR-A in the 

Eastern Sahara and postulated to exist in virtually all of the earth's major desert regions. 

Horizontal-horizontal (HH) polarization has been shown on theoretical grounds to maximize the penetration of radar signals in such regions [4-7], but the extent to which 

vertical-vertical (VV) or cross polarization is important should be determined during the 

SIR-C mission. On the other hand, multifrequency and multipolarization options are of 

equal importance for other studies dealing with backscattering response to variation in soil 

moisture, surface roughness, and vegetation cover. An imaging radar with a single frequency and polarization (e.g., SIR-A or SIR-B) does not supply enough information to 

study many land surface variables in detail. This is because the radar backscattering coefficient is related to several variables, so that several measurements are needed to invert the 

radiative transfer equation in order to estimate these variables. 

Many hydrologic studies will require two SIR-C flights separated by six to eight months 

at times of near-saturated and dry conditions. These flights will include mapping of 

seasonal changes of water storage in the form of soil moisture, wetlands, snow, and ice. 

Observations over two different seasons are also needed of the effect of vegetation on 

imaging radar remote sensing of hydrologic parameters. 

4-34
4.3.4 Scientific Basis for SIR-C Hydrology Experiments 

microwave A principal reason why the microwave region is useful for hydrologic investigations is 

sensitivity its sensitivity to changes in the dielectric constant of the surface, especially changes caused 

to water by soil moisture or water boundaries. As pointed out previously, the dielectric constant of 

water is about 80 while that of dry soil is about 3. The dielectric constant of very wet 

soils may approximate 30. This is responsible for the strong dependence of both the emissivity and the radar backscattering coefficient on soil moisture. The effects of soil moisture 

are clearly seen in Seasat SAR images and more recently in SIR-B images (cf. Fig. 4-17). 

Another important reason why the imaging radar is useful to hydrologists is its sensitivity 

to surface roughness and slope. The intensity of radar backscatter depends strongly on 

local slope and is also affected by smaller-scale surface roughness. 

attenuation and Still another factor affecting radar backscatter is the presence of vegetation, whose canopy 

scattering by acts as an attenuator and scatterer of incident radar waves. In the hydrologic context, this 

vegetation aspect can be both an advantage and a disadvantage. To the extent that backscatter from 

vegetation is an indicator of stand vigor, it may be related to underlying soil moisture conditions and therefore be useful. However, in other situations, vegetation may act as a confusion factor that partially or completely masks underlying soil moisture conditions or 

soil-water boundaries. The presence of snow or ice can also affect radar backscatter, particularly at the shorter wavelengths. 

the two-layer From a radar perspective, two layers of the earth's surface affect hydrology, and both 

model are important for quantifying the dynamic water balance. Typically these two layers are a 

vegetation canopy and a soil layer, or a snow pack and a soil layer. The problem facing 

hydrologists using remotely sensed data is one of measuring the properties of each layer 

without interference or confusion from the other layer. Multifrequency SAR data will help 

to keep the layers distinct. 

The two-layer system typical of most surfaces of hydrologic interest can be considered 

an inhomogeneous layer overlying a homogeneous layer. The vegetation canopy or snow 

pack is considered inhomogeneous because it is a mixture of materials of different dielectric properties. In this case, the transmitted radar wave is subjected to volume scattering 

within the inhomogeneous layer. The soil layer is considered homogeneous because its dielectric properties are relatively constant within the layer. A transmitted radar wave is subjected to surface scattering in this case. The ideal remote sensing system for hydrologic 

applications would consist of several frequencies and polarizations. In general, the system 

characteristics for hydrologic applications are as follows: for measuring upper-layer (crop 

or snow) properties with minimal contribution from the lower (soil) layer, the system 

would use shorter wavelengths (K, X, or C), larger angles of incidence, and multipolarization; for measuring lower-layer (soil) properties with minimal contribution from the upper 

(crop or snow) layer, i.e., for maximum depth of penetration, the system would use longer 

wavelengths (C, L, or P), smaller angles of incidence, and like polarization. 

extracting The problem of extracting useful hydrologic information from multiparameter radar 

hydrologic images of terrain surfaces may be posed in the following quasi-mathematical way: 

information from 

terrain-surface 'nmp = f( SM, VEG, SR, SL, CV; X, p, 0, CX) (4-2)

images

4-35 
where I is the image intensity. The integers n, m, and p refer respectively to the n th 

wavelength, the m th incidence angle, and the p th polarization. This equation states that 

the image intensity is a function of soil moisture (SM), vegetation cover (VEG), surface 

roughness (SR), slope (SL), and temporal cover, e.g., snow (CV). It also explicitly recognizes the effect of wavelength (X), polarization (p), angle of incidence (0), and image 

context (CX). Of course, no explicit mathematical relationships of the above type actually 

exist for most scenes of practical interest, because of their complexity. A typical problem 

confronting a hydrologist might be to estimate the soil moisture SM at some point in a 

SAR image, in the presence of the confusing factors of vegetation, surface roughness, slope, 

and cover. Mathematically, the problem is to invert the equation and "solve" for soil 

moisture. Even though no explicit relationship exists, the above formalism is useful, since 

it hints that even though we may have as many as five unknowns, we also have quite a 

number of equations provided by SAR imagery taken at various frequencies, polarizations, 

and angles of incidence. We also obtain additional information through context, which in 

the past has been virtually the only tool available to the photointerpreter. 

Can we really invert this set of equations and solve for soil moisture (or for some other 

parameter)? The answer is "yes" for some situations, "no" for others, and "we don't 

know yet" for quite a number of cases. We do know, for example, that SAR response to 

surface roughness is relative as to wavelength, so that by perhaps ratioing SAR images 

taken at one or more frequencies, incidence angles, or polarizations, we may be able to 

estimate roughness, at least for bare soils. In general, we need a better understanding of 

the interaction of electromagnetic waves with hydrologic surface features and conditions. 

Even though a great deal of information available in the literature is based upon theoretical 

models and experimental measurements, these usually refer to idealized circumstances such 

as bare soils, uniformly vegetated surfaces, or gentle slopes. 

ground-based 

measurements

An exhaustive series of ground-based radar measurements of the dependence of the 

radar backscattering coefficient on soil moisture, vegetation, and snow were made by F. 

T. Ulaby and his colleagues [4-8] over the period 1974-83. Most of these measurements 

were made using an FM-CW radar whose frequency was selectable between 1 and 18 

GHz, and whose polarization and angle of incidence were likewise selectable. The soil 

moisture and vegetation measurements were primarily for agricultural fields. A strong dependence of a° on soil moisture was found at both L-band and C-band; however, surfaceroughness effects for agricultural fields were found to be minimized at C-band. 

Figure 4-18 illustrates the truck-scatterometer-measured dependence of a 0 , at C-band, 

on soil moisture expressed as percent of field capacity for both bare fields and fields with 

mature corn, soybeans, milo, and wheat. These curves are the average for 181 independent samples for the bare-soil case and 143 independent samples for the vegetated case. It 

should be emphasized that measured data points are scattered about these curves due to the 

effects of surface roughness, row direction, etc. However, several conclusions can be 

drawn from these curves: 

(1) The total expected dynamic range of a° as the soil goes from dry (0%) to wet 

(100%) is about 15 dB for the bare-soil fields and 10 dB for the vegetated fields. 

(2) The vegetated fields are brighter (by about 4 dB) than the background soil when the 

soil is very dry (10%); however, as the soil moisture increases, the difference 

quickly becomes negligible because the surface scatter from the background highreflectivity soil is much greater than the volume scatter from the vegetation canopy. 

4-36
1-dB radiometric 

fidelity required 

across swath 

1-dB relative 

calibration 

required

We can conclude from this that a SIR-C channel using C-band, HH polarization, and a 

20 0 angle of incidence should see a similar strong dependence on soil moisture for both 

bare fields and fields planted with agricultural crops. It can also be seen that in order to 

use SIR-C C-band imagery for soil moisture discrimination, good radiometric fidelity must 

be achieved both across the swath and from pass to pass. This is because soil moisture experiments will be performed to determine both spatial variability and temporal variability: 

(1) For these experiments, it will be necessary to determine the variability of soil 

moisture over the entire area covered by a single pass. For example, if we wish to 

discriminate soil moisture over 5 discrete levels from wet to saturation (i.e., 20% 

soil moisture variation in each level), then for vegetated fields this would correspond to about 2 dB per level (see Fig. 4-18). This means that the radiometric fidelity over the image should be at least ± 1 dB rms. 

(2) For these experiments, we will want to image the same area, say, once per day to 

determine dry-down rates or other temporal variables. Using the above example of 

vegetated fields, this would mean that the relative radiometric calibration should be 

at least ± 1 dB, so that image intensity from day to day can be compared and used 

with an algorithm, such as that in Fig. 4-18, to determine temporal variation of soil 

moisture. 

The fairly simple cause-effect relationship depicted in Fig. 4-18 makes it appear that 

we can use SIR-C images to determine an intensity (or ao), and from that determine soil 

moisture, even in the presence of agricultural vegetation. Unfortunately, the situation in 

Fig. 4-18 does not consider more realistic situations where the radar backscattering coefficient is strongly modulated by local topography or surface roughness. In addition, this 

curve is limited to the case of agricultural vegetation and does not consider the case of a 

forest canopy or other vegetation. In order to achieve a more quantitative understanding of 

these other variables, we need additional data sets. 

4 

o

b o Iz

-12

VEGETATED

SOIL 

,>SARE OIL FREQUENCY: 4.5GHz 

POLARIZATION: HH 

ANGLE OF INCIDENCE: 100 

20 40 60 ou IOU IU 

SOIL MOISTURE, PERCENT OF FIELD CAPACITY 

Fig. 4-18. Average dependence of radar backscattering on soil 

moisture in the top 5 cm measured as percent of field capacity, for 

both bare soil and soil covered with an agricultural vegetation mix 

of corn, soybeans, milo, and wheat. These curves are based on data 

obtained by Ulaby et al. (4.8, Volume II, p. 8641 with a C.band 

HH.polarized radar scatterometer using a 100 angle of incidence; 

the curves are the means based upon 181 independent samples for 

the bare soil case, and 143 independent samples for the vegetation 

case

4-37
SIR-C will provide a unique opportunity to understand better the interaction of electromagnetic energy with hydrologic surface features and conditions through multiparameter 

SAR imagery. This interaction has been difficult to effectively study using the single frequency and polarization of Seasat, SIR-A, and SIR-B, in the sense that there were more 

unknowns than equations. We need to understand better how radar backscatter depends on 

the hydrologic scenes in order to make effective quantitative use of these radar images. 

Therefore, it is important to identify the specific classes of electromagnetic scattering and 

attenuation geometries for which models are needed. When idealized, these classes of 

geometries can be mathematically modeled to some degree, as in equation (4-2), and are 

very useful as guidelines in the interpretation of more complex situations. For these 

classes, we seek to understand the role of wavelength, polarization, and angle of incidence 

on the relationship of the radar backscattering coefficient (SAR image intensity) to soil 

moisture, vegetation cover, surface roughness, slope, and surface cover. 

In this sense, there appear to be four broad areas where SIR-C could contribute to a 

better understanding of electromagnetic interaction: 

(1) The effects of overlying vegetation 

(2) The effects of surface roughness, slope, and penetration 

(3) The effects of soil dielectric constant 

(4) The effects of overlying snow packs and ice sheets 

4.3.4.1 Overlying Vegetation 

SIR-C will allow investigations of 

(1) The degree of attenuation introduced by vegetation cover, leading to the masking of 

the underlying surface 

(2) The mechanisms of scattering and re-reflection when vegetation grows in standing 

water 

(3) The density of vegetation as a hydrologic indicator 

vegetation Vegetation cover is a confusion factor when we attempt to measure underlying surface 

as mask of or soil properties. Moreover, there is a wide range of vegetation morphology apparent in 

underlying scenes of interest to hydrologists. Radars are sensitive to vegetation structure, so that 

surface SIR-C will provide an opportunity to investigate the attenuation introduced by vegetation 

cover, as a function of wavelength, polarization, and angle of incidence. 

When there is standing water or saturated soils underlying a plant canopy cover, there 

can be an enhancement of SAR image intensity due to the re-reflection of volume-scattered 

radiation from the canopy, as illustrated in Fig. 4-19. Figure 4-20 illustrates this effect as 

observed in a black-and-white Seasat image of a wetland region near Trinity River, Texas. 

The bright area surrounding the water body is due to re-reflection from understory water. 

This is not seen in the color image, which is an infrared aerial photograph taken at the same 

time. We need to use SIR-C to better understand the influence of vegetation morphology 

on the polarization-dependence of radar returns at long (L-band), medium (C-band), and, 

potentially, short (X-band) wavelengths, in these wetland regions. 

vegetation as The occurrence and type of vegetation, and its location is used as an important hydrohydrologic logic indicator, especially in wetland areas. SIR-C will permit studies of the extent to 

indicator which vegetation density and species can be distinguished for wetland classification 

purposes.

4-38
(a) LOW

(b)

HIGH 

RETURN RETURN 

possible 

surface 

effects

LOW -

•.- -: HIGH 

DC NONSATURATED ... SATURATED SOIL DIELECTRIC 

WATER 0 CONSTANT CONSTANT SOIL, LOW VER SOIL, 

REFLECTIVITY. * .. *-'.`

.

- HIGH REFLECTIVI -

Fig. 4-19. Surface reflectivity. With dry soil (a) the surface reflectivity is low, there is little 

surface re-reflection of volume-scattered radiation from the canopy, and returns are low. When 

(bl, there is standing water or saturated soil under the canopy, there is considerable re-reflection 

and net returns are high 

4.3.4.2 Surface Roughness, Slope, and Penetration 

At SIR-C wavelengths, measurements of surface backscatter will be sensitive to a wide 

range of roughness scales from a few centimeters (small-scale roughness) to tens of meters 

(large-scale relief). This presents an opportunity to study the dependence of SAR imagery 

on

(1) Small-scale roughness 

(2) Large-scale topographic relief 

(3) Surface penetration 

The identification and separability of small-scale surface roughness in radar images is 

important to the classification of runoff potential for watersheds. In addition, surface 

roughness can be a serious confusion factor when attempting to extract soil moisture information from radar measurements. SIR-C presents an opportunity to improve our understanding of how well radar imagery can be used to discriminate categories of surface 

roughness that are relevant to hydrologic classification, as well as our understanding of the 

relationship between surface roughness and cross-polarized backscatter. 

Many watersheds lie in regions of large-scale topographic relief. Mountainous features 

with large-scale topographic relief strongly modulate the intensity of the radar image and 

may also introduce a geometric distortion known as layover, especially at near-nadir angles 

of incidence. This complicates the task of extracting local surface features (e.g., soil 

moisture) on mountainous slopes. An important problem is how to remove or minimize 

topographic effects from radar imagery in order to measure surface soil moisture features 

in mountainous regions. 

It is well known that microwave wavelengths penetrate very dry soil to some degree. 

However, direct evidence in image form of this penetration and subsurface interaction was 

not demonstrated until the SIR-A pass over the Eastern Sahara. Those images demonstrated 

penetration of 1-3 m into the sand as well as evidence of volume scattering from subsurface calcium carbonate (caliche) nodules and other scatterers. SIR-C will provide an opportunity to replicate this experiment at a wavelength of 23 cm and at 6 cm as well. This

4-39
-' - . -

- 

Ar- - L- k - •i-. 

j

in 

- 

0 1 k

dR AERIAL PHOTOGRAPH L-BAND SEASAT IMAGE 

Fig. 4-20. The re-reflection effect. The Seasat image (a) of a wetlands region near Trinity River, Texas, shows a bright area 

surrounding the body of water. This area is due to re-reflection from understory water. The bright area is not visible in the 

infrared aerial photograph (b), which was taken at the same time. 

ORIGINAL PAU II 

OF POOR QUALITY 

4-40
should allow an estimate of the attenuation constant, thereby providing the ability to 

predict the depth of penetration at even lower frequencies, e.g., P-band (70 cm). 

4.3.4.3 Soil Dielectric Constant 

soil conditions SIR-C will permit detailed studies of the dependence of the radar backscattering coeffiof interest cient on the soil dielectric constant in the presence of confusion factors such as slope, surface roughness, and vegetation. There are four soil conditions of particular interest: 

(1) The low dielectric constant (approximately 2 to 3), such as obtained in arid or 

hyperarid regions 

(2) Medium-to-high dielectric constant soils 

(3) Snow or ice overlying soil 

(4) Permafrost 

The low soil dielectric constant associated with very dry soils leads to enhanced 

penetration at longer wavelengths. SIR-C will permit studies of not only the attenuation 

constant (see discussion above), but also the effect of subsurface random volume scatterers 

on the polarization characteristics of the return. This may allow some discrimination of 

subsurface scattering types. 

Soils in humid-region watersheds have moderate-to-high dielectric constants because of 

the elevated soil moisture levels. SIR-C will provide the opportunity to study the response 

of radar backscatter to a range of soil moisture conditions for different wavelengths and 

polarizations. For example, SIR-C will provide the opportunity to study the relative sensitivity of cross-polarized backscatter compared to like-polarized backscatter for different 

surface roughnesses, as well as the water-holding capacity of soils. This capacity depends 

on soil texture, soil density, organic matter content, and other parameters, all of which can 

be expected to modulate partially the radar image intensity. 

permafrost There is little information available on the dependence of the radar backscattering cocharacteristics efficient on permafrost, which is composed of soil or other surficial deposits that have 

been at a temperature below freezing continuously over a long period of time (from two 

years to tens of thousands of years). Permafrost depths range from more than 3000 feet in 

the Arctic to as little as 1 foot over 20% of the earth's land area outside the Arctic. SIR-C 

may allow the establishment of radar signatures for permafrost as a function of frequency, 

polarization, and angle of incidence. Moreover, it may be possible to determine the effects 

of overlying soil conditions on permafrost signature where the permafrost does not extend 

to the surface. 

4.3.4.4 Snow 

snow Snow packs and ice sheets overlying soil are of considerable interest to hydrologists. Of 

parameters particular value are three parameters: 

(1) Snow pack extent 

(2) Snow wetness 

(3) Snow-water equivalent

4-41
In the microwave spectrum, a snow layer causes both attenuation and scattering of signals, 

especially at millimeter wavelengths. The microwave response to snow increases dramatically as the frequency is increased above about 10 0Hz, and this is the case for both the 

active and the passive response. 

By using ground-based scatterometers mounted on a truck boom, Ulaby and Stiles [4-9] 

have been able to quantify the radar response to snow. Figure 4-21 shows that the measured radar scattering coefficient of a 48-cm-deep snow layer as a function of frequency 

for both dry snow (0% moisture by volume) and wet snow (1.26% moisture by volume) is 

less than 1 dB at L-band but increases to about 4 dB at C-band and X-band. Moreover, 

the radar backscattering coefficient a° increases with frequency and as the snowpack becomes dryer. This indicates that at C-band and X-band, a diurnal variation in snow wetness of only about 1 % should be clearly visible in SAR imagery for snowpacks of about 

40 cm depth or greater. 

DATE: 3/3/77 

POLARIZATION: HH 

ANGLE OF INCIDENCE 9: 50° 

SNOW DEPTH: 48 cm 

WATER EQUIVALENT: 10.5 cm DRY SNOW-7

TIME m(%) 

—f 0800 0 

---S 1600 1 2

11116-11111 41"o 

;

WET SNOW

5 

0 o

b

-5 

U

-10 

0 U 

() -15 

z 

cc

-30

FREQUENCY, GHz 

Fig. 4-21. Spectral response of a° for wet and dry snow (from 

Ulaby and Stiles, 1980 (4-9]) 

frequencies 

C-band or 

higher needed 

for snow

The calculated dependence of a°, at various frequencies, on the depth of a dry snow 

layer containing 2-mm-diameter ice particles is shown in Fig. 4-22. This is again for an 

HH-polarized radar using a 50° angle of incidence. It is apparent that there is no sensitivity 

to snow depth at L-band (1.2 GHz) and that even at C-band (5.0 0Hz) a 1-rn-deep snow 

layer produces only a 2-dB increase in cr° over the background soil (assumed here to have 

a dielectric constant of 5 and an rms surface roughness of about 1 cm). However, at 

X-band, a 1-rn-deep snow layer produces an 8-dB increase of a° over the background soil. 

These measurements and calculations suggest that in SIR-C imagery, snowpacks will be 

essentially invisible at L-band, marginally visible at C-band, and quite visible at X-band. 

4-42
ICE LOSS 

FACTOR

SOIL SURFACE 

PARAMETERS

SNOW 

PARAMETERS 

ALBEDO Ke 

(GHz) €

k1 kL ka- m a (Np m3) 

1.2 0.001 0.1 3 0.3 - 0.01 0.003 

5.0 0.002 0.7 13 13.0 - 0.33 0.035 

10.0 0.005 1.4 20 20.0 - 0.68 0.270 

17.0 0.008 - -

- 0.27 0.85 1.790 

35.0 0.020 - -

- 0.27 0.95 28.800

10

FREQUENCY: 35.0 GHz 

17.0 GHz 

10.0 GHz 

5.0 GHz 

= 3.15 SNOW

ANGLE OF INCIDENCE 9: 500 L a,m 

___ - 

POLARIZATION: HH _______________ 

ICE-PARTICLE RADIUS: 1 mm

1.2 GHz 

0 20 40 60 80 100 120 140 16t) WV

PHYSICAL DEPTH d, cm 

Fig. 4-22. Calculated variation of a°HH with depth for a dry 

snow layer containing ice particles 1 mm in radius. Note the 

important role of frequency. (After Ulaby at al. (4.5, Volume IlJ) 

4.3.5 SIR-C Hydrology Experiments 

hydrologic SIR-C presents the opportunity to conduct hydrology experiments at two levels: the first 

experiment level concerns traditional hydrologic research objectives in the various regimes, and the 

objectives second an improvement of electromagnetic models applicable to hydrologic research using 

microwave sensors. The latter experiments and their scientific basis were discussed in the 

previous section. The primary hydrologic research objective of SIR-C, however, is to determine its sensitivity to soil moisture, vegetation cover, surface roughness, slopes, and 

snow or ice cover. The following discussion of the SIR-C experiments is organized by 

hydrologic regime. These experiments, summarized in Table 4-3, are included for illustrative purposes only and are not intended to be either complete or sufficient. 

4.3.5.1 Arid Regimes 

hypera rid The SIR-A mission has demonstrated that, in at least one major and region (the Eastern 

regions Sahara), 23-cm-wavelength radar signals refract into and backscatter from within a meter 

or so of very dry sand and alluvium. SIR-A images of this region revealed unmapped 

b 

Z -5 

U 

LL 

U-

..10 

-15 

U

-20 

-25

4-43 
Table 4-3. Some SIR-C hydrology experiment classes 

Experiment Class Scientific Objectives 

Surface penetration in hyperarid regions 

Semiarid-region soil moisture 

Spatial variability and scale in 

hydrologic systems 

SAR image sensitivity to precipitation 

SAR image sensitivity to hydrologic 

characteristics 

SAR image sensitivity to flooding 

Groundwater resource analysis 

Wetland boundary delineation 

Wetland vegetation discrimination 

Snow extent and characteristics 

Glacier discrimination 

Permafrost

Delineation of subsurface hydrologic features in buried pluvials 

Temporal and spatial variation in semiarid soil moisture 

Spatial variability of hydrologic parameters; scale of hydrologic 

units; development of criteria for hydrologic uniformity 

Direct measurement of precipitation 

Area information for characterizing watershed hydrology: 

temporal changes in soil moisture 

Flood extent and duration 

Identification of groundwater recharge and discharge areas 

Definition of understory landwater boundaries 

Identification of broad classes of vegetation in wetland settings 

Snowpack extent, snow water equivalent, and snowpack 

ripeness; snow runoff potential 

Distribution of morainal material, crevasse patterns, and ice 

surface roughness 

Permafrost boundaries 

bedrock features as well as sand-buried networks of previously unknown stream deposits 

dating from the Middle Tertiary to the Late Pleistocene. Subsequent evidence for radarsignal penetration up to a meter in the semiarid and and Mohave Desert in California was 

described by Blom et al. [4-10], from an analysis of Seasat images of alluvium-buried igneous dikes. Elachi, Roth, and Schaber [4-7], using a simple backscatter model, have recently 

shown that the presence of a low-loss completely dry sand layer refracts the incident wave 

and actually enhances the capability of the radar to image the subsurface, particularly at 

moderate angles of incidence (e.g., the 50° of SIR-A) and with HH polarization. Theoretically, HH polarization offers a factor of 2 to 3 times greater sensitivity than VV polarization for detecting a dielectric layer below about 1 m of dry sand, in such hyperarid 

terrains. The general behavior of wave penetration and subsurface scattering in hyperarid 

zones is suggested by Fig. 4-23. 

Given the demonstrated successes of penetration experiments using SIR-A, Seasat, and 

SIR-B, the SIR-C SWG recommends that one broad category of SIR-C hydrology experiments in desert regions focus on the depth of penetration at L-band, C-band, and for all 

polarizations (HH, VV, and HV). This may provide geomorphologic and geologic evidence indicating the possible availability of groundwater at economically recoverable 

depths, and will certainly add to our understanding of the attenuation and scattering introduced by these eolian and alluvial materials. However, given the widespread publicity 

of the successful SIR-A results from the Eastern Sahara, the SWG also wishes to empha - size strongly that the physical, chemical, and climatic conditions required for maximum signal 

penetration are stringent and that such conditions are likely to exist only within arid 

regions. The Eastern Sahara is perfectly suited to optimum radar signal penetration, being 

extremely dry, unconsolidated, and containing very small amounts of clay minerals that are 

known to severely limit signal penetration [4-11]. To help to set reasonable limits on 

regions proposed for desert penetration experiments for SIR-C, this plan provides a map of 

the semiarid, arid, and extremely and regions of the world (Fig. 4-16). This map, however, does not show the nearly 5 million km2 of polar deserts, which constitute over 3% 

of the earth's land area. Parts of the polar deserts may also be candidates for radar 

penetration. Penetration experiments restricted to the and and extremely and regions 

should have the greatest potential for success, but of course will depend on the lack of 

surface roughness, the degree of aridity, and physical, electrical, and chemical properties. 

4-44
MODERN SAND COVER TO SHUTTLE 

/ FROM SHUTTLE

_—SHUTTLE

AWAY FROM 

ID zZl,"I 0 ^ZX \,O\/ ID BURIED 0 

CHANNEL 

BEDROCK 

g 

& BRIGHT

x

-----_:iii----- 

VOLUME SCATTERERS 

VALLEY ALLUVIUM 

GRAZING OUTCROPS 

(DIFFUSE BACKSCATTER X 

AT SURFACE) 

RADAR INTERMEDIATE (j BURIED INHOMOGENITIES 

(VOLUME SCATTER) 

RADAR DARK 

BURIED FLUVIAL GRAVEL 

(SPECULAR REFLECTION 

FOLLOWING SIGNAL REFRACTION)

07::X7 X X X 

RADAR INTERMEDIATE 

BURIED BEDROCK INTERFACE 

(DIFFUSE BACKSCATTER 

FOLLOWING SIGNAL 

REFRACTION) 

Fig. 4-23. Penetration into dry sand covering ancient river beds. Subsurface scattering is 

introduced by hard-pan and volume scattering by calcium carbonate nodules 

semiarid 

regions 

possible rain 

events in 

semiarid regions

A second important category of SIR-C desert hydrology experiments would take full 

advantage of the "mapping mode." In this mapping mode, effective swath widths in 

excess of 150 km could be obtained from multiple passes. This would be particularly useful for studies of not only hyperarid regions, but also semiarid regions (see Fig. 4-16). 

Maximum areal coverage would require the lowest possible angle of incidence and would 

emphasize the like-polarization (HH and VV) and possibly degraded resolution in favor of 

more swath. Such mapping-mode experiments would provide synoptic overviews from 

which regional assessments of hydrologic potential could be made. These SIR-C mosaics 

could be more easily compared to Landsat TM and similar data. 

SIR-C experiments in the semiarid environment may be difficult to plan and conduct 

because of their dependency on climatic events, which are usually infrequent. However, 

the pointing ability of SIR-C instruments will make it possible to conduct some studies if 

the Shuttle crew can respond to short-notice (24-hour) data-collection requests. The most 

important of these studies would involve the spatial distribution of rainfall. The location of 

this experiment could not be planned in precise detail. Rather, the Shuttle and ground data 

crews would have to respond to synoptic weather observations, to approximately locate the 

convective rain cells. Rapid turnaround of SAR imagery would increase the chances of 

success because the ground data crews could be guided to areas where rain had fallen by 

the apparent soil moisture differences from the imagery. 

Range-condition experiments could be conducted within a Shuttle mission time frame. 

Sites of good and poor range condition could be identified before the flight and detailed 

ground data-collection programs could be conducted. The questions of interest for the SAR 

would be related to soil moisture, soil cover, and erosion. Poor-condition rangeland typically would have lower soil moisture, less-dense canopy of more woody vegetation, and an 

erosion-induced rougher surface. Good rangeland features would be the opposite. 

Multifrequency-multipolarization studies would be possible from successive orbital passes 

because we could generally expect little temporal change over the duration of the Shuttle 

mission.

4-45
Various semi-arid regions throughout the world have recently been selected as test sites 

in the International Satellite Land Climatology Project (ISLSCP). Objectives of the 

ISLSCP include the development of methodologies for obtaining quantitative land-surface 

climatological data from satellite observations. A SIR-C radar system would contribute 

significantly to a better understanding of the hydrologic processes by aiding in quantifying 

some of the physical surface parameters required in modeling the moisture and energy 

fluxes. Active radar measurements may complement existing satellite microwave radiometer data, which are currently being evaluated in surface wetness investigations under the 

ISLSCP Retrospective Analysis Program (IRAP). 

4.3.5.2 Humid Regimes 

Humid-area hydrology presents scientists with a set of problems that, although not 

necessarily unique to humid areas, are intensified there. Perhaps the most important of 

these is the spatial variability of most factors that affect a basin's hydrology and water 

balance. These factors include topographic features, both micro and macro, as well as 

soil properties and soil moisture, drainage patterns, land use, and subsurface features. 

A second major factor that affects humid-basin hydrology and that has been difficult to 

represent scientifically is the temporal effect of climate, both short-term (minutes and 

hours) and long-term (seasons). This temporal factor is complicated by the spatial variability of inputs, such as precipitation or potential evapotranspiration, and, in turn, their 

results, such as soil moisture or snow packs. 

Although much of the current research effort in hydrology is focused on these spatial 

and temporal questions, no dramatic breakthroughs have occurred. The characteristics of 

the multifrequency, multipolarization SIR-C instrumentation could provide some of the information needed to advance our understanding in these areas. The following experiment 

descriptions provide examples of important hydrologic issues relevant to SIR-C radar 

measurements. 

spatial 

variability 

and scale in 

hydrologic 

systems

There is a need to develop ways to measure the spatial variability of hydrologic parameters and variables, to determine the scale (size) of important hydrologic units, and to 

develop criteria for delineating areas that can be treated as hydrologically uniform. Partialarea hydrology is a hydrologic concept that has been formulated to account for spatial 

variability in watersheds. This concept is based on a dynamic watershed approach in which 

the sizes of subareas in a basin that produces runoff have dimensions that vary in time and 

space, subject to soil infiltration capacity as well as to storm duration and intensity. The 

source-area concept, on the other hand, is an attempt to account for the heterogeneous 

nature of natural watershed systems. 

The research questions dealing with spatial variability and scale can best be studied with 

a series of coordinated ground, truck, aircraft, and Shuttle experiments involving selected 

test sites. Detailed ground measurements at these sites will define the spatial variability of 

the hydrologic characteristics selected for study. The characteristics selected will be those 

that depict decreasing (degraded) resolution, but that at the same time average or integrate 

the point measurements into a single response for sequentially larger areas. One or more 

distributed hydrologic simulation models will be used to take these data as inputs, and the 

simulated results will be compared to each other and to measured watershed responses. 

These comparisons will be the basis for evaluating the hydrologic significance of spatial 

variability, and the scale of the important hydrologic parameters and variables. 

4-46
The SIR-C experiments should concentrate on the two layers of the earth's surface 

described in 4.3.4. The problems of scientific interest involve measuring spatial changes in 

the dielectric constant and measuring the nature (geometry) and biomass of the crop canopy. 

A single Shuttle flight is too short to ensure observing significant temporal changes in the 

target. However, two SIR-C flights scheduled approximately 6 months apart could be ideal 

for observing temporal changes resulting from seasonal effects. These studies should help 

determine the spatial distribution of the two surface layers and aid in studying the effects 

of topography (effectively incidence angle) on radar response. To account for topography 

and other unknowns, relative differences between SIR-C images acquired within one mission must be examined. Moreover, this should be done during both SIR-C missions, with 

one timed for wet-season coverage and the other for dry-season coverage. 

Runoff prediction is generally the single most important factor affecting water-resource 

decisions (e.g., flow controls, drainage design, water supply, hydropower, etc). Almost 

without exception, precipitation data are not adequate for accurate runoff predictions because the available rain gauges do not depict the spatial distribution of rainfall over large 

basins. Therefore, more accurate and timely precipitation measurements, especially in 

areas with few gauges, could prove highly beneficial. Radar has the potential for making 

real-time estimates of both precipitation distribution and intensity. 

radar The unpredictability of where and when rainfall will occur makes research in this area 

sensitivity to difficult to plan and conduct within the Shuttle flight duration of 7 to 10 days. However, 

soil moisture this difficulty could be overcome if Shuttle data-collection activities were sufficiently flexiafter rain events ble for measurements to be directed by ground observers. Depending on the dates of the 

Shuttle flights, some windows on the earth could be identified where there would be a 

good probability of significant (greater than 2-cm) rainfall at some point during the flight. 

Such experiments would require good weather forecasts and precise coordination between 

ground observers and the Shuttle crew. It would then be possible to examine time series of 

the drying of near-surface soil after saturation, which may be related to bulk soil hydraulic 

properties. 

correlation of A coordinated series of aircraft SAR and SIR-C tests should be designed to observe the 

SIR-C images radar response from rainfall as it is occurring and to measure the spatial distribution and 

with rain-gauge amounts of rainfall after the rain has ceased. These tests should be designed to demondata strate that SIR-C images can be correlated with rain-gauge data and to determine whether 

imagery can be effectively used to interpolate between rain gauges for improved precipitation estimation. See the section on semiarid hydrology for additional possibilities. 

direct The ability of remote sensing to take measurements over an entire area rather than at a 

measurement single point and to average the measurements' information for that area may lead to entirely 

of hydrologic new and powerful ways to characterize a watershed's hydrology. 

characteristics

The ability of microwave energy to penetrate vegetation (the degree of penetration 

depending on frequency, polarization, and angle) and to respond to soil structure, surface 

roughness, and soil moisture are perhaps the most important features for hydrologic applications. These are the four watershed features that affect rainfall runoff and historically 

have been used as input parameters for runoff models. However, in the existing hydrologic 

procedures, these features are seldom measured directly, but are estimated according to arbitrary relative scales. The ability to measure the features directly could be a significant 

breakthrough for improving hydrologic techniques. If successful, this procedure could provide an objective and cost-effective method for obtaining input data for operational hydrologic models.

4-47 
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Experiments of this nature could be conducted over a site where extensive ground data 

collection is feasible. Concurrent ground and Shuttle data collection would not be critical, 

and temporal changes would not be of major importance. Multiple angle, polarization, and 

frequency observations of the same site would be necessary. A one- to two-day revisit 

schedule would be necessary. 

flood 

mapping 

groundwater 

resource 

analysis

Radar imagery is useful for monitoring the extent of floods and their duration, even 

under forested conditions, as can be seen in the SIR-B image of the coast of Equador 

shown in Fig. 4-24. Experiments can be designed to study SAR response to land-water 

boundaries and to flooding where total inundation has not occurred (i.e., islands), and 

SIR-C experiments can define the optimum frequencies, angles of incidence, and polarizations needed for delineating land-water boundaries through crop canopies of various densities and geometries. These objectives are similar to the research needs for studying 

wetlands, and well-designed experiments should satisfy both needs. 

It may be possible to conduct groundwater resource experiments using SIR-C. The 

objectives of such an experiment would be to identify groundwater recharge and discharge 

areas in complex watersheds and to develop methods for conducting a resource inventory 

of groundwater by identifying seeps and springs and quantifying seasonal changes of 

groundwater elevation. 

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15°N 

10s

95W 7O 

Fig. 4-24. SIR-B image of flooded forest in coastal Ecuador 

4-48
Identifying groundwater recharge and discharge areas is a major aspect of any landmanagement program and is important to meeting certain surface-water and groundwater 

pollution-control objectives. Conventional methods of groundwater assessment are time 

consuming and costly, and any procedure that could do it more efficiently would be extremely helpful. Groundwater discharge areas often respond to seasonal differences in 

precipitation and evapotranspiration, and the two-flight SIR-C should provide a basis for 

observing spatial changes in groundwater discharge and recharge areas resulting from 

seasonal differences in soil moisture and surface water. 

4.3.5.3 Wetlands 

Because trace-gas fluxes in wetlands form a major component of the global biogeochemical cycles, wetlands are among the most important of the world's ecosystems. The 

role that wetlands play as filters, or sinks, for a wide variety of pollutants is well-known; 

wetlands act as extremely effective buffers for nearby, less resilient ecosystems (e.g., estuaries). Although limited in area compared with the major ecosystems of the world, coastal 

wetlands have a high per-unit-area productivity and contribute substantially to estuarine 

productivity as well. Wetlands are extremely vulnerable to alteration by humans. Drainage 

to expand urban areas or produce useable land for agriculture or forestry can drastically 

affect biogeochemical cycles and estuarine productivity and pollution levels. A rise in sea 

level, postulated as a result of global increases in atmospheric carbon dioxide, could result 

in a substantial loss of coastal wetlands. Changes in rivers (e.g., channelization, increases 

or decreases in sediment load, or alterations in flow volume or pattern) could also substantially affect wetland extent and processes. If wetlands are to be properly used and protected, 

it is important that they be effectively mapped and their status monitored. An accepted approach uses color infrared (CIR) photography for analysis, which is a reasonable method 

for determining relative biomass and for overall species discrimination. CIR imagery cannot, however, define the land-water interface in densely vegetated shoreline areas. Nor 

can it reliably locate boundaries between the various wetland "water regimes," i.e., soil 

saturation levels. SIR-C multiparameter imagery used either alone or in conjunction with 

photography or multispectral scanner imagery in the visible and near-IR wavelengths 

should be able to overcome these significant gaps in effective wetland-mapping analysis. 

wetland One significant problem in mapping wetlands is simply defining where they begin and 

boundary end. A wetland lying hard against a water body is easy to delineate if the vegetation stops 

delineation at the water's edge, but not if the vegetation continues into the water. However, a plantobscured boundary should be definable by longer-wavelength radar energy, which penetrates the vegetation and is either reflected off the water's surface or backscattered strongly 

from the usually moist substrate near the water's edge. The L-band channel of SIR-C 

(23-cm wavelength) will penetrate wetland grasses and shrubs, but areas of larger wetland 

tree species will probably show stronger returns in the images. The C-band channel should 

behave similarly, except that even smaller flooded trees will cause significant image brightness. It would be desirable to determine the optimum wavelength and polarization for 

shoreline delineation in areas of various vegetation densities and stem sizes. This shoreline 

delineation is dramatically illustrated in the SIR-B image of Florida wetlands in Fig. 4-25. 

A problem similar to shoreline delineation is that of defining the upland boundary of a 

wetland. A transect across a typical estuarine wetland would pass from the water to the 

saturated-soil wetlands that are inundated daily, then to the wetlands inundated less than

4-49
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Fig. 4.25. SIR. B image of Florida wetlands 

daily (which may or may not have saturated soils) then to the areas that are irregularly 

flooded and only seasonally have saturated soils, and finally to the uplands. These transition zones normally cannot be delimited on color infrared photography or on equivalent 

multispectral scanner imagery. However, it may be possible to see these transitions in 

SIR-C imagery, depending on how well longer-wavelength radar can portray differences in 

soil-moisture areas covered by vegetation. Besides determining optimum wavelengths and 

polarizations, we need to determine to what extent specific wetland water regimes can be 

defined in the imagery. 

The water regime is a key factor for biogeochemical cycling in wetlands. Major fluxes 

of trace gases, such as methane, occur only under reducing conditions in the soil. Reducing conditions are created when soils are covered by water, which prevents oxygen from 

4-50
entering the soil matrix; thus, the duration and extent of inundation controls the amount of 

trace-gases released into the atmosphere. Despite their small areal extent, wetlands can contribute to the atmosphere a major proportion of the terrestrial trace-gas flux. Coupling of 

ground measurements with remotely sensed information on the spatial extent and the temporal dynamics of flooding could yield significantly improved estimates of regional tracegas fluxes to the atmosphere. 

The water regime also influences wetland and estuarine productivity. As water flows 

over a vegetated surface, it brings a fresh supply of nutrients to the plants. Wetlands more 

frequently inundated are often more productive. Water flowing out of a wetland area removes organic detritus, which then serves as the basis for secondary productivity in riverme and estuarine ecosystems. 

It may not be sufficient to determine the upper and lower boundaries of wetlands; it may 

also be necessary to determine the patterns of inundation within the wetlands. The spatial 

resolution of SIR-C should be adequate for the investigation of coarse-scale patterns of 

flooding. Fine-scale distributary channels may not be discriminable. 

Determination of water regime is of extreme importance because of its influence on tracegas fluxes, vegetation type, and productivity in wetlands. This information could also be 

useful in settling disputes over public versus private ownership of land. 

vegetation 

discrimination

From a wetlands-analysis standpoint, it would be desirable for SIR-C to include X-band 

imaging radar to augment the L- and C-band imagery. Earlier investigations have shown 

that X-band can discriminate broad classes of vegetation in wetland settings and that when 

X-band is augmented by L-band, discrimination is further improved. The major advantage 

of L- and C-band imagery of wetlands is complete-to-partial penetration through the vegetation to the moist soil underneath. While it is desirable to know which of these two wavelengths is better for measuring relative soil saturation in wetlands of different vegetation 

density and species makeup, it would be even more beneficial to determine which frequency 

and polarization combination (among X, L, and C) would be best for discriminating vegetation types. 

An example of the type of wetlands site that might be studied is the estuarine system 

lying near Galveston, Texas, which contains low-lying estuarine wetlands that are perennially saturated. The barrier systems contain palustrine wetlands (dune swales) as well as a 

variety of estuarine wetland classes. The area of the Trinity River, which empties into the 

Galveston estuarine system, includes riverine and lacustrine systems, and also forested wetlands standing in relict oxbows. This area encompasses many pristine and modified wetland systems: the Gulf Intercoastal Waterway cuts completely through the area and 

portions of the lower Trinity have been severely channelized. There is a great variety of 

wetland vegetation species and wetland habitat classes. This wetland system has been classified and mapped recently as a part of the U.S. Fish and Wildlife Service's National 

Wetlands Inventory. 

4.3.5.4 Snow-Covered Watersheds 

In many areas of the world, the majority of fresh water available for consumption and 

irrigation results from snowmelt runoff. Snowpacks providing domestic water supplies are 

found in varying settings; many are in rugged mountainous terrain, while others are in

4-51
higher-latitude moderate-relief plains areas. Determination of available water in the snowpack just prior to melt season is important for the proper management of river impoundments and for reservoir regulation. SARs operating at shorter wavelengths offer an 

all-weather capability to regularly monitor changes within the snow and provide useful information to water managers. There are three snowpack measurements of interest: 

(1) Areal extent 

(2) Snow-water equivalent 

(3) Condition of the snowpack 

Each has a specific set of parameters that affect the microwave signal and that vary during 

the snowmelt season. These parameters include moisture in the underlying soil, whether 

the soil is frozen or unfrozen, vegetation under the snowpack, whether the plains are 

forested, and varying topographic relief. These parameters principally affect the radar scattering coefficient, which can exhibit significant temporal changes during the melt season. 

The microwave response, both active and passive, to snow-water equivalent and liquidwater content increases as the frequency is increased above 10 GHz. By using truck 

cherry-picker-borne radiometers and scatterometers, Ulaby and Stiles [4-9] have been able 

to quantify the radar and radiometer response to snow. Figure 4-21 shows the radar scattering coefficient as a function of frequency for various levels of snow-water equivalent. 

This indicates that we may expect some C-band sensitivity to snow, at least for thicker and 

wetter packs, but that for this purpose the X-band channel is even better. 

For the SIR-C mission it is desirable to have a polar orbit available in late winter 

through spring, since otherwise the snow cover and thickness may be insufficient for observation. Changes in the snowpack would certainly be observable at X-band, and to a 

lesser extent at C-band. Other microwave data, however, such as from the L-band channel, or from ancillary ground or aircraft microwave radiometer data at selected test sites, 

would act synergistically to provide a more complete analysis of snowpack conditions. The 

effect of frequency and polarization dependence could also be addressed. 

Snow hydrology problems suitable for study with SIR-C data would include the detailed 

measurement of snow-cover area (i.e., the delineation of snow-nonsnow boundaries), the 

measurement of changes in snow properties (wetness, water-content, grain size) with elevation and aspect, and the measurement of snow properties through vegetation (forest) canopies. These experiments could be carried out during a Shuttle mission of 7 to 10 days by 

selecting a study site with the kind of aspect and elevation variations that would provide 

differences in snowpack properties. The effects of topography on radar response (i.e., the 

effects of slope and aspect, both of which can cause the angle of incidence to vary) is a 

major research question that must be answered before operational snow-monitoring sensors 

can be considered. 

4.3.5.5 High-Latitude Regions 

glaciers SIR-C provides an excellent opportunity to expand our limited knowledge about 

SAR remote sensing of glaciers. A further discussion of this potential is presented in 

Section 4.5.5.3. 

4-52
permafrost Figure 4-1 shows the distribution of different types of permafrost terrain in the Northern 

Hemisphere. Little quantitative information is available on microwave response to permafrost, so it is difficult to predict what the SIR-C response to permafrost features will 

be. However, there are several permafrost features of interest, including its depth; the effects of the overlying soil, whether saturated (coastal) or unsaturated (inland); and the effect of changes in terrain and vegetation. 

Assessment of these features and their effects on the radar signatures will be difficult, if 

possible at all. Permafrost should be viewed as a target of opportunity. Data will be required at different times during the year, to separate the effects of changing surface vegetation. Variations in terrain, soils, and geomorphology will necessitate the selection of 

several test sites at coastal and inland regions. Previously collected Seasat SAR data will 

provide a basis for the formulation of the required studies, which will include consideration of the permafrost signature as related to different frequencies (L- and C-, and possibly 

X-band), polarizations, and viewing angles. 

4.3.6 Summary of SIR-C Mission Requirements for Hydrology 

It is clear that most SIR-C hydrologic research investigations will require plans that 

carefully coordinate SIR-C observations with in-situ field observations of a limited number 

of well-selected sites. Because of the wide diversity of hydrologic regimes, there is no 

common set of SIR-C mission parameters that is optimum for all hydrologic research 

topics. However, there are unifying themes. For example, all areas require radar parameters 

that maximize sensitivity to soil moisture, e.g., longer wavelengths and near-nadir angles 

of incidence. Vegetational investigations, e.g., in humid and wetland regions, will seek to 

use shorter wavelengths and diverse polarization. This section attempts to summarize the 

principal SIR-C mission requirements for the majority of the hydrology experiments. 

4.3.6.1 Orbital Parameters 

high-latitude A high-inclination orbit is required for observations of high-latitude hydrologic 

orbit regimes, including permafrost, glaciers, and snow-covered watersheds. A drifting orbit, 

requirement which would allow wide-area coverage (mapping mode) at near-nadir angles of incidence 

(for soil moisture) is best for arid-region studies. However, orbits providing a revisit cycle 

of 1 to 2 days are preferred for humid regions and wetland studies. Many of these experiments will require a comparison of repeat-coverage images. 

two-flight 

requirement

4.3.6.2 Mission Timing 

The most desirable mission timing is that which would provide continuous observations 

of the earth from space, thus allowing studies of temporal variability in various hydrologic 

regimes. Since this is not possible with SIR-C, the next-best timing requires two Shuttle 

flights separated by about six months, using the same orbit inclination and launch times, so 

that the mission ground tracks will coincide. The scientific benefit would depend, of 

course, on when during the hydrologic year the flights occurred.

4-53
There are also a number of important hydrology research opportunities that are afforded 

by a Shuttle flight of 7 to 10 days. These studies would focus principally on optimum instrument response (wavelenghts, polarizations, and illumination geometries) for target characteristics such as soil moisture, vegetation canopy interaction, surface roughness, topography, 

and snow or ice cover. Carefully chosen target areas may allow these characteristics to be 

experimentally controlled by changing soil moisture through irrigation, by changing surface 

roughness through tillage, and by the removal of vegetation canopies. 

4.3.6.3 Swaths, Resolutions 

The swath width required depends on hydrologic regime. Wide swaths of 100 to 200 km, 

built up through several contiguous passes, would be required for studying hyperaridregion geohydrology, glaciers, or sites of opportunity such as flooded areas. On the other 

hand, a coastal wetland may require a swath of only 15 to 20 km. A resolution of approximately 30 m is adequate for wetland and humid regions, whereas a resolution of 15 to 

100 m may be adequate for hyperarid-region research. 

4.3.6.4 Frequencies, Polarizations, Incidence Angles 

For soil moisture investigations, L-band and C-band with like polarization (HH and VV) 

at near-nadir angles of incidence (e.g., 20°) are preferred. Vegetation-cover studies for 

humid regions and wetlands will require the use of C-band and, if available, X-band. 

These studies will also require both like- and cross-polarization imagery acquired at higher 

angles of incidence. X-band and, to a lesser extent, C-band are best for investigating 

snow. Studies of the penetration of hyperarid regions will concentrate on the longer wavelengths, e.g., L-band, with both like- and cross-polarization. 

4.3.6.5 Data Products 

need for relative 

calibration of 

±1 dB

For maximum sensitivity to soil moisture changes (especially in the presence of vegetation), it is desirable for SIR-C to achieve a relative radiometric calibration (stability) of 

about ± 1 dB. In order to relate the absolute level of L-band response to that at C-band, it 

is desirable to achieve an absolute radiometric calibration of ± 1 dB (relative to each 

other) or better. 

Because ground control points can be used to establish location on a cartographic grid, 

absolute geometric calibration is not critical, although it is critical that the relatively narrow SIR-C swath be located in the ground-range image to within 5 km or better of the 

ephemeris-predicted value. Most hydrologic investigations will require SAR image 

products to be geometrically rectified to a standard cartographic grid, and some will require geocoded images. 

4-54
4.4 Vegetation Science 

4.4.1 Background 

the earth's Vegetation is responsible for the primary production of life's essentials—from oxygen 

ecosystem to fuel—on the earth. Energy is captured as carbon is fixed photosynthetically by green

plants, and for this process to take place, solar radiation, water, and certain essential elements are required. The entire planet can be viewed as a single ecosystem, with the biota 

(plants, animals, humans, and other organisms), the biogeochemical cycles (such as those 

of carbon, nitrogen, phosphorus, sulphur, etc.), the hydrological cycle, and the earth's 

energy balance all inextricably linked. Thus, any change in the environment that affects 

photosynthesis also affects some aspect of the water, carbon, and chemical balance of the 

system. Moreover, the future habitability of the earth may be affected by any drastic 

changes in the states or fluxes of any of these components. 

The goal of vegetation studies is to develop an understanding of the state of the earth's 

vegetated surface, the major fluxes through it, and the major exchanges between vegetation 

and the hydrosphere, lithosphere, and atmosphere. Past regional-scale research has focused 

on determining states, i.e., on vegetation mapping, documenting land cover and land use, 

and classifying crops and vegetation. Prior to the early 1970s, the documentation of land 

cover and land use relied on several types of historical data and statistics that included 

vegetation and land-use maps as well as agricultural and forest-production statistics. These 

sources of data, however, were limited to only a few regions of the world, and the accuracy of the data was often unknown. A major difficulty in studying the dynamics of the 

global biogeochemical and hydrological cycles has been the spatial heterogeneity inherent in 

the terrestrial components of these systems. 

4.4.2 The Role of Spaceborne Remote Sensing in Vegetation Science

key vegetation The vegetation phenomena that are amenable to study by remote sensing include 

phenomena

(1) The spatial extent and distribution of vegetation 

(2) Landscape patterns 

(3) The water content of plant canopies 

(4) The biogeochemical composition of and fluxes through canopies (postulated) 

(5) The structure and orientation of canopies 

(6) Productivity (either biomass or net primary productivity) 

Of these, the determination of the type, distribution, and spatial extent of vegetation, and 

the estimation of biomass, have received the most attention. 

extension by Beginning with the Landsat remote sensing program in 1972, land-cover summaries have 

radar of been updated frequently and with increasing reliability. Optical scanners have proved quite 

detectable range useful for crop biomass estimation and forest and rangeland inventorying and mapping. 

of LA! variations However, to achieve high rates of identification accuracy, it has been necessary to use 

multidate observations (which are often difficult to accomplish in a single season because 

of the presence of cloud cover). The biomass per unit area, of which the green leaf area 

index (LA!) is one estimate, was identified as being a key to the dynamics of the carbon 

cycle. Landsat MSS data have been used to estimate LA!. However, the technique is insensitive to LAI values greater than about 4, and in some forest environments, LA! values may

4-55 
-5 

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0

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Iz -10 

U 

0 U 

(5 

Z 

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exceed 20. Recent research results (Fig. 4-26) indicate that it may be possible to measure 

LAI using radar over a wide dynamic range [4-12]. Recently, it has been suggested that 

productivity (a flux), rather than biomass (a state) may be the more important factor in 

understanding the carbon cycle—especially the effects of perturbation on the carbon cycle. 

Estimates of LAI from the beginning through the end of a growing season may provide 

such an estimate of productivity. 

4.4.3 The Role of Imaging Radar in Vegetation Science 

radar sensitivity 

to plant-canopy 

water content, 

LA!, and structure

Radar should provide complementary biophysical information about vegetation canopies, 

such as plant water content, leaf area index, and canopy structure. Optical sensors are 

most sensitive to plant structure at the micrometer scale, whereas radar responds to the 

centimeter and decimeter scales (see Fig. 4-27). Optical waves cannot penetrate deeply into 

thick vegetation canopies, but microwaves penetrate to varying extents, depending on frequency, polarization, and angle of incidence. Furthermore, because the target-wave interaction mechanisms are significantly different in the optical and microwave spectral regions, 

certain cover types that are difficult to discriminate in one spectral region are easy to discriminate in the other. These and other complementary attributes suggest that algorithms 

developed for monitoring vegetation resources in the future will employ data provided both 

by optical scanners and by imaging radars. 

4.4.4 The Scientific Basis for SIR-C Vegetation Science 

Experiments 

need for global Radars with multifrequency and multipolarization capabilities are powerful tools for 

data sets probing vegetation canopies. Extensive research conducted over the past two decades using 

multifrequency and multipolarization radars has led to numerous results, including algo-

-20

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I I T T I I T I 1 I I I I 1 I I 1 I I 1 I I

I I I T 

- . 

-

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- WINTER WHEAT 

13.0GHz 

- VV POLARIZATION 

6=50° 

I I I I 111111111 I I I I I 

0 1 2 3 4 5 6 7 8 9 

LEAF AREA INDEX (LAI), m2m2 

Fig. 426. Microwave response to leaf area index (LAI) 

4-56
SIZE DISTRIBUTION OF 

CANOPY SCATTERERS - 

MM 1 cm 10 CM im 

SIZE OF SCATTERER 

TWIGS LEAVES BRANCHES TRUNKS 

>-

U, 

Z 

ca

LU 0 

LU 

Z

contributors 

to radar 

backscattering

Fig. 427. Radar model of idealized response to various wavelengths according to the 

size distribution of canopy scatterers 

rithms and models for separating vegetation cover types and estimating biophysical properties (most notably water content and leaf area index). The research, however, is based 

almost exclusively on observations of crops made from ground-based and airborne platforms. Consequently, the models and algorithms thus developed are somewhat site- and 

time-specific and are therefore limited in applicability. SIR-C offers the first opportunity to 

verify and extend the research of the past two decades by providing calibrated, multifrequency, multipolarization data for a variety of different geographic regions and conditions 

over the globe. 

A short review of radar vegetation research is given in the SIR-13 Science Plan 

[4-13] and more extensive reviews are available [4-14, 4-8]. Instead of providing yet 

another review, this section will focus on the roles of frequency and polarization as they 

pertain to vegetation canopies. 

The total signal backscattered from vegetation-covered ground consists, in the general 

case, of three types of contributions, as illustrated in Fig. 4-28. These include 

(1) Direct backscattering from plants 

(2) Direct backscattering from the underlying soil surface (allowing for two-way 

attenuation by the canopy layer) 

(3) Plant-soil multiple scattering contributions

4-57
• DIRECT BACKSCATTER FROM PLANTS, X-BAND 

( DIRECT BACKSCATTER FROM SOIL, L-BAND 

(INCLUDES TWO-WAY ATTENUATION BY CANOPY) 

PLANT/SOIL MULTIPLE SCATTER, C-BAND 

2

Fig. 4.28. The role of frequency in canopy backscatter 

polarizationdependence of 

attenuation by 

plant canopy 

increase of 

canopy loss 

with frequency

The magnitude of these contributions and their variation as a function of sensor parameters 

(wavelength, observation direction, and polarization configuration) depends on many factors, including the following: 

(1) The dielectric constant of the vegetation material, which is strongly influenced by 

moisture content—because moisture content may be significantly different for different canopy constituents (such as leaves, stems, and fruit) depending on growth 

stage, the dielectric constants of the canopy constituents may vary as well 

(2) The size distribution of the scatterers in a canopy 

(3) The shape distribution of the scatterers in a canopy 

(4) The orientation distribution of the scatterers in a canopy 

(5) The roughness and dielectric constant of the underlying ground surface 

(6) The canopy cover's geometry, including cover fraction, plant height, plant spacing, 

and row direction in agricultural fields 

Representative samples of canopy-loss measurements are shown in Figs. 4-29 and 4-30 

for a canopy of winter wheat. Direct-transmission measurements were made using a transmitter placed atop a truck-mounted boom, and a receiver mounted on a rail placed on the 

surface of the soil. The measurements shown were made at frequencies approximately the 

same as those of SIR-C. 

The role of frequency is well demonstrated by the curves in Fig. 4-29, which represent 

two stages of growth characterized by LAI values of 4 and 8. Whereas the canopy is 

quasi-transparent at L-band at both stages of growth (the two-way loss is less than 

4.2 dB), the canopy is effectively opaque at X-band, particularly for the higher-LA! canopy (the two-way loss is 57.6 dB). 

A canopy in which a significant portion of the biomass is contained in constituents having 

a preferential orientation—such as vertical stems—will tend to exhibit polarization-dependent 

attenuation properties. The curves in Fig. 4-30 show that, as a result of the strong coupling between a vertically polarized incident wave and the vertical stems, the canopy at4-58
42 

36 

30 

-o

24 

0 

I-LI

18 

1) 

U, 

0 -j 12 

6 

0

40 

32 

-o 

-, 24 

0 I-Li 

U16 

0 

.1

8 

0

7 9 11 13 

L-BAND C-BAND X-BAND

FREQUENCY, GHz 

Fig. 4-29. Loss factor of wheat canopy 

FREQUENCY, GHz 

Fig. 4.30. Role of polarization in canopy penetration 

tenuation is significantly higher for V polarization than for H polarization. It is hypothesized 

that the majority of the loss experienced at L-band and C-band is attributed to the stems in 

the canopy, whereas the randomly oriented leaves become the dominant attenuators at 

X-band, thereby resulting in a smaller difference between the two curves than at lower 

frequencies. 

role of The orientation of the polarization vector of the incident wave affects not only the abpolarization in sorption by the canopy constituents but also the scattering, including the backscattering, 

backscatter direction. Thus, the polarization of the wave determines the effective depth of the volume 

responsible for the observed backscattered energy, as well as the intensity of the backscat4-59
tered signal. As one might expect, the effective depth of penetration for HV is intermediate between that for VV and HH, and the signal is caused by second-order or higher 

scattering. Figure 4-31 illustrates how multipolarization images may be combined to enhance the discrimination among different target categories in a forest environment. 

Temporal frequency is an important asset in any remote sensor used to observe a 

dynamic phenomenon such as vegetation. According to a study conducted by Hoogeboom 

[4-15], when single-date X-band radar images of a test site in The Netherlands were used 

for crop-identification purposes, only 30% of the fields (consisting of 182 fields comprising seven crop types) were correctly identified. When data from three dates were used 

together, the identification accuracy improved to 88%. Once a vegetation cover type has 

been correctly identified with a high degree of estimation accuracy, the next step is to estimate its biophysical properties. This may be accomplished through multifrequency, multipolarization, multiangle, and/or multidate observations. An example illustrating the 

temporal variation of the scattering coefficient is shown in Fig. 4-32 for a field planted in 

winter wheat. If multidate, calibrated radar observations are available, it should be possi41e to estimate stage of growth as well as LAI. Algorithms to provide this type of information from single-date, multifrequency, or multipolarization data are not available at 

present. 

4.4.5 SIR.0 Vegetation Science Experiments 

experiment The primary objective of the SIR-C vegetation science experiments is to address the sciobjec fives entific questions related to the information needs stated above. It is desirable, although not 

required, that experimental designs take into account the role of the SIR-C mission as a 

major step in the evolution of the spaceborne imaging radar project towards an operational 

free-flyer on EOS. Another desirable, but not required, possibility for the SIR-C vegetation experiments would be to concentrate the majority of the experiments on a select set of 

six to eight supersites. The supersite approach allows several investigators to use a common set of ground observations and aircraft support data. In terms of exact location, the 

supersites will be chosen to suit the scientific objectives of the SIR-C Science Team. As a 

general guideline, however, it is recommended that 

vegetation (1) At least one of the supersites encompass a major agricultural area so that the algosupersites rithms and models developed from ground-based studies of crops may be tested 

(2) The remaining test sites encompass areas that are good representatives of the earth's 

major ecosystems, such as grasslands, deciduous forests, mixed forests, rain forests, 

and tundra 

The second category includes representative vegetation types and will serve to provide concrete data to researchers, thus allowing them to develop models and algorithms to relate 

the radar scattering response to the biophysical properties of these vegetation canopies. 

It is understood that information derived from the SIR-C experiments will be used 

either to serve as input to or to build biophysically based models of canopy structure and 

function. Modeling must be an essential component of any overall effort to understand 

regional and global processes; it should therefore be a part of the SIR-C vegetation-science 

investigations. 

The following material discusses several classes of vegetation science experiments that 

could be conducted using SIR-C. However, the list (summarized in Table 4-4) should not 

be regarded as all-inclusive or complete.

4-60 
b41i; 

:T1 Pon Mae%. 

3 bbi2i ii4; 

L

LH H L VH LV V 

ILLUMINATION DIRECTION

-; JQF ..POOR

: 11W t 

RED -HH Kr 

N\ GREEN VV

BLUE = VH 

Fig. 4.31. Illustration of how multipolarization images may be combined to enhance discrimination among different target 

categories in a forest environment

4-61
10 

X 

LU

5 

<C'9 

ac 

UUi 

-J

0.25 

0.20 

U 

UU--

0.15 

CNe 

°b 0.10 

U 

U

0

GROUND-TRUTH 

MEASUREMENTS 

I I_i I I I I 

II I'I I I 

BOOTING WINTER WHEAT 

13.0 GHz 

WPOLARIZATION 

8=50° 

SECOND HEADING 3/4 NODE COMPLETE

CARYOPSIS HARD 

ANTITHESIS SOFT DOUGH 

COMPLETE

FIRST 

NODE

7 

MILK RIPE 

I I I I I 

110 120 130 140 150 160 170 180 190

JULIAN DATE (1979) 

Fig. 4. 32. Radar temporal signature of winter wheat 

Table 4.4. Some SIR.0 vegetation science experiment classes 

Experiment Class Scientific Objectives 

Identification and mapping of Identification of forest, rangeland, crops, etc. and determination 

vegetation types of their distribution and spatial extent (single and multidate, 

radar only, radar plus optical) 

Interpretation of landscape patterns To understand the major factors influencing the spatial extent 

and processes and distribution of vegetation and how changes in these 

factors affect regional processes 

Assessment of the biophysical To determine canopy structure, species geometry, foliage 

properties of plant canopies characteristics, and seasonal variations, and to estimate stand 

volume, canopy water content, soil moisture, LA!, and 

biomass 

Determination of the radar To assess penetration of various radar frequencies and polarizapenetration of canopies tions in different canopy types

4.4.5.1 Vegetation Type Identification 

single-date The SIR-C mission will allow experiments to evaluate the information content from 

experiments single date SAR data for vegetation type identification as a function of frequency (L, C, 

and X), polarization (HH, HV, VV), and angle of incidence (150 to 600). These evaluations 

could be made by: 

4-62
(1) Crop groups (e.g., small grains, irrigated crops, etc.) 

(2) Forest types (e.g., by dominant species or by evergreen versus deciduous habits) 

(3) Physioagronomic regions (i.e., soil type, climate, cultural practices, etc.) 

(4) Weather conditions 

(5) Time of day 

(6) Topography 

(7) Phenology 

multidate 

experiments 

radar/optical 

combination

If the SIR-C flight schedule is such that it is possible to make two observations corresponding to two different stages of growth, it would be useful to evaluate the improvement in crop-, grassland-, or forest-identification accuracy provided by the temporal 

dimension. Therefore it is recommended that the SIR-C mission consist of two flights, and 

that the flight dates be in the May-June and August-September periods of the same calendar year. 

It is also desirable to evaluate the complementary and redundant aspects of radar and 

optical (e.g., Thematic Mapper) data for vegetation identification. For forest types, this 

should also include multi-temporal studies (seasonal variations and/or changes since 1978 

[Seasat SAR], 1981 [SIR-A], or 1984 [SIR-B], as well as the optical data [TM]). 

4.4.5.2 Interpretation of Landscape Patterns and Processes 

The measurement of the areal extent and distribution of terrestrial biomes and the 

changes in them has been one of the basic objectives of all land remote sensing activities. 

Surface-texture information (e.g., gradual or abrupt changes in canopy height; the frequency 

and distribution of canopy gaps) from SIR-C (multifrequency, multipolarization, and multiangle) should be extremely useful in the interpretation of regional landscape patterns. Inferences about landscape dynamics may also result from the investigation of radar 

penetration of canopies. 

4.4.5.3 Biophysical Properties of Canopies 

Studies are needed to assess the dependence of the radar backscattering coefficient on 

the biophysical properties and conditions of plant canopies and on the underlying soil or 

overlying snow cover (if any), including: 

(1) Productivity and phytomass (LA!) 

(2) Canopy structure 

(3) Stress 

(4) Soil moisture 

(5) Snow-water equivalent 

The study should incorporate an evaluation of the roles of frequency, angle of incidence, 

polarization configuration, and optical data.

4-63
The identification of crops and assessment of their biophysical properties using imaging 

radar is often complicated by the presence of confusion factors. The radar coefficient depends not only on the type of crop under study (and its biophysical properties), but on soil 

roughness, row direction, row structure, the action of wind and rain, and the presence of 

dew. Even though some ground-based experiments have been conducted to estimate these 

effects, no definitive studies have been carried out using satellite radar data. It is recommended that experiments designed to estimate these disparate effects be conducted with 

SIR-C, using all combinations of wavelength, polarization, and angle of incidence. 

forests We need to assess radar response to the biophysical properties of forest structure and to 

foliage variables such as: 

(1) Stand volume 

(2) Productivity or phytomass (LA!) 

(3) Seasonal variations (leaves on or off, snow cover, etc.) 

(4) Stress (moisture, insect infestation, etc.) 

(5) Tree-species geometry 

(6) Clear-cut areas 

(7) Foliage characteristics (broad leaves, needles) 

(8) Stand structure (multiple-layer, tropical, understory vegetation) 

sparsity of data Very little information is available about the radar response to rangeland. SIR-C will 

on range/and provide an opportunity to evaluate the LAI, phytomass, plant morphology, and snow-water 

response equivalent of the various types of grasslands and shrublands. Such an evaluation should 

use the full multiparameter capability of SIR-C to determine the effects on radar response 

of species composition, soil type, topography, cultural practices, and weather conditions. 

4.4.5.4 Radar Penetration of Canopies 

frequency and From a practical point of view, we need to develop a better understanding of both how 

polarization roles much a plant canopy attenuates radar waves (as a function of wavelength, polarization, and 

in canopy angle of incidence) and how radar image texture can be used for the identification and asattenuation sessment of the biophysical properties of vegetation. In the former case, SIR-C will provide an excellent opportunity to conduct experiments on canopy attenuation at L-, C-, and 

X-band, for HH, VV, and HV polarizations, and for angles of incidence ranging from 15° 

to 600. In the latter case, we know that radar image texture is the spatial spectrum of 

image tone and is a consequence of natural variations in the imaged scene (over and above 

signal-fading fluctuations). SIR-C will thus provide an opportunity to use textural information (in addition to tonal information) for the identification of vegetation and the assessment of its biophysical properties. 

Thus, it is desirable to evaluate the variation of canopy with 

(1) Frequency 

(2) Polarization 

(3) Angle of incidence for various types and conditions of vegetation canopies, including 

cultural vegetation, trees, and grasses

4-64
4.4.6 Summary of the SIR-C Mission Requirements for 

Vegetation Science 

4.4.6.1 Orbital Parameters 

In order to include coverage of tundra vegetation (e.g., sedges, lichens, mosses), a high 

orbital inclination is required. 

4.4.6.2 Mission Timing 

need for Ideally, repeat coverage every 10 to 15 days during the growing season is needed to 

May-June and study the phenologic development of vegetation. However, very useful information could 

August-September be obtained from two SIR-C flights, one in the May-June time period and the other in the 

flights August-September period. 

4.4.6.3 Swaths and Resolutions 

criticality of A resolution of 30 m with at least four looks is adequate for many vegetation studies. 

narrow swaths Although 50- to 100-km swaths would be desirable, most experiments can use narrower 

crossing supersite swaths (20 to 30 km), when more simultaneous channels (frequencies, polarizations) are 

acquired. However, since supersites will be extensively used, it is critical that narrowswath passes cover these sites. 

4.4.6.4 Frequencies, Polarizations, and Incidence Angles 

need for For most of the experiments, it will be advisable to acquire as many simultaneous chanhigher angles nels (frequencies, polarizations) as possible, because this will permit valuable studies of 

of incidence canopy penetration, canopy volume scattering, etc. Although it is desirable to acquire data 

at all angles of incidence (15° to 600), it is expected that the higher angles of incidence 

(40° to 60°) will minimize the confusing effects of subcanopy surface scattering, particularly at C- and X-band. 

need for relative 

calibration of 

±1 dB and 

absolute 

calibration of 

+3 dB

4.4.6.5 Data Products 

In general, SIR-C imagery having pass-to-pass coregistration to within half a pixel is 

desirable. Images of vegetation supersites should be rectified (with respect to the ground) 

to within half a pixel. SIR-C images should maintain at least ± 1 dB of relative calibration 

or stability both within a frame and over the duration of the mission. Absolute accuracy of 

+3 dB is desirable. Because of the importance of using ground-truth teams to collect data 

from the experiment sites, it is critical that the swath be located within ±20% of the 

swath width.

4-65
The relative calibration requirement is important for several of the vegetation experiments 

listed in the previous section. For most vegetation scenes, the dynamic range of the backscattering coefficient seldom exceeds 10 dB (for a given frequency, polarization, and narrow angular range), and often is less than 6 dB. Hence, it is important that system-related 

variations both within a frame and between frames be confined to less than 1 dB. 

4.5 Glaciology

4.5.1 Background 

value of 

remote sensing 

to glaciology

Glaciology, which is the scientific study of ice in all its forms, is a field of investigation 

to which remote sensing has much to offer. The reasons for this are several. The areas 

where large snow and ice masses occur are extensive. They are also typically remote, being primarily beyond the range of human activity and hence of conventional surface observations. In addition, they are regions where it is commonly difficult and dangerous, as 

well as expensive, to carry out conventional surface observations. Finally, the polar 

regions where the largest ice masses occur are also shrouded in clouds and in darkness for 

much of the year, thereby restricting the effectiveness of many types of observing systems. 

The specific objectives of glaciological remote sensing vary widely, depending on the 

type of ice mass under study. In the following, we will discuss these different ice masses 

and their characteristics in the context of their different observational needs and objectives. 

need for 

sea-ice data

4.5.1.1 Sea Ice 

The polar oceans and seas are covered, at least seasonally, with a shifting and broken 

ice pack. For an adequate description of this ice, data are needed on ice extent, ice types, 

ice roughness, ice thickness, drift velocities, growth and melting rates, lead and polynya 

patterns and frequencies, flow size distributions, pressure ridge patterns, snow cover, and 

ice island and iceberg sizes and locations. This information is required both on a synoptic, 

timely basis for ice forecasting, as well as for a wide variety of scientific and operational 

problems. Similar information is needed on a seasonal or yearly basis for climatological 

studies. Recently, these latter types of observations have received increased emphasis, in 

that the largest worldwide surface temperature change, resulting from CO 2-induced warming, is expected to occur in the polar regions, and changes in the nature and extent of the 

sea-ice cover are believed to be sensitive indicators of these differences. Of particular interest is the response of the ice cover to mechanical and thermal forcing by the air and 

sea. This includes ice motion, deformation, and formation/melt. By knowing more about 

these processes, the climatological and operational properties of the ice cover can be 

predicted with increased accuracy. 

4.5.1.2 Lake and River Ice 

hazards in lake The formation of ice covers on lakes and rivers can result in a variety of hazards by 

and river ice impairing shipping and causing severe flooding. Data required for lake- and river-ice 

4-66
studies are, in many ways, similar to those required for sea-ice studies, in that the ice 

covers on many large lakes and rivers are mobile, at least during part of the freezing 

season, drifting and deforming as the result of wind and current forcing. However, as will 

be discussed later, ice—radar interactions for lake and river ice are quite different than for 

sea ice. 

4.5.1.3 Ice Sheets, Ice Shelves, and Glaciers 

ice-sheet The large ice sheets of the world, located in the Antarctic and in Greenland, contain the 

boundaries great percentage (92%) of the world's fresh water, locked up as ice. In many locations, 

particularly in the Antarctic, these continental ice masses flow into vast ice shelves which 

ultimately calve into the sea large, tabular icebergs with typical thicknesses of 200 to 250 m. 

Although the flow rates of large ice sheets and shelves are small, relative to those of pack 

ice (meters to a few kilometers per year as compared with kilometers per day), nevertheless, the deformation rates are readily measurable using modern techniques. Data of interest 

include locations of the boundaries of these ice masses, measurements of their internal 

movements, location of crevasses, distribution of morainal material, annual accumulation 

and ablation rates, detection of surges, and determination of the structural characteristics 

of the ice. SIR-C, flown in a polar orbit, could provide coverage of both Greenland and 

the Antarctic. 

4.5.1.4 Seasonal Snow Packs 

Roughly 50% of the earth's land surface is covered by snow in any given year. This 

snow cover is highly variable in extent and in properties. Information of particular interest 

includes extent, thickness, density, water equivalent, and average grain size. Snow is of 

interest in its own right. It also serves as an important hydrologic resource, and covers the 

surface of most sea-, lake-, and glacier-ice masses. 

4.5.2 Role of Spaceborne Remote Sensing in Glaciology 

current 

data sources

The need for information on ice and snow has led to the use, with some notable successes, of data from various earth-observing satellite instruments. This use includes applying Landsat data to ice motion studies; applying NOAA Polar-Orbiter data to ice extent 

and motion studies, notably in the Bering Sea; and extensively using a number of microwave systems to obtain data from both polar regions. The Landsat and NOAA systems use 

reflected visible light and emitted infrared (IR) radiation with the consequence that clouds 

in summer and near ice margins, the darkness of polar winter, and the low temperature 

contrast in summer interfere significantly with observations. Landsat also suffers from 

limited coverage. 

Microwave radiometer and radar systems are virtually unaffected by the factors that limit 

visible and IR observations, and the use of those systems has significantly changed ice and 

snow data availability. Radiometer systems that are sensitive to emitted radiation have been 

flying in space since 1973 and have produced global data sets on ice type, concentration, 

and extent, some data on snow cover, and some information on ice sheet accumulation at 

fairly coarse resolution, about 25 km. Future systems may improve this resolution to about 

11 km, but such a reduction would be expensive. For global, large-scale ice and snow in4-67
formation, no existing technology is superior to microwave radiometry. Another coarseresolution system is the scatterometer, a calibrated nonimaging radar that flew on Seasat 

and will fly again on NROSS. This system is valuable in its ability to generate backscatter 

data at different angles of incidence. 

4.5.3 Role of Imaging Radar 

radar's 

independence 

of clouds and 

darkness

The two shortcomings of radiometry for ice observations, its coarse scale and some uncertainty of interpretation, are successfully avoided by the use of imaging radar. The great 

advantage of imaging radar derives not only from its ability to observe through clouds and 

in darkness, but also from its fine surface resolution, 10 to 100 meters, 100 to 1000 times 

finer than the radiometer's. This fine scale permits identification of ice features by texture 

and form, as well as by signal strength, thus vastly reducing interpretive difficulties, and 

also permits the tracking of features to develop velocity fields based on a high density of 

observations. Calibrated systems can also provide improved snow observations, since some 

of the natural spatial variability of snow can be directly observed. 

Seasat 

discoveries 

SIR-C potential

Although there is a significant body of experience concerning the interpretation of 

SLAR and SAR imagery of sea ice, lake ice, and glaciers, obtained by aircraft-borne systems, the SIR-C experiment offers the first opportunity to verify the interpretation of many 

of these features as seen in imagery obtained by a satellite-borne system. This statement 

needs a bit of explaining, since it is common knowledge that the Seasat SAR system obtained excellent images of sea ice along the Beaufort Coast of the Arctic Ocean. The lack 

of verification was the result of several factors, the most important of which was the time 

period when Seasat operated (June 26-October 10, 1978). Because this is a time period 

when surface operations in the Arctic Ocean are both difficult and dangerous, ground-truth 

programs were scheduled for later during the winter and early spring, when operating conditions would be more favorable. These observations, of course, never came to fruition, as 

a result of the power failure on Seasat on October 10. In addition, because of its timing, 

its orbit, and the lack of appropriately spaced receiving stations, Seasat simply did not obtain imagery of most glaciological entities of interest, including the seasonal snow cover. 

This situation has continued until the present, as a result of the inability to launch Shuttle 

missions into polar or near-polar orbits. The only exception to this statement was the 

SIR-B mission, where limited imagery was obtained of the northern edge of the Antarctic 

ice pack. The SIR-C mission, if launched into near-polar orbit, would not suffer from 

these difficulties. In short, there would be extensive coverage of the Arctic Basin, of 

Greenland, of the Alaskan glaciers, and of the Antarctic ice pack, ice sheet, and shelves. 

In addition, if the mission is launched in northern winter, there should be extensive 

ice covers on the Great Lakes and in the Bering, Labrador, and Greenland Seas. In summation, SIR-C offers a unique potential to obtain multifrequency, multipolarization, 

variable-look-angle SAR imagery of the majority of the large ice masses of the world. It 

would also result in validated interpretations of the majority of the features seen on this 

imagery and make possible the selection of the appropriate combinations of frequency, 

polarization, and look angle that will most effectively reveal glaciological features of interest. SIR-C is clearly the logical step that should lead to an optimal utilization of the 

free-flying SAR systems that are planned for deployment in the 1990s on missions such as 

ERS-1 and Radarsat, as well as to the optimal design of the SAR system for EOS. 

4-68
45.4 Scientific Basis for SIR-C Ice Experiments 

ice-scattering The ways that microwaves interact with ice masses can be surprisingly different. This is 

mechanisms the result of changes in the electromagnetic characteristics of the ice and differences in the

surface geometry and roughness of the ice bodies relative to the wavelength of the electromagnetic radiation that is used. For instance, sea ice is not pure ice, in that it contains entrapped sea salt in the form of both included brine and solid salt crystals. The exact 

amount of salt depends on the rate at which the ice grew, its age, and particularly its thermal history. Of particular interest is whether the ice has survived one or more summers, 

in that during the summer melt period much of the salt is flushed out of the upper portions 

of the ice. If the ice contains an appreciable amount of salt (first-year ice), it is a veryhigh-loss dielectric, and the electromagnetic radiation only penetrates, at the most, a few 

millimeters. In this case, the strength of the radar return is strongly influenced by the roughness 

of the upper ice surface. If the surface is flat, as in the case of undeformed first-year ice, 

the return will be low, as most electromagnetic energy is reflected away from the radar 

receiver. If the surface is rough, as in the case of new pressure ridges and most multiyear 

ice, a strong return will occur. This is a somewhat similar situation to the return from an 

ice-free ocean, in that a calm sea gives a low return while a rough sea gives a strong 

return. Fortunately, it is usually possible to distinguish between ice and open water, in that 

the patterns and textures of their returns are commonly different. For instance, as the 

result of Bragg scattering, open water usually gives a strong return at HH and a weaker 

return at VV. As was mentioned, the upper portion of multiyear ice is characteristically of 

low salinity, as the result of brine drainage. Therefore, the electromagnetic energy penetrates into the ice where it undergoes volume scattering; that is, it is scattered by the inhomogeneities (air bubbles, cracks, brine drainage tubes) within the ice mass. Accordingly, 

for a given surface roughness, multiyear ice commonly gives a stronger return than does 

first-year ice. This distinction is of interest because multiyear ice is invariably thicker and 

stronger than first-year ice and is, therefore, a better insulator and a more imposing operational hazard. A schematic drawing indicating the nature of radar returns from sea ice is given 

as Fig. 4-33(a). 

ice dielectric Although sea ice is a high-loss dielectric, lake and river ice are low-loss dielectrics. 

constants This is the result of the fact that lake and river ice are essentially pure ice without the impurities

characteristically found in sea ice. Therefore, radiation penetrates deeply into them, and 

the strength of the return can be a complex function of the roughness of both the upper 

and the lower surfaces of the ice, as well as of the volume scattering within the ice. In 

fact, in shallow lakes, such as occur on the North Slope of Alaska, radar returns clearly 

indicate the portions of these lakes where the ice is frozen completely to the bottom. 

Glaciers, ice sheets, and ice shelves are similar to lake ice, in that the ice masses are 

essentially pure ice. The electromagnetic radiation penetrates well into the ice mass where 

volume scattering occurs, primarily associated with the presence of air bubbles and rock 

and dust layers. 

However, these ice masses are sufficiently thick (hundreds to several thousand meters), 

that at typical radar frequencies there is no return from the bottom of the ice mass (from 

the ice-rock or ice-ocean interface). Therefore, the strength of the return is a function of 

the roughness of the upper ice surface, of the volume scattering within the ice mass, and 

of the geometry of large discontinuities within the ice such as crevasses or major changes 

in ice type. The general nature of the radar return from glaciers and ice sheets, as well as 

from lake ice, is also indicated in Fig. 4-33(b).

4-69
(a) 

I MULTIYEAR: 

LOW-SALINITY, 

LOW-LOSS 

SURFACE + 

VOLUME SCATTERING

FIRST YEAR: OPEN WATER: 

HIGH-SALINITY, HIGH-LOSS HIGH-LOSS 

SURFACE SCATTERING SURFACE 

SCATTERING 

SEA LEVEL

RIDGE

VVF',I LIS 

Fig. 4.33. Interactions between radar and different ice types: (a) sea ice and (b) glaciers, 

ice sheets, and lake ice 

snow-layer 

effects 

value of SIR-C 

multifrequency 

and 

multipolarization 

data

Seasonal snow layers are invariably thin (< 5 m), chemically pure, and of a low density. 

Therefore, they commonly give a very low return and, as a result, are nearly invisible at 

longer wavelengths (e.g., at L-band). However, if the snow is thick or wet or has densifled as the result of freeze-thaw processes and, particularly if the included air bubbles are 

of the appropriate size to serve as effective volume scatterers, moderate returns can result. 

Also, the upper surface of the snow can change from very rough (sastrugi and irregular 

ablation features) to perfectly smooth in the matter of a few hours. Therefore, the radar 

return from snow is sometimes strong and sometimes very weak. One result of the SIR-C 

experiment should be a better understanding of these variations in radar return and their 

associated causes. 

Mention should be made here of the unique opportunities offered by the fact that the 

SIR-C mission will provide both multipolarization and multifrequency data. Multipolarization 

data gives valuable clues relating to the scattering mechanisms, and insight into separating 

surface scattering from volume scattering. In the case of surface scattering, there are two 

well-established mechanisms: geometric optics and resonant, or Bragg, scattering. In the 

case of the radar return from sea ice and glacial ice, experimental data indicate that geometric optics dominate for viewing angles less than 30 0

to nadir and that Bragg scatter4-70
SAR phase 

images

ing will be expected from the SIR-C radar if all the return is from the surface. Surface 

scattering cannot be uniquely determined without comparing polarization data. In sea ice, 

the absence of volume scattering implies the limited penetration of electromagnetic waves 

and hence the presence of younger, more saline ice types or wet multiyear ice. 

A lack of polarization dependence at large viewing angles implies negligible surface 

scattering. In these cases the electromagnetic waves penetrate the ice and interact with subsurface scatterers. Moderate volume scattering is commonly associated with multiyear sea 

ice, and very strong subsurface scattering is known to occur over the ice-covered regions 

of Southern Greenland. In these cases, a strong HV return is to be expected, as volume 

scattering is invariably strongly depolarized. 

Recently, SAR phase images have been produced using two polarization components. 

Again, this is another way to use polarization data to separate surface and volume scattering in that, for reasons that are just now becoming understood, volume scattering produces 

a near 00 relative phase shift while surface scattering can produce a 180° phase shift. 

A prime application of multifrequency data is to determine the relative size of the volume scatterers. For instance, recent airborne active and passive microwave data collected 

over Greenland indicate that the subsurface scatterers are large compared with the electromagnetic wavelength (C- through K-band). If this can be verified, electromagnetic theory 

indicates that the average radius of curvature of these objects can be determined. Observations at different azimuth angles will also reveal shape asymmetries and whether there is a 

preferred orientation in the alignment of the scattering objects. If the subsurface scatterers 

are small compared to a wavelength, Rayleigh scattering occurs and the absolute return 

varies as the wavelength to the fourth power. As this type of scattering is observed from 

sea ice, information could possibly be obtained regarding whether or not the size of the 

scatterers varies geographically over the Arctic. 

4.5.5 SIR-C Glaciology Experiments 

Some specific SIR-C experiments in the general area of glaciology are considered in the 

following section and are summarized in Table 4-5. 

Table 4-5. Some SIR-C glaciology experiment classes

Experiment Class Scientific Objectives 

Sea ice Sea-ice feature verification, ice drift and deformation, spatial 

variations in pack ice, nature of ice margin eddies, improved 

characterization of sea-ice type 

Lake ice Lake-ice feature verification, lake- and river-ice operations, 

lake-ice dynamics 

Ice shelves, ice sheets, and Ice-shelf and glacier boundaries, icebergs and ice islands, icealpine glaciers stream delineation, alpine glaciers 

Snow Snowpack extent, snow-water equivalent, snow wetness

4-71 
4.5.5.1 Sea Ice 

sea-ice This program, which should be carried out during a polar orbiting SIR-C mission at least 

imaging at two locations in the Arctic, say the Beaufort and the Greenland Seas, would be dependent 

mechanisms upon rapid transmission of the data to ground-truth parties that have flexible logistics support. They would then have the possibility of visiting locations where unusual or interesting radar signatures are observed. For instance, the bright cigar-shaped return in Fig. 4-34 

is believed to be an ice-island fragment within the ice pack, based on the fact that parts of 

the known ice island T-3 (see Fig. 4-35) gave a similar strong return. Whether this supposition is correct is unknown, as is the exact reason for the strong return in the first 

place. Similar uncertainties exist in interpreting the return patterns from the fast ice areas 

shown in Fig. 4-36. Simple on-site inspection and sampling should remove such interpretative uncertainties and advance our understanding of the scattering mechanisms encountered in these ice masses. The fact that SIR-C will provide multifrequency data with 

different polarizations and angles of incidence will significantly contribute to resolving 

these problems. An additional portion of a verification program would be the under-flying 

of selected SAR passes with high-resolution aircraft-borne SAR such as either the ERIM 

or the Intera systems, and aerial photography. Utilization of data obtained by other satellite 

systems such as the SSM/I system should also be very useful. These flights would provide 

instructive comparisons between SAR systems with different resolutions and also with 

high-resolution visual imagery. Their use would also permit the field parties to obtain the 

down-linked aircraft data in near real time so that in situ sampling can be carried out 

before ice drift and deformation modify the ice beyond recognition. 

ice-drift and Analysis of the Seasat imagery has revealed numerous eddies and complex deformation 

deformation patterns within the pack ice. The SIR-C imagery should expand this data set, thereby proexperiments viding modelers with an improved understanding of scales in sea-ice deformation, as well 

as providing valuable experience in the application of image-analysis procedures to general 

ice-dynamics studies. Our only reservation here is that an 8-day mission may not prove to 

be long enough to observe a complete deformation cycle or the growth and decay of an 

eddy. 

spatial It is known that structural characteristics of the pack ice, such as floe sizes, ridging 

variations patterns, and lead geometry, vary with season. It is also presumed that they vary spatially 

in pack ice at a given time, although little information is available on the subject. In that the SIR-C 

SAR system, flown in a polar orbit, would provide a reasonable sample of both the Arctic 

and the Antarctic ice packs, a detailed examination of the imagery should finally allow 

definitive comparisons to be made of the "tectonic style" of regions such as the Beaufort 

Gyre as contrasted with the Trans-Polar Drift Stream (in the Arctic) and the Weddell and 

Bellingshausen Seas, near the Antarctic Peninsula, as contrasted with other Antarctic seas 

not influenced by a blocking landmass. 

ice-margin Summer studies of the edge of the ice pack in the Greenland Sea, made during MIZEX, 

eddies have revealed the presence of well-defined eddies near the ice edge that are clearly delineated in airborne SAR imagery. These eddies have also been observed by Seasat in the 

Beaufort Sea (Fig. 4-37). In that large wavelike patterns appear to be present in the 

passive microwave images of both Arctic and Antarctic ice edges during the winter, 

similar and perhaps even more striking eddy generation may well occur during the winter. 

SIR-C, flown in a polar orbit, would provide up to an 8-day sample of the numbers and

4-72 
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Fig. 4.34. Seasat SAR image of pack ice in the Beaufort Sea. The bright cigar-shaped object above the center 

of the image (arrow) is believed to be an ice-island fragment 

sizes of the eddies that occur along the Arctic and the Antarctic ice margins. Admittedly, 

it will not provide the time series that is desired, but it will, nevertheless, result in a 

major improvement in our data base on this poorly understood phenomenon. Other possible experiments near the ice edge could investigate the interactions between waves and ice 

characteristics. 

optimum 

radar 

parameters

Sea-ice radar parameters have been only partially explored up to this time. While it is 

known that nearly any image of the ice pack can be used with feature location and tracking for ice-velocity determination, the use of radar images to better classify ice types re4-73
ORIGINAL PAGE IS 

OF POOR QUALITY 

4 km 

Fig. 4-35. Seasat SAR image of the ice island 1-3 

quires further study. The physical basis for examining backscatter-signal dependence on 

wavelength, polarization, and angle of incidence comes from the fact that many of the key 

differences in ice types are expressed in the geometry and chemical structure of the upper 

surface. The key differences are the density, salinity, roughness, crystal structure, and 

snowcover of the upper half-meter. These properties significantly affect the backscattered 

radiation. Since they also affect the penetration depth and the multiple scattering statistics, 

they should appear in the wavelength dependence and in the cross-polarization strength. A 

general impression of the variations in the return from sea-ice fields with changes in frequency and polarization can be obtained by examining Figs. 4-38 and 4-39. The breakdown of the ice cover by types, especially in the Arctic Ocean, is scientifically a very 

significant issue in that it relates to basic questions of how much ice there is and how it is 

formed and melted. Space-based passive microwave techniques have to date not proved 

able to develop this information to be the degree of accuracy desired. Imaging radar with 

its fine resolution and strong ice-type sensitivity is a logical candidate for the job. It now 

4-74
OCT 5. 1978 

REV 1438

OCT 8, 1978 

REV 1481

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Strait, Canadian Arctic Islands. Note the numerous features identifiable on generally low-return (undeformed) fast ice. 

.

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ARCTIC OCEAN

170•N 

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Fig. 4.37. Seasat SAR images that reveal an eddy in the ice near the ice edge in the Beaufort Sea

4-75
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MULTIYEAR NILAS MULTIYEAR GRAY-WHITE NILAS 

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Fig. 4.38. XJLband comparison of pack ice (data courtesy of Lawrence Gray, Canada Centre for Remote Sensing). 

X-band is at the top and L-band at the bottom.

ORIGINAL PAGE Is 

OF POOR QUALITY 

4-76
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81 

00 

450 

570 

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Fig. 4.39. Variations in SAR imagery of sea ice, with changes in polarization (data courtesy of Lawrence Gray, Canada 

Centre for Remote Sensing) 

appears that frequency, angle of incidence, and polarization dependence may be key pieces 

of information in resolving not only this problem but also the problem of unequivocally 

distinguishing between thin ice and open water under all conditions and during all times of 

the year. SIR-C will be a most useful tool in this regard.

4-77
4.5.5.2 Lake Ice 

lake-ice The problem of providing high-quality ground-truth for the interpretation of SAR 

feature imagery from lake ice is, in a way, similar to that of providing ground-truth for sea ice. 

verification However, it is more difficult, in that in sea ice the roughness of the ice-water interface 

does not contribute to the strength of the return as it does in lake ice. Therefore, to adequately characterize lake ice for radar interpretation, a detailed specification of both the 

upper and lower ice surfaces is required, as well as information on the distribution of internal scatterers within the ice. If such observations are coupled with photographic underflights associated with SIR-C overpasses and an ice-coring program to examine internal 

scatterers, a major advance in the understanding of the radar returns from lake ice should 

result. 

arctic Detailed studies of radar returns from shallow lakes along the Arctic coastal plain have 

coastal-plain shown that the strength of the return correlates with whether the ice is frozen to the lake 

lake bed (weak return) or is free-floating (strong return). Inasmuch as lake-ice thicknesses on 

bathymetry the North Slope are reasonably constant, changing slowly with latitude, a few lake-ice 

thickness measurements coupled with SIR-C SAR imagery could provide bathymetric information on the innumerable shallow lakes on the coastal plain, in that the location of the 

strong-return/weak-return boundary corresponds to a water depth equal to the ice thickness. Also, if the imagery could be obtained at the time of maximum ice thickness, it 

would be possible to identify lakes that are suitable as year-round water supply sites. 

lake- and As is well known, lake and river ice development in constricted areas is the cause of a 

river-ice wide variety of problems associated with an extended winter navigation season on the 

operations St. Lawrence Seaway-Great Lakes and on the Ohio and Mississippi River systems. In the 

past, on Lake Erie, ice reconnaissance with SLAR systems proved to be extremely helpful 

in dealing with a variety of such operational problems. SIR-C will provide an opportunity 

to compare ice charts prepared from a satellite-borne system with those resulting from the 

analysis of aircraft imagery. Depending on the exact timing of the Shuttle mission, it may 

also be possible to couple ice conditions as seen by radar from space to ice conditions as 

seen from the bridge of a freighter transiting the lakes. 

SAR and On many large lakes, there is an ice pack that drifts and deforms under the influence of 

lake-ice winds and currents for at least a portion of the freezing season. Although the general 

dynamics physical processes are similar to those occurring in sea ice, the "constants" associated 

with the different processes are commonly quite different. The SIR-C imagery could provide a detailed data set on ice drift and deformation against which a variety of scattering 

model calculations could be compared and techniques for studying ice dynamics tested.

4.5.5.3 Ice Shelves, Ice Sheets, and Alpine Glaciers 

ice-shelf and Although it is commonly believed that the location of the borders of such slowly varying 

glacier entities as ice shelves and glaciers is well known, this is not necessarily the case. For inboundaries stance, in the Antarctic much of the coast is composed either of ice shelves or of nongrounded glacier termini that discharge directly into the sea. In the past, a number of instances of large ice masses (on the order of 50 to 100 km in diameter) calving into the sea 

have been reported. The exact times of these calvings are commonly not known (more that 

within a several year interval). The same lack of knowledge applies to the drift tracks of 

the icebergs once they leave their region of birth. In that SIR-C, flown in a polar orbit, 

4-78 
would provide multiple passes over the margins of the Antarctic continent, the resulting 

imagery would provide a valuable delineation of the boundaries of the ice shelves as well 

as the numerous glacier termini that border directly upon the ocean. This "map" can then 

be compared with similar spotty observations acquired during the past decade by Landsat in 

order to assess changes in the ice boundaries with time. 

A related problem in the Northern Hemisphere is the calving of tabular icebergs (the 

so-called ice islands) from a relict ice shelf located along the north coast of Ellesmere 

Island, the northernmost island in the Canadian Archipelago. The SIR-C data set should, at 

the least, provide an up-to-date map of the edge of this shelf. 

icebergs and As has been well known since the sinking of the Titanic, even small icebergs can pose a 

ice islands major hazard to the largest ships. This problem will become particularly pressing if the 

marine routes that have been proposed for transporting oil and gas from the Arctic are developed. Similar concerns apply to ice islands drifting hidden in the pack ice of the Arctic 

Seas, in that they pose a failure threat to production drilling structures that will soon be in 

place on the margins of the Arctic Ocean. Icebergs and ice islands are also of interest in 

their own right, in that their drift tracks provide us with information on the currents and 

winds in regions such as the Southern Ocean, where such information is generally lacking. 

The SIR-C data set, from a polar orbiting mission, would allow the first census of the 

numbers, locations, sizes, and shapes of ice islands in the Arctic Ocean and of glacier and 

shelf icebergs off the Antarctic continent. The former data set can be used to make 

reasonable estimates of encounter probabilities with offshore structures. In addition, the 

iceberg estimates in the North Atlantic, based on SAR, can be compared with similar 

estimates developed by the International Ice Patrol, using aircraft. This should be very informative in improving our understanding of the iceberg sizes and shapes (if any) that 

SIR-C may not see. Also, as icebergs commonly project well above the surrounding waves 

and sea ice, the application of shadow identification procedures and stereo-SAR should be 

explored. In that icebergs and ice islands are fresh ice, the radar backscatter properties are 

very different from sea ice. Canadian aircraft radar data indicate that L-band data may 

penetrate icebergs and scatter from the ice-water interface, thereby producing a bright 

return slightly displaced on the image. The C-band data do not show this. Available data 

also indicate that iceberg detection is strongly dependent on angle of incidence. Simultaneous data at different frequencies, polarizations, and angles of incidence will clearly be 

very helpful in studying this problem. 

The use of SAR imagery in the investigation of the behavior of large ice shelves and ice 

sheets has been inadequately explored. The SIR-C imagery should be examined very carefully in this regard. Fortunately, because large ice sheets and shelves change slowly, most 

ground-truth observations could be made as long as a few months after the SIR-C mission. 

ice-stream One possible observation of interest is the delineation of ice streams within the Ross Ice 

delineation Shelf. Recently, it has been discovered that the Ross Ice Shelf (an Antarctic ice feature approximately the size of Texas) contains streams of rapidly moving ice within a more 

slowly deforming ice matrix. As these ice streams contain many large crevasses, it may 

prove possible to map them accurately with SAR imagery. The possibility of using movements of crevasse patterns to estimate surface flow velocities should also be explored, as 

should the use of both active and passive radar transponders placed on the ice surface as 

reference points to measure surface velocities. Such techniques could prove extremely attractive, in that the transponders would presumably still function after burial beneath the 

snow. Again the wavelength and polarization dependence of the scattering is expected to 

be strong in that the scattering occurs off the ice grains within the ice mass.

4-79
alpine 

glaciers

In 1978, Seasat collected data on many glaciated regions around the world. Particularly 

good coverage was obtained of the glaciers in the Alaskan Range (see Fig. 4-40). In addition, SIR-A observed a number of low-latitude glaciers in 1981. SIR-C now offers the 

possibility of examining the changes in ice extent, in crevasse patterns, in the distribution of 

morainal material, and in ice-surface roughness that have occurred over a 10-year (Seasat) 

and an 8-year (SIR-A) period. Also, as the backscattering mechanisms in alpine glaciers 

are still not well understood, an interesting experiment could be developed taking advantage of the multiple frequencies, multiple look angles, and variable polarization afforded 

by the SIR-C system. A reasonable approach to this problem would be to select a limited 

number of "accessible" glaciers, for which Seasat or SIR-A imagery is available, and develop an appropriate ground-truth program that would be based in part on the examination 

of this existing data set. 

4.5.5.4 Snow 

seasonal 

observations 

of snowpack

The possible timing of the SIR-C launch during midwinter in the Northern Hemisphere 

offers the opportunity at C-band and X-band for useful observations of the seasonal snow 

pack, as discussed earlier in Section 4.3.5.4. Based on a knowledge of the snowpack distribution during the SIR-C mission, the exact times of overflights, and the meteorological 

conditions in different areas, a snow-sampling program could be marshalled to provide a 

ground-truth base of direct snow observations tied in both time and space to the SIR-C 

data. Also useful would be comparative studies of snow properties as estimated from the 

passive microwave imagery that will be obtained by the Scanning Multichannel Microwave 

Radiometer (SMMR) system on Nimbus-7 and the Special Sensor Microwave Imager 

(SSM/I) system on the Defense Meterology Satellite Program (DMSP) satellite. 

The SIR-C mission can provide the necessary understanding and data base required to 

extract the maximum amount of geophysical information on the snow and ice masses in the 

Northern Hemisphere from the several radar satellites that are planned for launch in the 

early 1990's. Its role may prove to be even more important in the Antarctic, in that, when 

flown in a polar orbit, it will provide the only multiparameter SAR data on this vast area 

until either proper receiving stations are installed in the region or improvements are made 

in SAR data storage and transmission capabilities, so that data obtained from the Antarctic 

can be retrieved with a line-of-sight communication link. 

4.5.6 Summary of SIR-C Mission Requirements for Ice 

need for 

well-planned 

field 

observations

To obtain the maximum utility from the SIR-C data for glaciology research, it will be 

necessary to couple it with a well-thought-out series of in-situ field observations. Historically such observational programs have been carried out by a multinational group of investigators supported by a variety of agencies in a manner somewhat similar to the supersites 

envisioned in this report. The same situation will undoubtedly hold during the SIR-C mission. Although it is impossible to exactly specify supersite locations at the present, possibilities for the polar-orbiting-mission include the Beaufort Sea north of Deadhorse or 

Barter Island, the Greenland Sea during the time of the WINTER-MIZEX, a U.S.-

Canadian site in North Baffin, and the Weddell Sea during a cruise of the Polar Stern or a 

U.S. ice breaker. Whatever sites are selected, it is essential to have good logistic support 

to allow investigators to get to ice features of interest. It is also necessary to have the 

capability of getting SAR imagery to the investigators in the field in near real time so they 

can use the imagery to identify features of interest. If it proves impossible to provide the 

4-80
0001AL r 

J QUALITY 

ps.. 

' .... 

40

0 30 km 

RADAR 14 N 

ILLUMINATION 

0 5 k 0 5 k 0 5 k 

MULDROW AND MULDROW ELDRI DGE 

TRALEIKA GLACIERS GLACIER GLACIER 

Fig. 4•40. Seasat SAR image of the Alaska Range, Alaska

4-81
field teams with SIR-C SAR within 2 days or less of the satellite pass, it will be necessary 

to carry out satellite under-flights with an aircraft-borne SAR system. If this proves to be 

necessary, it will be desirable to also obtain passive microwave and scatterometer measurements as well as high-resolution photography. Field measurements on the large continental 

ice sheets are not so logistically demanding, as these entities change very slowly. 

Therefore, field sites could possibly be visited several months after the satellite mission. 

4.5.6.1 Orbital Parameters 

need for Many glaciological studies of both sea ice and ice sheets require an orbit inclination 

near-polar between 78° and 102° (inclinations in the high 80s would allow observations of the fastorbit moving ice streams in the Ross Ice Shelf) and will therefore require flying SIR-C in a 

polar orbit. However, many of the studies described here could be undertaken using SIR-C 

data from a 57° inclination orbit. A nearly frozen orbit allowing variable incidence angles 

over the same sites would be useful. The specific inclination will influence the location of 

the supersites, since it would be desirable to have sea-ice motions generally parallel to the 

satellite ground track to maximize the length of time that a given floe could be tracked. 

4.5.6.2 Mission Timing 

need for Two SIR-C flights, six months apart, are optimum. The optimum periods are late 

two flights February through April (Arctic winter) for the first flight and early July through midOctober (melt season through freeze-up) for the second flight. The ideal times during these 

periods would be late March through April for the first flight (February through early 

March is dark, very cold, and generally operationally difficult) and either August (maximum melting) or the first two weeks of October (freeze-up) for the second. The exact 

time of day is not important. 

4.5.6.3 Swaths and Resolutions 

Since SIR-C is both a research and a mapping mission, there is, for glaciological 

research, a preference for high resolution even at the expense of swath width. 

4.5.6.4. Frequencies, Polarizations, and Incidence Angles 

need for L-band and C-band (and, if available X-band) data will be very useful in improving our 

at least 5 bits understanding of the nature of the varied scattering processes occurring within snow and 

ice covers. Useful polarizations include HH, VV, and cross-polarization, plus a measurement of the phase difference between the HH and VV channels. We also require the 

highest bandwidth that is feasible and at least 3 and preferably 4 channels of data to obtain 

the simultaneous use of frequency and polarization information. Five or preferably more 

bits of data are required to obtain dynamic range commensurate with the range of scatterers in the scenes. The use of Block Floating Point Quantization appears to be permissible. In general, the radar parameters suggested for SIR-C appear to be adequate for useful 

glaciological studies. 

4-82
4.5.6.5 Data Products 

need for 

relative 

calibration 

of 1 dB

The desired quality of the data obtained is determined by the range of backscatter observed 

on natural ice features of interest. As the range of backscatter from many ice features is 

within 10 dB, a relative calibration to within 1 dB would be necessary. The images should 

be geometrically corrected to map-correct format. Absolute data registration at sites far 

from distinguishing coastal features should be accurate to within 1 km for studies of ice 

dynamics, and relative registration to within 100 in would be useful. In coastal zones 

where distinguishing features are available in the imagery, registration should be at the 

resolution scale. It would be very desirable to have an automatic positioning system onboard the Shuttle to aid in these problems. 

4.6 Oceanography 

4.6.1 Background 

hostile The region near the ocean surface represents one of the most hostile environments on 

observational earth for scientific measurements. Yet it is through the ocean surface that fluxes of 

environment momentum, heat, and moisture flow between ocean and atmosphere. Systems to measure 

the surface signatures of these important interactions, as well as signatures of processes 

occurring beneath the surface, can provide vital information needed for the construction 

and testing of ocean and air-sea interaction models. 

The geophysical phenomena of interest, however, span a wide range of spatial and temporal scales, and require frequent, high-resolution measurements covering large geographic 

areas for long periods of time. Such data can be acquired only from satellite-mounted 

instruments. 

Potential applications of spaceborne SAR to oceanography and meteorology have now 

been amply demonstrated with both the Seasat and SIR-13 data sets [2-3. 4-6]. Among the 

many potential oceanographic applications, SAR appears to hold great promise in the following areas. 

4.6.1.1 Ocean-Wave Forecasting 

inadequacy of Present wind-wave forecast models are generally inadequate for reliably predicting the 

wind-wave surface-wave directional energy spectrum. Major questions exist both in properly specifyforecast models ing the input wind fields and in the associated growth and wave-wave interaction physics. 

Present theories are based primarily on directionally integrated spectral measurements. 

There have been few opportunities to verify and refine models with reliable measurements 

of directional wave spectra. Consequently, many forecast models are in gross disagreement, especially in cases of turning or growing winds, which are of the highest interest.

4-83
4.6.1.2 Internal Wave Physics 

internal wave 

refraction at 

current 

boundaries 

undetected 

mesoscale 

eddies

Although internal wave packets are fairly ubiquitous in SAR imagery along continental 

shelves, they are also occasionally observed in the deep ocean, presumably associated with 

bathymetric features, such as sea-mount chains. Internal wave patterns provide a natural 

test-bed with which to refine and extend SAR imaging theories. Moreover, internal waves, 

by virtue of their refraction at current boundaries, can provide a vehicle for the delineation 

of mesoscale- and submesoscale-current features. Our understanding of SAR internal wave 

imaging is likely to foster algorithm development in other geophysical problem areas. 

4.6.1.3 Currents, Fronts, and Eddies 

One of the major unsolved problems of oceanography is that of large-scale heat and 

mass transport. Such large-scale transport profoundly influences life on the earth and 

greatly ameliorates the polar-temperature extremes by carrying heat from the equator 

toward the poles. It is now widely recognized that the mesoscale variability can have 

energy levels one or more orders of magnitude greater than the mean flow. Vast regions 

of the ocean apparently are filled with mesoscale eddies, most as yet undetected and uncharted. 

understanding 

the behavior 

of short 

gravity waves

4.6.1.4 Bottom Signatures 

Although Seasat was able to sense bottom signatures in a few cases, the environmental 

conditions for optimum surface modulation from these features is not yet understood. If 

reliable mapping of bottom features is possible, an inventory of sometimes rapidly changing shoals would be possible on a global basis. 

4.6.1.5 Spatial Variability of the Wind Field 

Conventional measurements of the surface wind field are limited to single-point temporal 

records, which are extremely sparse for most of the ocean. The instantaneous spatial variability of the wind field might be a key ingredient to further refinement of wind-wave 

generation models, which usually assume spatially homogeneous wind fields. 

4.6.2 Role of Spaceborne Remote Sensing in Oceanography 

Previous spaceborne SARs have revealed a large variety of atmospheric and oceanic 

phenomena on all spatial scales from 25 in to 100 km. However, because SAR is sensitive 

primarily to the structure of the short gravity waves on the ocean surface, the extraction of 

quantitative geophysical information from oceanic SAR data is critically dependent upon 

understanding the behavior of the short waves—in particular, their generation and modulation by winds, long waves, and currents, and their interactions with microwave electromagnetic radiation. The relative importance of the various scattering mechanisms, and 

4-84
how they act to produce or distort the final SAR image, will be one of the central futureresearch questions addressable using SIR-C data. Simultaneous in-situ measurements of 

short waves, long waves, winds, and currents will provide a basis for constructing and 

refining models relating short-wave characteristics to the larger-scale geophysical quantities 

of interest. 

Over the past two decades, a number of spaceborne remote sensors have demonstrated 

their unique value for oceanography. The early Tiros and later Nimbus visible and infrared 

imagery has become a vital ingredient in routine weather forecasting. The geosynchronous 

GOES imagery provides temporal sequences of cloud cover on a global scale. Similar multispectral sensors, such as the Coastal Zone Color Scanner, have provided remarkable 

delineation of coastal fronts and eddies. In the last decade, the Seasat complement of active and passive sensors has been expanding our knowledge of global wind fields, 

mesoscale circulation dynamics, and the spatial evolution of wave spectra. In the coming 

decade, many of these prototype sensors will evolve into operational complements on missions such as NROSS, TOPEX, and ERS-l. It is clear that remote sensing will play an increasingly vital role in global-scale ocean problems, particularly in establishing surface 

boundary conditions with which to initialize, refine, and update global predictive models of 

wind, wave, and current fields. 

4.6.3 Role of Imaging Radar in Oceanography 

advantages 

of SAR

The microwave imaging radar is the only instrument with the capability to acquire allweather measurements of ocean-surface conditions and to provide the high-resolution and 

wide-spatial coverage necessary for addressing the geophysical problems listed in Section 

4.6. 1. Because SAR is primarily sensitive to the structure of the short gravity waves on 

the ocean surface, the extraction of quantitative information is critically dependent upon 

our understanding short-wave behavior, in particular how short waves are generated and 

modulated by winds, long waves, and currents. If the short waves are either deterministically or statistically describable, there is a good likelihood that quantitative physical ocean 

parameters will ultimately emerge from SAR imagery. The scattering-mechanisms giving 

rise to ocean SAR images are similar to those used by scatterometers and altimeters to determine near-surface winds. Thus, increased knowledge of electromagnetic/short-wave interactions that is obtained from imaging radars with frequency and polarization diversity is 

directly usable for refining and optimizing other types of active microwave oceanobserving instruments. 

4.6.4 Scientific Basis for SIR-C Ocean Experiments 

coherent 

modulation of 

short waves by 

longer waves

A variety of SAR ocean-imaging theories have been advanced over the last decade, with 

each distinguished mainly by its assumptions regarding the spatial distribution and detailed 

motion of the scatterers. Most theoretical work assumes a two-scale scattering model, 

where the Bragg resonant short waves are simply tilted and strained by the longer waves, 

producing a short-wave spatial modulation which is coherently linked to the longer waves. 

However, the real ocean is a complicated ensemble of scatterers, some moving randomly, 

and others coherently linked to a variety of larger-scale phenomena, e.g., surface winds, 

waves, and currents. Moreover, scattering originates not only from Bragg resonance with 

the transmitted radiation, but also from specular reflection and wedge diffraction mechanisms. Although Bragg resonance may be dominant at angles well off nadir, specular scattering can be important at these large angles of incidence, especially for broad surface 

slope distributions such as are associated with high sea states or localized wave breaking.

4-85
A cogent theory for SAR imaging of the ocean is not yet available. Ocean imaging is 

complicated by the sometimes significant motion of the scatterers during the SAR integration time. Because it is dependent upon an accurate measurement of target radial velocity 

to determine azimuth position, the SAR will interpret any scatterer radial motion as a 

change in position. For example, a scatterer with radial velocity V. will produce an 

azimuth displacement

Xa = (R/V) Vr 

advantage of 

lower altitudes 

for SAR imaging 

of ocean

where R/V is the range-to-velocity ratio of the platform. For Seasat, R/V 2Z 130 s; for 

both SIR-B and SIR-C, RIV 35 s at the Seasat angle of incidence of 200. Consequently, 

ocean motion effects in the Shuttle SARs should be nearly four times less severe than they 

were in Seasat, for the same angle of incidence. This improvement may be critically important in some ocean applications, particularly in the imaging of long gravity waves. 

Advances in SAR ocean-Imaging theory will emerge only from well-conceived and wellexecuted experiments. In general, such experiments will involve techniques for directly 

measuring or indirectly inferring the relevant scatterer velocity distribution in the presence 

of various oceanographic phenomena of interest. The experiments should, of course, be 

conducted coincidentally with the SIR-C overflights, and over a wide range of environmental conditions. 

Because of the lack of well-controlled supporting experiments, Seasat SAR ocean data 

are largely descriptive in nature. SIR-A, with its high off-nadir angle of incidence, was not 

optimized for most ocean applications. However, SIR-B had much more flexibility. In 

spite of the reduced scope of the SIR-B mission, a number of significant ocean experiments were conducted in several regions of the world. The SIR-B experiments are still in 

an early stage of analysis, but it is already clear that the variable angle of incidence and 

the high-quality digital data will begin to resolve some of the longstanding issues in SAR 

oceanography. SIR-C and later SIR-D, with their ability to provide multifrequency and 

multipolarization data, will represent additional major steps toward the optimal definition 

of future SAR oceanographic missions. 

4.6.5 SIR-C Ocean Experiments 

Several broad categories of SIR-C ocean experiments are suggested in the following and 

are summarized in Table 4-6. However, this list is merely suggestive of what is possible 

and is not meant to be all-inclusive. 

4.6.5.1 Ocean-Wave Forecasting 

SAR can provide 

global wave 

directional 

spectra

The collection of global wave spectra is one of several rationales for flying an orbital 

SAR. By themselves, these spectra would be of little value, but as a supplement and 

periodic update to a global wind-wave forecast model, the impact of actual measurements 

of directional spectra could be revolutionary. For example, present wave-generation 

models in operation around the world are in gross disagreement with respect to the directional properties of waves generated from even the simplest wind fields. The behavior of 

ocean waves in the presence of turning and sometimes adverse wind fields, e.g., the active 

region of a hurricane, has been a particularly difficult problem, with few directional spec4-86
Table 4-6. Some SIR-C oceanography experiment classes 

Experiment class Scientific objective 

Ocean-wave forecasting Directional wave energy spectra, supplement to global wind-wave 

forecast models 

Internal waves Understanding wave-current interactions 

Currents, fronts, and eddies Detection of current-system boundaries, oceanic fronts, and 

mesoscale eddies; extraction of surface currents directly from 

Doppler spectrum 

Bottom signatures Relationship of ocean-bottom features to surface expressions, direct 

detection of surface gravity wave field, studies of nonlinear interactions between subsurface currents, surface gravity waves, 

and Bragg waves 

Wind signatures Correlation of surface-wind magnitudes to absolute backscatter 

tra measurements available. There are no good data on the large-scale directional evolution 

of wind-driven waves, and therefore no valid criteria for the acceptance or rejection of 

particular wind—wave generation models. 

In addition to its purely scientific value, timely knowledge of the directional wave spectrum is of practical importance to operational wave forecasting and ship routing. Over the 

long term, such measurements will be useful in both local and global wave climatology, 

with practical applications in offshore tower design and coastal erosion research. Moreover, there is some evidence that crude estimates of simultaneous directional wave spectra 

may be necessary to further refine scatterorneter model function algorithms. 

production of Long surface waves are visible because they produce an apparent periodic spatial moduperiodic lation of the local wind-generated 30-cm waves. The modulation may be much less than 

modulation of the noise on the scale of a single 25-rn-resolution element, but the spatial spectrum of the 

local wind- wave field is generally well-behaved and homogeneous over tens and even hundreds of 

generated kilometers. Extensive averaging over both wavenurnber and space, therefore, can reduce a 

short waves very noisy background by as much as a factor of 30, revealing extremely subtle modulaby long waves tions of only a few percent. For example, Fig. 4-41 shows the spatial evolution of the 

dominant wavenumber of a swell system over a 900-km pass. The significant wave height 

of the swell system was under 1 m. With appropriate filtering, the spatial evolution of the 

dominant-vector wavenumber can be tracked with mean residuals of only a few percent. 

This particular spatially evolving swell system clearly shows deep-water dispersion, refraction in the Gulf Stream, and shallow-water wavelength shortening. Moreover, subtle perturbations of the wavenumber in shallow water reveal the presence of subsurface sea 

mounts and depressions. The spatial evolution of the wavenumber can be used to accurately locate the origin of wave-generation sources. 

decreased A number of significant advances in our understanding of SAR ocean-wave imaging are 

sensitivity necessary prior to defining an operational system. For example, it is well-established that 

in azimuth the Seasat SAR lacked response in the azimuth (along-track) direction, especially during 

direction high sea states. Figure 4-42, showing a Seasat SAR directional wave spectrum during a 

particularly high sea state (H - 4.4 m), vividly illustrates the azimuth falloff problem. 

The explanation for this falloff is presently in dispute. For example, most models predict 

improvement in azimuth response at lower range-to-velocity (RI V) ratios. The relative im4-87 
- 3) 

-r pr

(a)

0.05

300 km 

a 

- 0.04 

z u-i 

>

0.03 ' DEEP WATER L 

DISPERSION SHALLOWWATER 

GULF STREAM REFRACTION 

SMOOTHING KERNEL: 40 km 

0.02 I I I I I 

U zo 40 

(b)

NJ 80 100 120 140 

FRAME NUMBER 

E

0.050 

Z 0.035 

0.030 

0.025

DISTANCE FROM SHORELINE, km 

250 200 150 100 50 

GULF 

- STREAM

'CONTINENTAL 

SHELFELF

- 

-

SHELF EDGE DEEP-WATER DISPERSION

(EXTRAPOLATED) 

I I I

0 

50 

100

E 

I 150 

u-i 

200 

250 

300 

100 110 120 130 140

SAR FRAME NUMBER 

Fig. 4-41. Spatial evolution of a SAR-measured wavenumber over a 900-km 

Seasat pass: (a) the entire 900-km pass; (b) the northernmost 300 km 

portance of instrument integration time, however, and the explicit dependence of the 

problem on local sea state remain controversial for lack of good experimental data. 

Moreover, there is no consensus yet on whether, and under what conditions, an estimate 

of wave energy can be extracted from SAR wave spectra. SIR-C, with its variable RI V 

(via angle of incidence) and multiple frequencies (therefore permitting variable integration 

time for comparable resolution), represents a valuable opportunity for designing experiments to distinguish among the various imaging models, and to establish the degree of 

uniqueness between the SAR-measured directional spectrum and the actual ocean directional spectrum. 

4-88
PRIMARY 

SECONDARY 

TERTIARY 

AZIMUTH 

FALLOFF

LOCAL 

WIND 

DIRECTION 

ORIGINAL PAGE 

WAVE SYSTEMS

COLOR PHOTOGRAPH 

Fig. 4.42. Seasat azimuth wavenumber falloff in a high sea state; outer circle corresponds to a 50-rn wavelength 

4.6.5.2 Internal Waves 

Numerous SAR images of surface features associated with oceanic internal waves have 

been obtained from Seasat, SIR-A, SIR-B, and aircraft surveys. Figure 4-43 shows tidally 

generated internal waves in the New York Bight, observed during the SIR-B mission. 

The linear features in the image are due to small-scale roughness changes induced by the 

internal-wave surface currents. 

Dual-frequency (L- and X-band) observations of internal waves with an aircraft SAR 

exhibit distinct differences that have been attributed to wave-current interaction differences 

for short-wavelength gravity waves and capillary waves. Existing wave-current interaction 

theories have been found to adequately describe reported measurements of the short-gravitywave (— 30-cm) current response, but appear to underpredict the response of capillary 

(-3-cm) waves. These hydrodynamic results suggest that internal-wave images from an 

L-band SAR can be explained by known wave-current interaction phenomena, whereas

4-89
/N ILLUMINATION 0 lOk 

45N 

35N 

Fig. 4.43. SIR-B image of the New York Bight (Data Take 9621) 

OR%GL 

OF pOOR QUAUT

6O 

4-90
X-band images might not agree with theoretical expectations. Research efforts using SIR-C 

should be directed to investigate these questions. 

SIR-C sensitivity 

to currents, 

fronts, and eddies

The SIR-C experiment will be the first opportunity to obtain dual-frequency SAR imagery of internal waves from space. By varying the angle of incidence from 15° to 500, 

the C-band Bragg waves will change from short gravity waves (11 cm) to near-capillary 

waves (4 cm). The corresponding L-band Bragg waves range from 45 to 15 cm. This 

large Bragg-wave variation with angle of incidence presents a unique opportunity to critically probe the hydrodynamics of wave-current interactions over a wide range of the spectrum and to elucidate the imaging processes underlying SAR signatures of internal waves. 

4.6.5.3 Currents, Fronts, and Eddies 

SAR sensitivity 

to currents, 

fronts, and eddies

SAR imagery from Seasat demonstrated that current-system boundaries, oceanic fronts, 

and mesoscale eddies can be detected via their influence on the short gravity waves 

responsible for L-band microwave backscatter. Figure 4-44 shows the strong expression of 

a Gulf Stream eddy from Seasat SAR imagery. The mechanisms by which a SAR detects 

these phenomena are not well understood. In at least some situations, it is likely that current gradients modify the spectrum of short waves, producing the microwave backscatter. 

In other instances, or perhaps concurrently, sea-state changes can also be induced by seasurface temperature variations that alter the atmospheric boundary-layer stability, giving 

rise to local variations in wind drag. A third mechanism, azimuthal displacements in the 

SAR image plane due to Doppler frequency shifts from variable current components along 

the radar look direction, has also been advanced. 

Seasat images of the Gulf Stream boundary and associated cold-core and warm-core 

rings are consistent with the first two mechanisms. Observations of mesoscale eddies provide additional evidence. Well-planned sea-truth experiments are needed in conjunction 

with SAR observations from space to make further progress in this area. The SIR-C mission can provide this opportunity; acquisition of dual-frequency SAR images should significantly enhance our understanding of the imaging mechanisms associated with these 

phenomena. 

relation of 

surface currents 

to Doppler 

spectrum

Attempts have been made to extract surface currents directly from SAR Doppler spectrum 

information, with the hope of remotely measuring surface-current fields. This technique is 

based on the fact that the Doppler-spectrum centrold depend g on the velocity of the scatterers along the line of sight of the radar. Reasonable success has been demonstrated by 

special processing of aircraft SAR data for currents ranging from 0.5 to 2.0 m/s. Satellite 

measurements present a greater challenge because the Doppler spectrum broadens due to 

the greater platform velocity, whereas the spectrum centroid shifts are only a few Hz for 

currents of interest. Research currently in progress may yield sufficiently accurate Doppler 

centroid estimates to warrant additional testing of this concept during the SIR-C mission. 

Again the dual-frequency and variable angle of incidence capabilities of the SIR-C SAR 

are important because the spectrum shift increases with increasing angle of incidence and 

decreasing radar wavelength. For example, the Doppler centroid shift at C-band and the 

45° angle of incidence will be approximately 8 times larger than that observed by Seasat 

for a given surface current.

4-91
0 10 km

CL- P 3 

OF POOR QUALITY 

.,. .)• 

'.. 

P ' ' 

•: . 

..

.:

• 

Fig. 4-44. SAR image of an area 100 km long, taken during a pass over the western half of a large 

warm-water ring less than a month before the ring began to merge again with the Gulf Stream. Warm 

ring boundaries, perhaps representing current shear zones, are particularly evident in radar imagery. The 

brighter radar signature inside the ring may be at least partially due to the increased surface drag at 

warmer temperatures 

4.6.5.4 Bottom Signatures 

A number of investigators have noted a variety of SAR-observed ocean-surface patterns 

that are closely related to submerged bottom features [4-16]. Figure 4-45 shows a striking 

example of a SAR signature that is clearly related to bottom topography. Even though radar wavelengths do not penetrate the ocean's surface, imaging radars (both real and syn4-92
OF POOR QUALITY 

0 10 km 

Fig. 4-45. This Seasat SAR image of an area 100 km long, taken from above Nantucket 

Shoals, provides a dramatic example of bathymetric expressions occasionally evident over 

large areas. Most of the region included in this image is less than 40 m deep, a good 

fraction is less than 20 m deep, and portions are less than 2 m deep. The Island of 

Nantucket is at the upper left 

thetic aperture) can detect bottom features due to interactions between physical ocean 

processes and the features, which result in a modulation of the small-scale ocean-surface 

scatterers (i.e., the Bragg waves) to which radar is sensitive. These ocean processes include 

surface gravity waves and currents.

4-93
two classes There are two distinct classes of surface patterns caused by gravity waves. First, a SAR 

of surface can often image the surface gravity-wave field itself, and from this image, estimates of 

patterns dominant wavelength and direction of propagation can be extracted. The change in 

wavelength and direction as a wave field propagates into shallow coastal waters can be 

measured and used in a linear wave-refraction model to estimate water depth. This technique has been demonstrated using Seasat SAR imagery. Secondly, nonlinear interactions 

between the surface gravity waves and the Bragg wave sometimes result in distinct changes 

in radar backscatter. These nonlinear wave-wave interactions occur as the gravity-wave 

field propagates onto an abrupt depth discontinuity, such as a reef or shoal region surrounding an island. 

Oceanic currents flowing over bottom features are the second major cause of SARobserved bottom-related surface patterns. The precise mechanism for the appearance of 

these patterns depends on the water depth. Tidally driven currents flowing over shallowwater features interact directly with the Bragg waves, resulting in a distinct surface pattern. 

Tidally driven currents in deep water (>200 m) flowing over bottom features such as seamounts, ridges, shelves, and banks often generate internal waves and areas of upwelling. 

Although the general principles and concepts responsible for SAR detection of bottomrelated surface patterns are now understood, SIR-C will offer the opportunity to further 

study and quantify these phenomena. Research is still needed to determine the exact cause 

of the hydrodynamic interactions that alter the Bragg waves, and the reliability of the 

water-depth estimates inferred from the bottom signatures as a function of angle of incidence, radar wavelength, and surface environmental conditions. 

4.6.5.5 Wind Signatures 

Any geophysical process that directly or indirectly influences the short 30-cm waves 

on the ocean surface will produce a signature in SAR imagery. For example, surface expressions of winds, waves, currents, and bathymetry have all been observed in the imagery from Seasat. Some of these surface expressions are easily visible in the spatial 

domain; others are much more obvious in the spectral domain. Moreover, some signatures 

are instantaneous expressions of the local wind field, while others are the results of winds 

occurring many days previously and thousands of kilometers distant. 

strong Figure 4-46 illustrates a Seasat SAR image in a region of widely varying surface winds. 

correlation The overall brightness of the SAR image is generally correlated with the amplitude of the 

of SAR image 30-cm surface waves, which in turn respond directly to the local wind. This relationship is 

brightness most clearly evident at very low wind speeds, where the 30-cm waves are effectively exwith surface tinguished. Although the amplitude of these waves may not continue to increase indefinitely 

wind speeds with wind magnitude, there is good evidence that the local average brightness (or radar 

backscatter) of SAR imagery is strongly correlated with surface-wind magnitude at least up 

to 13 m/s. For example, Fig. 4-47 shows the correlation between scatterometer-deduced 

winds and SAR backscatter over an entire 900-1cm-long pass (pass 1339, September 28, 

1978), in which the local wind varied from null up to 13 m/s. The deviations between 

scatterometer and SAR may be revealing limitations caused by excessive spatial averaging 

(-50 km) of the scatterometer, while the SAR accurately follows the finer-scale fluctuations in the magnitude of the wind field.

4-94
ORIGINAL P?€ 3 

OF P'' ''"'TY 

0 10 km 

Fig. 4.46. Seasat SAR image of an area 100 km long, located just outside the entrance to 

Chesapeake Bay. Surface wind is essentially calm (U 10 :!51 m/s) in the center (dark) region 

and gradually increases toward the edges. Surface roughness patterns on this scale reflect 

not only surface wind patterns but spatial changes in air-sea temperature differences, 

which directly affect the surface drag coefficient 

wind direction 

information

There is also strong evidence that SAR ocean imagery, at least occasionally, contains 

information related to local wind direction. Under the right conditions, as the horizontal 

component of the wind stresses the surface, it produces large streaks in the imagery that 

correspond to higher backscatter and roughly align with the local wind direction. These 

wind streaks have spatial scales of a few hundred meters to a few km. At the higher wind 

speeds, and when the sea-surface temperature exceeds that of the air, elongated atmospheric 

convection cells can be established, with their long axes approximately aligned with the 

wind. These phenomena produce asymmetric directional spectra at the low wavenumbers,

4-95
tJ I I 

4---W SCATTEROMETER 

A A SAR RMS RESIDUAL 

DIFFERENCES 

OVER ENTIRE PASS: 

•

<lm/s 

II.] 

LU 

LU 

3-

a 

Z

5

I I

4 

0 I I I I I I 

29 30 31 32 33 34 35 36 37 38 39 

LATITUDE, deg 

Fig. 4.47. Comparison of SAR . and scatterometer.derived wind 

magnitudes 

which are generally aligned with the direction of the local wind. Figure 4-48 indicates the 

potential of the Seasat SAR for estimating wind direction with respect to the Seasat scatterometer along a single 900-km pass. On this pass, at least, the residual directional deviations from a smoothed estimate of the local wind field are approximately equal when 

determined with either the scatterometer or the SAR. Perhaps the SAR can provide an estimate of the fine-scale spatial spectrum of the wind field, information that would be useful 

in understanding the physical-error structure in future scatterometers, e.g., NROSS and 

ERS-l. The dependence of the SAR signature on environment, transmitter wavelength, 

polarization, and angle of incidence is presently unknown. 

4.6.5.6 Variable Squint-Mode Experiments 

The possibility of SAR operation in variable squint modes (accomplished by a Shuttle 

yaw maneuver of 10 to 2°/s through at least 90°) will permit a number of critically important experiments over the ocean. 

4-96
275 

225 

0) 

I

175 

0 

Z 

0 

U,

125 

L) 

0 -J 

U

75 

25

I I I I 

A A A 

A .94 A A 

A 

A A 

S •\ • •?A. 

• 'AA

' 

,A

AIRCRAFT

441 ••• --- FITTED WIND

A 

• SAR 

A SCATTEROMETER A 

•• 

prS• 

I I 

29 30 31 32 33 34 35 36 37 38

LATITUDE, deg 

Fig. 4.48. Comparison of wind-direction estimates from both 

the scatterometer and the SAR 

surface winds 

wave spectra 

currents

By collecting data over a variety of look directions (squint angles)-including the wind 

direction (or its supplement)-the azimuth dependence of the backscatter as a function of 

wind speed, radar frequency, polarization, and angle of incidence can be determined. 

Using a similar geometry, the SAR-measured wave directional spectrum can be compared 

with nearly coincident spectra derived with short-pulse techniques (using the same instrument, but with no azimuth processing). Such an experiment will reveal the azimuth dependence of the ocean-wave modulation transfer function. 

By collecting data in an area of strong currents and current gradients, raw SAR-signal 

phase variations can be correlated with surface-current measurements, further exploring the 

potential of SAR for both relative and absolute current estimates. 

4.6.6 Summary of SIR-C Mission Requirements for Oceanography 

The experiments discussed above implicitly impose certain requirements on the SIR-C 

instrument and the mission. This section briefly summarizes those system constraints.

4-97
The value of the supersite concept cannot be determined prior to the evaluation of 

proposals. It is unlikely that particular sites established by one discipline will be compatible with those established by the others, especially in view of the orbital constraints. Most 

oceanic phenomena of interest are sufficiently diffuse that they can be studied in any of 

several regions. 

4.6.6.1 Orbit Parameters 

Most oceanic experiments appear to be optimally served by a slightly drifting orbit, to 

allow a variety of look angles over a fixed test site. 

4.6.6.2 Mission Timing 

six or eighteen Two missions, separated by either six or eighteen months, appear optimal for gathering 

months seasonally variable data over the oceans. For internal-wave and bathymetric experiments in 

separating the Northern Hemisphere, and extremely high storm waves in the Southern Hemisphere, 

missions the July-August period is preferred. For high waves in the Northern Hemisphere, the 

February-March period is optimal. 

4.6.6.3 Swaths and Resolutions 

desirability The range resolution of SIR-B was significantly degraded over that of Seasat, due to a 

of dual receiver bandwidth reduced from 19 MHz to 12 MHz. This resolution loss is particularly 

bandwidth severe in monitoring ocean-wave directional spectra. An increase in the SIR-C bandwidth

is desirable in order to restore the Seasat resolution while maximizing the available swath. 

4.6.6.4. Frequencies, Polarization, and Incidence Angles 

150-450 It is desirable to obtain imagery of some oceanic test sites using all frequencies (L, C, X) 

incidence simultaneously. Angles of incidence ranging from 15° to 450 are desirable, particularly to 

angles reconcile existing differences in SAR imaging theories regarding the ocean and to assist in

the choice of optimum operational modes. Both HH and VV polarization are desired; obtaining cross-polarization imagery is not expected to have a high priority. 

4.6.6.5 Data Products 

BFPQ A four-bit block floating-point quantizer is an excellent scheme for increasing the 

dynamic range while maximizing swath width. However, to prevent potential miscalibration in coastal areas, an override option should be available. 

4-98
radiometric Relative radiometric calibration (long-term system stability) is desirable for meaningful 

calibration wind experiments. Relative stability to a small fraction of a dB is desirable over a single 

stability required pass. 

geometric 

position accuracy 

to 1 km 

variable squint

In experiments conducted over the open ocean, precise location is essential, both before 

and after the experiment. For many experiments involving in situ measurements, location 

accuracy to at least 1 km is necessary. 

The capability for variable squint experiments (— V to 2°/s yaw maneuver) is desirable 

for open-ocean experiments involving the angular dependence of the scattering. 

A variety of data products, sometimes over the same test site, will be desirable to satisfy 

a diversity of users. In many cases, a rapid supply of raw digital data will be more useful 

than the refined image product. A flexible data dissemination scheme will be most efficient.

4-99
Chapter 5 

SIR-C Sensor Experiments 

5.1 Introduction

In this section we discuss a number of experiments that do not fall naturally into the specific 

geoscientific disciplines discussed earlier, either because, as calibration experiments, they 

fulfill the needs of all experimenters and are best carried out directly by the SIR-C 

Project, or because they are too novel and unproven. 

5.2 SIR-C Calibration Experiments 

radiometric 

calibration 

experiments 

corner 

reflectors

As support for the earth-surveillance experiments described in this plan, a method of 

calibrating the overall performance of the sensors in situ is very desirable. Obviously, frequent onboard measurements of transmitted and received power levels represent good engineering practice, and such measurements will be implemented to the extent possible, but 

the use of a distributed antenna in the SIR-C mission greatly complicates this procedure. 

Therefore, an overall system calibration using artificial ground targets of known scattering 

properties is especially important in assisting the interpretation of SIR-C radar data. 

There are several major roles that may be played by surface test targets. For example, 

radar corner reflectors placed in the vicinity of supersites and elsewhere could: 

(1) Provide fiducial ground locations that can be identified in the images. In addition to 

improving cartographic representation of the images, observations of these identifiable reference points would allow improved accuracy in orbit determination. Both 

corner reflector and active calibrations (repeaters) should be used for this experiment. In addition, the method of continuously calibrating the antenna pattern in 

terms of angle by observing a homogeneous target should be repeated, preferably 

using the Amazon rain forest as in SIR-B and Seasat SASS calibration. 

(2) Provide known radar cross sections simultaneously at several frequencies. Such data 

are essential to any attempt to verify cross-sectional changes that vary with frequency. 

(3) Provide targets with 'clean" polarizing properties to test the isolation of crosspolarized receiving channels. Coherent measurements of the actual scattering from 

such point targets can be used to improve estimates of the polarizing properties of 

other targets. 

The SIR-B mission successfully demonstrated the practicality of emplacing artificial 

reflectors; the SIR-C mission, because of its distributed antenna and the several frequencies and polarizations available, is even more dependent on external calibration. In order 

to yield the best results, the calibrators should be viewed at the highest resolution available 

and at as many simultaneous wavelengths and polarization modes as possible. The penalty 

for such viewing complexity, of course, is a narrow swath width, and thus an enhanced 

dependence on accurate orbital prediction.

5-1
ground We also recommend that ground receiving stations be set up to directly measure signal 

receiving strength in several polarizations as a means of verifying antenna patterns and the transmitting 

stations system's performance. While such observations are not a replacement for preflight and onboard calibrations, experience from earlier missions has shown the value of redundant observations to help clarify unexpected results and to verify predicted behavior. 

5.3 Novel Sensor Experiments 

An integral part of the SIR-C mission, in addition to applying SIR-C's multiparameter 

capability directly to the study of the earth sciences as described in earlier sections of this 

plan, is the extension of the sensor system into novel operating modes. Several examples 

are discussed below. 

5.3.1 Squinting 

squint 

observations 

of azimuth 

backscatter 

dependence

By providing information on a target's scattering properties as a function of viewing 

aspect, the "squint" mode has potential applications to several disciplines. As a relatively 

untried technique, however, its utility must first be demonstrated. The radar system of 

SIR-C provides an ideal test-bed for such a demonstration, without requiring substantial 

modifications to the system's nominal configuration, although special maneuvers would be 

required during the data collection, as well as special processing of the data. 

The research areas in which the squint mode might prove especially useful include 

oceanographic measurements of the type detailed in Section 4.6 of this plan, as well as 

several terrestrial applications. For the latter, data collected at two or more squint angles 

would yield information on the azimuthal angle-dependence of the backscatter, which 

might provide a useful discriminant of surface structure. Furthermore, areas having high 

surface relief containing shadowed terrain could be mapped more completely by viewing 

them from more than one aspect angle. For both terrestrial and oceanographic applications, 

a variable squint or spotlight mode would allow additional radiometric resolution at no cost 

to surface resolution by reducing speckle caused by the incoherent averaging of an enlarged data set. 

Two kinds of squint-mode experiments can be envisioned for SIR-C. The first would 

collect data over a given test site with two or more fixed squint angles on subsequent 

overpasses. The second would vary the squint angle continuously during a single overflight, so as to keep the test site within the field of view of the antenna over a range of 

squint angles. The latter mode (referred to as "spotlight") would obviously entail a more 

complex orbital maneuver than the former, but provides comparative data from a shorter 

time base, an obvious advantage in oceanographic applications. 

5.3.2 Bistatic Observations 

In bistatic observations involving an underflying aircraft, simultaneous data can be obtained both in the backward and in one other scattering direction. With properly chosen 

5-2
angles and receiving polarizations, these measurements can distinguish diffuse from quasispecular scattering components. If the aircraft is instrumented to receive simultaneously in 

several orthogonal polarizations, the data set becomes especially powerful, and contains 

useful redundancy. Such observations have become available for portions of Mars, and it 

would be useful to have terrestrial experience against which to compare the planetary data. 

5.3.3 SCANSAR 

For many SAR applications, frequent coverage is preferred but only modest surface 

resolution is required. Examples include the monitoring of sea ice, of flooding, of changes 

in soil moisture, and of ocean phenomena such as internal waves and eddies. In each of 

these cases, repetitive observation is needed at a rate that is not compatible with the finite 

SIR-C mission lifetime and the narrow swath widths set by the usual observing constraints. 

These constraints normally arise from the finite data-transmission bandwidth coupled with 

the need for good resolution and for multiple wavelengths and/or multiple polarizations. 

Even if resolution is degraded, a basic swath-width limitation remains as a result of antenna resolution in the range direction. 

increasing 

swath width 

at expense 

of azimuth 

resolution

A way around these rather fundamental constraints that is particularly useful can be 

provided in the case where an electronically scanned antenna is available, as it is for 

SIR-C. By operating the radar in a burst mode, rather than continuously, the high instantaneous pulse-repetition rates necessary to prevent azimuth ambiguities can be achieved, 

without exceeding the data transmission-rate limitations. Furthermore, by electronically 

scanning the antenna up and down by a beamwidth or so between bursts, the effective 

swath width of the system can be doubled or tripled. The price, of course, is degraded 

azimuth resolution (from the finite burst duration) and a possibly reduced number of 

"looks" as compared to the continuous operating mode. The use of an antenna, electronically scanned in this way, has been given the acronym "SCANSAR." 

5.3.4 Scattering Statistics Investigations 

In some applications, the statistical variation of radar echoes from a surface that is 

thought to be essentially homogeneous is of interest. These variations may arise in successive observations of the same resolved surface element ("look"), or from spatially separated, 

but statistically homogeneous, resolution elements. By assembling data from many such 

elements, the statistics of the surface scattering may be determined and compared with 

those statistics expected purely on the basis of random scattering events. Any departure 

can form the basis for characterizing the surface, and may serve as a discriminant. 

This type of experiment can be performed with many existing SAR data sets of course, 

but the multiple-wavelength capability and the uniform coverage of large areas available to 

SIR-C renders it a potentially more valuable resource for this application. 

5.3.5 Interferometric Topography 

This experiment uses a novel but powerful technique made possible by the waveform

coherence intrinsic to SAR measurements. As diagrammed in Fig. 5-1, coherent echo data

5-3
Fig. 5-1. Geometry for SAR interferometry 

obtained from separate orbital passes that nearly, but not quite, reproduce each other's geometry relative to the surface are combined interferometrically. Because it measures directly 

the phase of the echo as received at two or more spatially separated locations, this method 

is very sensitive to the angle of arrival of the echo. 

sensitivity to 

topographic 

variations of 

5 meters or more

With a baseline having a vertical component on the order of half a kilometer, sensitivity 

to topographic variations of as little as five meters is possible for surface elements that 

have retained a fixed relationship between the observations. An example of such an interferometric reconstruction is given in Fig. 5-2. Unlike conventional stereography, it is not 

necessary to identify common feature signatures in order to determine topography from 

their overlap. Thus topographic measurements of featureless "rolling plains" are possible. 

If the elements of the surface have moved by more than a few centimeters between two 

or more observations, the coherence is lost and the method fails. If only a portion of the 

surface is mobile, say the surface of a river or an ice pack, the loss of coherence calls immediate attention to this fact, and may be used to quickly identify such features. 

In order to satisfy the requirements of this method, the later orbits must be suitably 

aligned with their earlier counterparts. Some overlap will occur near the northern and 

southern culminations of adjacent orbits in any case, but if this technique is to be used 

more extensively, it will be necessary to fine-tune the orbital periods of the SIR-C mission 

to ensure commensurability within the flight duration. 

5-4
ORIGINAL PA! ORtGINAC PAGE 

LOR 'T'Y' OH COLOR PHOTOGRAPH 

/N

0 2 k 

Fig. 52. Composite made from two Seasat passes, separated by 3 days, near Baker, California. The colors, superimposed 

on radar brightness, show the phase difference between corresponding pixels of the two passes. Contours of constant 

color are in excellent agreement with published elevation contours. The contour resolution is about 100 m. (Courtesy of R. 

Goldstein, JPL)

5-5
5.3.6 Observations of Rain Cells 

C-band and 

X-band 

sounding of 

atmospheric 

rain cells

The C-band instrument (and X-band, if carried) can be used to sound the atmosphere 

for the presence of rain. Under the proper conditions, it may even be capable of mapping 

the location, altitude, and intensity of rain cells. To accomplish this, the Shuttle must be 

flown with the antenna pointing as closely to nadir as possible in one of two 

configurations. 

In the first, the long axis of the antenna is kept parallel to the orbital velocity vector, 

yielding a resolution of approximately 16 km across track, and 1 km along track. In the 

second, the Shuttle is yawed 900 so that the short axis of the antenna coincides with the 

velocity. If the pulse repetition rate is increased sufficiently to suppress the associated 

azimuth ambiguities, an aperture can be synthesized that yields 1-km resolution along track, 

while the long axis of the antenna also gives a cross-track resolution of 1 km. The latter 

mode is particularly desirable, since rain cells are typically only a few kilometers across. 

Note that the echo correlation time necessary to synthesize 1-km azimuth resolution is only 

about I ms at C-band, while the observed correlation has a duration of the order of 5 ms. 

Preliminary calculations suggest that rainfall rates in a cell that exceed about 1 mm/s 

may be detectable with the SIR-C system, provided a modulation waveform capable of distinguishing the relatively weak rain echo, occurring only a few tens of microseconds ahead 

of the far stronger surface echo, can be devised. 

5-6
Chapter 6 

SIR-C Data Collection and Image Processing 

6.1 Site Recommendations 

Based on experience gained during the SIR-B mission, and considering the increased 

complexity of SIR-C, the strategy for site selection will be to concentrate on acquiring 

data over a limited number of test sites. This will optimize mission operations and facilitate coordination of simultaneous ground-truth and aircraft-underflight activities. Although 

actual site locations will depend on investigators selected for the SIR-C Science Team, the 

Science Working Group recommends some general site types for each discipline: 

(1) Geology—polar, arid, tropical forest areas (deciduous/coniferous) 

(2) Hydrology—arid, southern coastal (Gulf of Mexico), humid, high-latitude areas 

(3) Vegetation—northern-latitude forests, Great Plains (cultural), tropical rangeland/prairie 

(4) Glaciology—Beaufort Sea, Antarctic (Ross Shelf), Greenland Sea 

(5) Oceanography—A gulhas Current (South Africa), North Sea 

The Science Working Group also recommends a high-inclination orbit for the SIR-C experiment. An orbital altitude of approximately 240 ± 20 km will be required for a oneday repeat cycle, as shown in Fig. 6-1. Examples of potential orbits with inclinations of 

57° and 92° are shown in Figs. 6-2 and 6-3, respectively. 

6.2 Mission Timing Recommendations 

The SIR-C mission should comprise at least two flights. Each discipline team on the 

SWG has recommended optimum flight times during the year, based on maximum scientific return. These are shown in Fig. 6-4. 

two flights 

required

For geologic investigations, one summer (May-June) flight and one winter (NovemberFebruary) flight are recommended in order to enhance the seasonal differences in scenes 

with vegetation or snow/ice cover, and the seasonal changes in river discharge. Essentially 

the same rationale exists for hydrologic investigations. For vegetation studies, the first 

flight should be in late spring (planting time in the Northern Hemisphere), and the second 

in late summer (peak biomass). For glaciologic studies, the ideal time for the first flight 

would be late March through April (northern winter, but with enough light to permit 

ground-truth operations), and the second flight in either August (maximum melting) or the 

first two weeks of October (freeze-up). For oceanographic investigations of high waves in 

the Northern Hemisphere, the February-March period is optimal; for internal wave and 

bathymetric experiments in the Northern Hemisphere and extremely high storm waves in 

the Southern Hemisphere (e.g., the Agulhas Current), the July-August period is preferred. 

These optimum times are obviously quite different for each discipline and there is no 

common set of two flight times which is best for all investigations.

6-1
ORBITS, DAY

:A::5o: 

46 ORB1 S, 

31 , ORBITS , 2 DAYS 

16 ORBITS DAY

4::isiDi:2:::i 

ORBITS'

I I I I I

500 

400 

- 300 

-4 

a 

-a

200 

100 

0

0 15 30 45 60 75 90

ORBITAL INCLINATION, deg 

Fig. 6. 1. Altitude vs. orbital inclination for various orbital 

exact-repeat cycles 

6.3 Data Acquisition and Processing 

As previously described, the SIR-C instrument will collect both C-band and L-band data 

with each frequency band consisting of direct (HH, VV) and cross-polarized (HV, VH) 

data. It will also be possible to acquire X-band VV data if the X-SAR instrument is flown 

along with SIR-C. Considering all possible combinations, as many as 8 to 9 different data 

types will be available for any given target area. These data will be digitized and formatted onboard and recorded on an onboard high-density digital recorder. In addition, some 

data will be downlinked directly via the Tracking and Data Relay Satellite System 

(TDRSS). The transmitted data will be received by the TDRSS ground station at White 

Sands, New Mexico, and will, in turn, be relayed via DOMSAT to the high-data-rate 

recording facility at GSFC (Fig. 6-5). The tapes will then be shipped to JPL for processing into imagery and eventual distribution to the SIR-C investigators. 

ADSP image- All SIR-C raw data will be processed digitally by the Advanced Digital SAR Processor 

processing in (ADSP). This processor, designed and built by JPL, can perform SAR image correlation at 

real time real-time or near-real-time throughput rates. The system configuration for SIR-C is shown 

in Fig. 6-6. It centers around the ADSP, which consists of 4 racks of VLSI circuit boards 

6-2
l0b 1200

ORGUAL PACE L3 

OF 'NOR QUAIJTY 

00 60°E 120°E 180°

80° 

60° 

40° 

20° 

0° 

20° 

40° 

60° 

80° 

60° 

400 

20° 

0° 

20° 

400 

60°

180° 120°W 60°W 0° 60°E 120°E 180° 

Fig. 6.2. Potential ground tracks for an orbit with a 570 inclination 

80° 1200 000 0

60°E 120°E 1800 

80° 800 

60° 600 

40° 40° 

20° 20° 

0° 0° 

20° 20° 

40° 40° 

60° 60° 

80° 80° 

180° 120°W 60o 0° 60°E 120°E 180° 

Fig. 6-3. Potential ground tracks for an orbit with a 92 0 inclination

6-3
FEB APR JUN AUG OCT DEC JAN MAR MAY JULY SEPT NOV 

---a--a-----

a. NONE 

VEGETATION 

_____-----a------ 

_____-- . a a.. 

___------------ a. I.. 

L.I1 I.Ie1:flWil

OPTIMUM MONTHS 

Fig. 6.4. Optimum SIR-C mission times for each science 

investigation

TDRS S

SPACE 

SHUTTLE 

WHITE SANDS, N.M. 

GSFC

Fig. 6.5. SIR-C data downlink path 

controlled by a VAX 11/730. The system also features a SIR-C specific-input interface, 

two high-density digital recorders (HDDRs) for the input and output data, and a scrolling 

display with a videocassette recorder for quick-look image products. 

The input interface contains logic necessary to decode the subcommutated header data 

in real time and to perform data quality analyses such as bit-error-rate checks, radarparameter change detection, or data-dropout detection. The decoded header data are transferred to the VAX controller for initialization of the autofocus and clutterlock algorithms. 

In addition, the data are used for determining range-line and reference-function sizes as 

well as for estimating the geometric and radiometric correction parameters (e.g., antenna 

pattern, angle of incidence, azimuth skew, slant range, etc.). 

6-4
1 

I CUSTOM COMPUTATIONAL HARDWARE I 

HDDR Ui TURN RANGE _H CORNER I I AZIMUTH IMULTILOOK LLJ OUTPUT I HDDR I INTERFACEJ PROCESSOR MEMORY PROCESSOR 

I I I

PROCESSOR 

I

INTERFACE

I 

I 

I I 

I

I 

I

___ 

LBR 

I

80861 I PROCESSOR I 

I I I 

L ---------.4 H VIDEO VCR 

I VAX 11/730 ii CONTROL 

COMPUTER

--

BsPP 

HDDR - HIGH-DENSITY DIGITAL RECORDER

__

I I I

I I 

LBR - LASER-BEAM RECORDER I ARRAY I I FILM I I MASS CCI PROCESSOR RECORDER

I VCR - VIDEOCASSETTE RECORDER Ff RAGE I 

SPP - SPECIAL-PURPOSE PROCESSOR

Fig. 6-6. Block diagram of the SlRC processing system—ADSP custom hardware is shown in dashed box 

The correlation algorithm is essentially two one-dimensional matched filtering operations 

performed in the frequency domain (Fig. 6-7). The reference functions are determined 

from the characteristics of the transmitted pulse for the range reference and from the Doppler characteristics of the echo data for the azimuth reference. 

The ADSP can perform up to 6 x 109 floating point operations per second. It is designed to process raw SAR data into imagery in strips rather than on a frame-by-frame 

basis as in SIR-B. It also has the capability to dynamically update the azimuth reference 

function during the processing to compensate for variations in the earth-rotation rate or 

the Shuttle's attitude. However, the ADSP has a limited capability for updating the radiometric and geometric correction parameters. Depending on the stability of the Shuttle during 

a data take and the application of a specific data set, this may require special processing to 

maintain the fidelity of the output product. For this purpose a special-purpose processor 

(SPP) has been added to perform geometric and radiometric corrections on the image 

products. This system will interface with the ADSP output and will include mass storage, 

an array processor, a video display, and a film recorder. Its primary function is to meet 

the special processing requirements of the SIR-C investigators, for selected segments of 

image data. 

6.4 Data Products 

four levels of SIR-C data products will be furnished at four levels, as summarized in Table 6-1. 

data products Figure 6-8 outlines the expected schedule for SIR-C image processing at each level.

6-5 
DATA SAMPLES 

FFT 

RANGE RANGE 

REFERENCE COMPRESSION 

SPACECRAFT EPHEMERIS

FFT1 

DATA I I 

PRE- CORNER 

PROCESSOR TURN 

survey products 

will require 

2 months

FF1 

AZIMUTH AZIMUTH 

REFERENCE COMPRESSION 

IMAGE 

MERGE AND 

OVERLAY 

POSTPROCESSOR 

GEOMETRICALLY 

CORRECTED 

IMAGE 

Fig. 6.7. Functional block diagram of the image-formatting algorithm used by the ADSP 

6.4.1 Level 0 Products 

The SIR-C raw-data set will consist of digitized echo data for two frequencies, with each 

frequency containing one to three different polarizations. Contained in the raw-data header 

are the radar parameters and Shuttle parameters required for the processing. In addition, 

high-precision postflight attitude and trajectory files will be available 2-3 months after the 

mission. Approximately 1 month will be allotted for data validation and sensor-performance 

evaluation. During this period copies of the high-density digital tapes (HDDTs) for other 

processing centers will be made and a limited number of raw data computer-compatible 

tapes (CCTs) will be available to individual investigators. 

6.4.2 Level 1 (Survey) Products 

Following this period, data will be processed in a Level 1 survey mode to assess the 

quality and specific coverage of the data set. As a minimum for this pass, all HH data will 

be processed, plus a subset of the VV and cross-polarized data, to ensure that some im6-6
HD 

AT

Table 6. 1. SIR-C data products 

Data level Description Options 

Level 0 Digitized raw echo data HDDT in BFP 

CCT in BFP 

CCT, decoded into bytes 

Level 1 Survey image data products: I to 16 looks 

complex image data, 16-bit HDDT or CCT 

floating point 

Level 2 Standard image data products I to 16 looks 

8 or 16 bits integer 

HDDT, CCT, film strip 

or image frame 

Level 3 Special image data product Geocoded 

Geophysical units 

Terrain corrected 

Phase image 

Phase difference

Notes: HDDT = High-density digital tapes 

CCT = Computer-compatible tapes 

BFP = Block floating point 

DELIVERY OF 

PRECISION 

EPHEMERIS 

0 12 

DATA QUALITY 

AND 

PROCESSOR 

VERIFICATION 

REPORT 

RAW DATA 

DUPLICATION 

COMPLETE 

(LEVEL 0)

4 5 6 7 8 9 10 11 12 13 14 15 (MONTHS) 

STANDARD 

PRODUCTION SPECIAL 

COMPLETE PRODUCTION 

(LEVEL 2) COMPLETE 

(LEVEL 3) 

SURVEY 

PRODUCTS 

COMPLETE 

(LEVEL 1) 

Fig. 6-8. Expected schedule for SIR-C image products. The schedule for the 

second flight of SIR-C is the same, beginning after month 9 on the chart

6-7 
agery from each target area is available and that the processor can handle all data types. 

This output will be recorded on HDDT, and videocassettes or film strips of this imagery 

will be distributed to investigators for their test sites. This processing will not involve any 

special corrections for Shuttle instability, or for registration of multiple polarizations or 

frequencies, and will require approximately 2 months. All imagery will be detected in a 

16-bit, 4-look pixel format. 

6.4.3 Level 2 (Standard) Products 

standard products The third phase of the processing, requiring 3 to 6 months, will produce Level 2 stanwill require dard image products as requested by the principal investigator for each data take. The pro3-6 months posed options are 

(1) Complex image data, 16-bit floating point 

(2) Single-look, double-look, or 4-look data 

(3) Detected image data (byte format 8-bit or 16-bit integer) 

(4) Range-compressed-only data 

(5) Radiometrically uncompensated data 

(6) Slant-range de-skewed data 

The real-time output will be recorded on HDDT and film strips via the laser-beam recorder. 

These film strips will be annotated every 10 s (-70 km) with the time and location, and, 

for each data take, an ancillary data record will be generated containing the full set of 

Shuttle, processor, and radar parameters, including 10-s updates of time-varying parameters. The ancillary data record will be stored in the SPP and recorded on CCT for distribution to the investigators. 

This processor will interface to both the HDDR and the ADSP and will serve an additional function as the SAR data catalog. 

6.4.4 Level 3 (Special) Products 

geocoded images 

complete within 

15 months

In parallel with the generation of standard image products as described above, this 

processor will produce a limited amount of Level 3 special image products as required by 

the investigators. A proposed partial list for this category is 

(1) Geocoded images (i.e., rotated to north and resampled to specified map projection) 

(2) Radiometrically calibrated products in geophysical units (i.e., backscatter coefficient) 

(3) Imagery corrected for foreshortening due to terrain variations 

(4) Pure phase imagery, the phase difference between any two polarizations, or magnitude ratios between polarizations or frequencies 

The uncertainty estimates for the radiometric and geometric calibration have been described 

in Section 3.3. Depending on the amount of special processing, it is expected that this 

phase will last from 9 to 12 months and will be completed approximately 15 months after 

each flight. 

6-8
6.5 Data Distribution 

As previously described, the special-purpose processor will also act as a data-base management system for the SIR-C, and to a limited extent, the entire terrestrial SAR catalog. 

The system will contain all of the fundamental and derived parameters for the SIR-C data 

set. The catalog will contain maps illustrating the SIR-C coverage and will also have the 

capability to cross-reference target location with any of the SIR-C parameters to determine 

the extent of a particular type of coverage. In addition, coverage maps from Seasat, SIRA, and SIR-B will be available with algorithms for determining the extent of multisensor 

coverage. 

The catalog will be accessible by modem to remote users, enabling them to determine 

processing status of a target area, or communicate to the processing team a special 

processing or distribution request. The plan includes providing to remote users a limited 

capability for on-line access to low-resolution image data. The availability of this service 

will depend primarily on the expected development of mass optical storage and high-datarate modems and communication links. 

The primary means of product distribution will be via air freight. Survey products 

(Level I) will be in the form of a quick-look videocassette (or optical disk) or film strip of 

the investigator's test area. This will be provided approximately 3 months after the flight, 

primarily for survey purposes and, in the case of data from the first flight, providing input 

to data collection on the second flight. Associated with this will be a limited ancillary data 

set with periodic time and location updates. Note that the high-precision ephemeris and attitude data will not be available at this time; therefore, the radiometric and geometric fidelity of the survey products may not meet final product requirements. 

Based on investigator evaluation of the survey products and a priority schedule determined by the science team, production and distribution of the standard and special data 

products (Levels 2 and 3) will begin 3 months after the flight and will last for a period of 

approximately 1 year. This schedule optimally will meet the special needs of the investigators by generating a variety of low-level image products. The large volume of data associated with full-resolution SAR imagery precludes electronic transfer of this imagery. 

However, the processor development plan will, at a minimum, include access to the SIR-C 

ancillary data set and, potentially, remote access to low-resolution, compressed SIR-C 

imagery.

6-9
Chapter 7 

Summary 

The purpose of this concluding chapter is to summarize the key geoscientific and sensor 

experiments presented in Chapters 4 and 5, and to summarize the required sensor performance for the conduct of these experiments. 

7.1 SIR-C Geoscientific and Sensor Experiments 

This section summarizes the various classes of SIR-C experiments that could be conducted in various geoscientific disciplines. It also summarizes various sensor experiments. 

It is again emphasized that this is not intended to be an all-inclusive list, and that other 

worthwhile experiments not included below may be conducted with SIR-C. 

7.1.1 Geology

Six different classes of potential SIR-C geologic experiments have been described: 

cold-region (1) Cold-region geomorphology experiments would concentrate on glacial and periglacial 

geomorphology landform mapping as well as on other cold-region features, possibly including permafrost, in order to better understand how these landforms are modified by tectonic 

and climatic controls. 

fluvial (2) SIR-C images would be used to display subtle relief features associated with watergeomorphology shed boundaries, and to analyze the texture of landforms produced by downslope 

movement. 

lit hology, (3) It is expected that the use of multifrequency, multipolarization SIR-C data will allow 

rock weathering, the detection of different lithologies/ages of stratigraphic sequences because of their 

and distinctive backscatter curves related to surface roughness. In fault zones, this may 

geochronology lead to a technique to estimate the rate of slip per unit of geologic time. SIR-C 

multifrequency, multipolarization images would be used to study the structure of 

different weathered surfaces and to relate that structure to different horizons of the 

same material. Such a study would also attempt to use SIR-C imagery to determine 

quantitative measures of morphology on scales of 1 to 20 km that could be used as 

input into available slope-wash process models. By analyzing images of various 

polarizations and frequencies (which depend on surface roughness, blockiness, and 

age), it may be possible to derive relative age dates for lava flows and alluvial 

deposits.

7-1 
tectonics and 

geologic 

boundaries 

geobotany 

radar stereo 

and topography

(4) A high-inclination orbit of SIR-C will allow the coverage of Precambrian shields 

on most continents, which should permit improved structural mapping along 

traverses that are both normal and parallel to selected fronts (e.g., the Grenville 

front in Canada). The multiple angles of incidence and the multipolarization capability of SIR-C may also be useful in distinguishing and mapping ophiolite complexes, 

lava flows, or other lithologies related to tectonism along plate margins. 

(5) The detection and evaluation of stress in vegetation is a key element in geobotanical 

investigations. SIR-C multifrequency, multipolarization images may help to identify 

the detection of distinctive signatures of stressed plant communities that are related 

to underlying lithologic units. 

(6) SIR-B demonstrated that images using multiple angles of incidence can be used to 

produce radar-derived topography. SIR-C will allow this concept to be further tested at various frequencies and polarizations. It is also envisioned that a diverse range 

of geomorphologic investigations could be conducted with the topographic data derived 

by SIR-C. 

7.1.2 Hydrology 

Eleven classes of hydrology experiments have been suggested, which range from and to 

wetland to high-latitude regimes: 

surface 

penetration in 

hyperarid regions 

semiarid-region 

soil moisture 

spatial 

variability 

and scale

(1) The surface-penetration results of SIR-A could be extended by using the multipleparameter capability of SIR-C to delineate buried ancient drainage networks and 

other subsurface hydrologic features. 

(2) SIR-C imagery would be used to study temporal and spatial variations in the soil 

moisture levels in the top horizons of semiarid regions. Because of the short duration of the mission, temporal-variation studies would be based on seasonal differences or on targets of opportunity. 

(3) These experiments would emphasize the spatial variability of hydrologic parameters, 

especially the scale of hydrologic units. SIR-C images would be used to develop 

criteria for hydrologic uniformity. Because of the short duration of the mission 

these studies would have to be based on targets of opportunity. 

SAR image (4) These experiments would concentrate on relating SAR images of precipitation events 

sensitivity to (as soil moisture) to rain-gauge data and to determine if the SIR-C imagery could 

precipitation be effectively used to interpolate between rain gauges. The optimum frequencies, 

polarizations, and angles of incidence for this purpose would also be investigated. 

7-2
SAR image (5) The objective of this experiment would be to determine how multiple-parameter 

sensitivity to radar measurements could be used to integrate the four characteristics that are used 

hydrologic as input parameters to runoff models: vegetation, soil structure, surface roughness, 

characteristics and soil moisture. 

flood (6) If a flood occurred during either mission, SIR-C imagery could be used to determine 

mapping the optimum frequency, polarization, and angle of incidence for delineating flood 

boundaries and land-water boundaries through vegetation canopies. 

groundwater (7) The two flights of SIR-C would be used for observing spatial changes in groundresource water discharge and recharge areas resulting from seasonal differences in soil 

analysis moisture and surface waters. 

wetland (8) This experiment would concentrate on the different vegetation-penetration capabilities of 

boundary L-band versus C-band for the purpose of identifying understory wetland boundaries. 

delineation It would also examine the ability to discriminate among vegetation types as an indicator of underlying soil conditions. Results from these studies would also define the 

system characteristics useful for flood monitoring. 

snow-covered (9) The shorter wavelength channels of SIR-C and, especially, the X-band will be useful 

watershed for identifying snowpack areal extent, snow-water equivalent, and condition. The 

investigations two-season flights and polar orbit of SIR-C should allow investigation of snowcovered watersheds over a wide range of latitudes and permit the first quantitative 

comparison of two radar channels (X- and C-band) for relative discrimination of 

snowpack properties. 

glacier (10) SIR-C offers the possibility of examining the changes in ice extent, in crevasse patterns, 

discrimination in the distribution of morainal material, and in ice-surface roughness that have occurred over a 10-year (Seasat) and an 8-year (SIR-A) period. Also, as the backscattering mechanisms in alpine glaciers are still not well understood, an interesting 

experiment could be developed taking advantage of the multiple frequencies, multiple look angles, and variable polarization afforded by the SIR-C system. (See also 

Section 4.5.5.3.) 

permafrost (11) Permafrost, or permanently frozen soil, is not expected to have a distinctive dielectric 

discrimination constant in comparison to rocks or unfrozen soil. However, it may well have a distinctive textural signature related to its surface roughness. The multifrequency, multipolarization capability of SIR-C will allow this to be studied as a target of 

opportunity.

7.1.3 Vegetation 

Four classes of vegetation experiments have been suggested: 

vegetation type (1) This class of experiment involves the use of single- and multi-date radar data (at all 

identification frequencies and polarizations and at high angles of incidence) to establish the degree

to which radar data alone could be used to identify vegetation types. The experi7-3 
ments would then combine the radar data with optical data (e.g., TM) to determine 

the improvement in crop type identification obtained over optical data alone or radar data alone. 

canopy 

biophysical 

properties 

interpretation of 

landscape patterns 

radar penetration 

of vegetation

(2)SIR-C images of canopies (L-, C-, and X-band) at all polarizations and including 

phase images (the difference in phase between HH images and VV images) would 

be related to canopy leaf area index, phytomass, canopy structure, and stress. 

(3)SIR-C image texture would be used for the interpretation of regional landscape 

patterns. 

(4) The multiple-parameter nature of SIR-C allows an excellent opportunity to conduct 

fundamental research investigations into canopy penetration as a function of wavelength, polarization, and angle of incidence. Image texture for each of these 

parameters would be related to canopy characteristics. 

7.1.4 Glaciology 

Four broad categories of ice experiments have been suggested: 

sea ice 

lake ice 

ice shelves, 

ice sheets, and 

alpine glaciers 

snow

(1) The two-season coverage obtainable with SIR-C will allow valuable studies involving 

sea-ice feature verification, ice drift and deformation, spatial variations of ice-pack 

characteristics, the nature of ice margin eddies, and the improved characterization 

of sea-ice types. The discrimination of sea-ice types is expected to be improved by 

the addition of multiple wavelengths and polarizations. 

(2)SIR-C imagery would be used for lake-ice feature verification, for lake- and river-ice 

operations studies, and for investigations of lake-ice dynamics. 

(3) These experiments would concentrate on mapping ice-shelf and glacier boundaries, 

on obtaining a census of icebergs and ice islands, on delineating ice streams in ice 

sheets and shelves, and on studying temporal changes in alpine glaciers. 

(4) The shorter wavelengths of SIR-C will be used for studies of snowpack extent, 

snow-water equivalent, and snow wetness. X-band is preferable for these studies, 

but C-band could also be used, especially for thicker, wetter snowpacks. 

7.1.5 Oceanography 

There are five broad categories of oceanographic experiments that have been suggested 

for SIR-C. 

7-4
directional (1) The purpose of these experiments is to use SIR-C imagery to estimate directional 

wave spectra wave energy spectra as a supplement to global wind-wave forecast models. 

internal waves (2) The objective of these experiments is to improve our understanding of wave-current 

interactions by studies of SIR-C images of surface phenomena associated with internal waves. 

currents, (3) These experiments could utilize SIR-C imagery to detect current-system boundaries, 

fronts, and oceanic fronts, and mesoscale eddies, and would attempt to extract surface currents 

eddies directly from the Doppler spectrum. 

bottom (4) SAR images of shallow-water regions occasionally provide surface expressions of 

signatures ocean-bottom features. SIR-C images could be used to study the physical mechanisms 

responsible for bottom-feature detection, including the nonlinear-interaction mechanism between internal currents, surface gravity waves, and Bragg waves. 

wind signatures (5) SIR-C images could be used to correlate occasionally observed periodic surface signatures, on the scale of 1 km or longer, to the fine-scale properties of the surface 

wind field, including local wind speed and direction.

7.1.6 SIR-C Sensor Experiments 

Although SIR-C is primarily a geoscientific mission, it will allow a valuable test of the 

performance of the sensor itself. This is important because of the new distributed SAR 

technology being used. The flexibility of SIR-C will also allow a number of sensor-related 

experiments that will improve our understanding of SAR imaging as well as the performance of the instrument. 

corner reflection (1) The frequent onboard measurement of transmitted and received power levels is conexperiments sidered good engineering practice, although the distributed SAR technology greatly 

complicates this procedure. It will therefore be essential to also use system calibration techniques that employ artificial ground targets of known scattering properties. 

Corner reflectors could not only provide targets of known radar cross-section, but 

might also serve as targets having "clean" polarizing properties that could be used 

to establish the isolation of cross-polarized receiving channels. The use of calibrated 

ground receivers that could establish the antenna pattern and transmitting system 

performance is proposed. This calibration will be of particular assistance in the 

quantitative comparison of data acquired on the different flights of SIR-C. 

squint mode (2) This would include two kinds of squint operation, the first providing data over a 

given test site with two or more fixed squint angles on subsequent overpasses. The 

second would vary the squint angle continuously on a single pass so as to keep the 

test site within the field of view, thereby allowing a much larger number of looks.

7-5 
bistatic (3) This would involve coordination of SIR-C with an underflying aircraft and could 

observations provide a very useful set of bistatic imaging data at several combinations of angles, 

frequencies, and polarizations. 

SCANSAR (4) This experiment would utilize the electronically scanned SIR-C antenna along with 

a burst mode so as to achieve a high instantaneous PRF, which is necessary to prevent azimuth ambiguities. By electronically scanning the antenna beam up and down 

between bursts, the swath width can be effectively doubled or tripled. 

scattering (5) The statistical variation of radar echoes from a nominally homogeneous surface 

statistics would be examined and compared to the statistical variation expected purely on the 

basis of random scattering events. Departure of SIR-C radar-echo statistics from 

this could serve as a discriminant. The multiple-wavelength capability of SIR-C 

makes this an especially attractive sensor experiment. 

interferometric (6) Coherent echo data from two separate, parallel, and nearby SIR-C orbital passes 

topography could be combined interferometrically to reconstruct the topography of the scattering surface. 

observations (7) The C-band (and X-band, if carried) channels of SIR-C could be used to sound the 

of rain cells atmosphere for the presence of rain. Under the proper conditions, it may be possible to map the location, altitude, and intensity of rain cells. Special antenna orientation geometries are required for this experiment.

7.2 Recommended Mission Parameters and Sensor Performance 

Based upon the geoscientific experiments discussed in Section 7.1 (and Chapter 4), 

recommendations of overall mission parameters and sensor performance levels can be 

made. Some of the sensor recommendations may be considered enhancements to the baseline SIR-C design described in Chapter 3. 

7.2.1 Orbital Parameter and Mission Timing 

It is strongly recommended that the SIR-C orbit have an inclination of at least 570 

Two flights, each in a different season, are required by all the geoscientific disciplines, although 

the optimum timing of these flights depends on the discipline. As shown in Fig. 6-4, a JanuaryJune pair would be satisfactory for geology and hydrology experiments; a March-August pair 

would be satisfactory for glaciology and oceanography; a May/June-August/September pair would 

be preferred for vegetation-science experiments. 

7-6
7.2.2 Swath Widths and Resolutions 

swath width 

of at least 

15 km required

The 40-rn (4-look) nominal resolution of SIR-C at a look angle of 25° in the lowresolution mode is considerably lower than that of Seasat. For estimates of directional wave 

spectra, it may be inadequate. While the 10-MHz bandwidth appears adequate for many 

other investigations; for directional wave spectra, a higher bandwidth would be better. For 

geologic and glaciologic mapping studies where swath widths of 150 km or more are 

desired, a decrease of resolution (and bandwidth) can be accommodated. The minimum 

acceptable swath width is 15 km. 

7.2.3 Frequencies, Polarizations, and Incidence Angles 

A majority of the experiments will make use of multifrequency, multipolarization 

images taken at various angles of incidence. Exceptions to this are oceanography, where 

there appears to be no interest in cross-polarization images, and mapping modes for some 

structural geologic experiments (e.g., studies of the Precambrian shield) where the primary 

interest is in maximum wide-swath imaging. 

7.2.4 Radiometric Calibration 

A number of crucially important SIR-C experiments will ratio images of the same test 

area taken at different times during the mission. These experiments will require that SIR-C 

demonstrate ± 1 dB relative calibration (stability) during the life of the mission, so that 

quantitative comparisons of temporally acquired images may be made. For studies of soilmoisture variations in vegetated regions, for example, it is required that the instrument 

calibration be stable to less than a dB over the life of the mission. For a comparison of 

images taken during the two separate missions, an absolute calibration of ±3 dB is required. 

For studies of spatial variability (across the swath), it is important that processed 

images show good radiometric fidelity across the swath. A good target figure is 0.2 dB in 

conjunction with ground calibration, or better uniformity across spatially homogeneous 

scenes (e.g., the undisturbed ocean or the Amazon forest). 

Other experiments will ratio images acquired at L-band and C-band and use the ratio of 

the radar backscattering coefficients at these two frequencies to determine surface morphological parameters. These will require that both channels be calibrated to ± 1.5 dB (relative to each other) or better. 

7.2.5 Data Products 

Most experiments will require some quick-look (Level 0) uncorrected data delivered as 

soon as possible after the mission. Requirements for survey (Level 1), standard (Level 2), 

and special (Level 3) processing vary from experiment to experiment. Please refer to Sections 4.2.6.5, 4.3.6.5, 4.4.6.5, 4.5.6.5, and 4.6.6.5 for further details.

7-7
Appendix A 

Introduction to Radar Scattering 

A.1 Introduction

This section presents a brief tutorial on radar scattering as it applies to the quantitative 

use of SIR-C data. The relationship between the SAR image intensity and the radar backscattering coefficient is described, and a brief discussion is given of surface and volume 

scattering. 

A.2 The Radar Backscattering Coefficient 

definition 

of the radar 

backscattering 

coefficient

Point targets such as trucks, aircraft, buildings, corner reflectors, etc., produce a radar 

echo whose intensity is dependent on the target's radar cross section a, given in units of 

M2 . Area-extensive distributed targets such as agricultural fields, geologic scenes, or 

oceanic areas produce a radar echo whose intensity is the radar cross section per square 

meter. The radar backscattering coefficient 0 of an area-extensive target is equal to its 

radar cross section (m2) divided by its physical area (m2 ) in the horizontal plane therefore, a° is unitless (m2 rn-2). For rough surfaces and/or at near-nadir angles of incidence, 

c o is large. For smooth surfaces and large angles of incidence, o° is small. The backscattering coefficient often exhibits a dynamic range extending over several orders of magnitude, particularly when angular variations are involved. To compress its range, 00 is 

usually expressed in decibels:

a°(dB) = 10 log a0(rn2 rn-2) (A- 1)

A.3 SAR Image Intensity (Tone) 

After digital processing, the output product of an imaging radar is a digital image composed of a two-dimensional array of pixels, as suggested in Fig. A-i. The intensity (also 

called tone or gray level), or digital number DN(i,j) of the pixel (i,j), is related to the 

power P, backscattered from the corresponding ground cell by 

DN(i,j) = a..fP.(i,j) + b (A-2) 

where a and b are known scaling constants. The above relationship assumes that the 

receiver uses linear detection, which was the case for Seasat, SIR-A, and SIR-B, and 

which will be the case for SIR-C. The received power r (i, j) is directly proportional to 

the radar backscattering coefficient a°(i,j) of the ground cell, i.e., 

r('J) = K(j) o°(i,j) (A-3) 

where K(j) is a range-dependent system factor that incorporates transmitter power, range 

to target, area of ground cell, and antenna gain function. If K(j) is known on an absolute

A-i
scale it is then possible to directly relate DN(i,j) to a°(i,j) and therefore produce an image whose intensity can be related on an absolute scale to the backscattering coefficient. If 

only the relative variation of K(j) is known, a relative backscattering image can be generated. Both internal and external calibration tests are planned for SIR-c; these tests will establish the radiometric calibration of SIR-C. This Science Plan calls for an absolute 

calibration accuracy of ± 3 dB and a relative calibration of ± 1.5 dB. 

DN (I

GE 

PROCESSOR 

1 RADAR 

Fig. A.1. Correspondence of the radar backscatter coefficient 

at location (1,1) pixel in the scene, to the (!,j) digital number in 

the processed image 

The radar backscattering coefficient, which is analogous to the bidirectional optical reflectance (BDRF) for the special case where the source and detector are at the same location, provides the link between the physical properties of the imaged scene and the radar 

observations. The purpose of this section is to introduce the nonspecialist to the general 

topic of radar scattering from area-extensive targets. 

A.4 SAR Image Speckle (Texture) 

SAR uses coherent illumination of the scene and coherent detection of the backscattered 

signal to achieve high resolution in the azimuth direction. The total signal backscattered 

from a ground cell is the coherent sum of the signals backscattered from all the scatterers 

contained in the ground cell. Terrain surfaces usually consist of a large number of randomly distributed scatterers. This randomness is responsible for image speckle, which 

takes the form of random variability of image tone among pixels corresponding to different 

cells of a uniform target. Thus, speckle is a consequence of the coherent imaging process 

A-2
N= 4'

2 

0.9 

0.8 

0.7 

0.6 

0.5 

Z UU- 0.4 

0.3 

0.2 

0.1 

0

DENSITY FUNCTIONS FOR MEAN OF 

N RAYLEIGH DISTRIBUTED VARIABLES 

N 1 2 3 4 

cr/^L 0.52 0.37 0.31 0.28 

dB 1+o/# 3.65 2.73 2.33 2.13 

dB 1- O/.0 -6.41 -4.05 -3.00 -2.84 

statistical 

distribution 

of radar 

backscatter

employed by SAR systems and not a result of spatial variability (natural texture) in the 

physical or electromagnetic properties of the surface. 

If a radar is used to measure cr°(i,j) for a very large number of pixels (i,j) for an 

area-extensive target with uniform properties, the magnitude of an individual a°(i,j) is 

related, in a statistical sense, to the mean value a by 

a°(i,j) a°FN (A-4) 

where FN is known as a fading random variable and has the following properties [A-1, 

Volume II, Section 7-2]: 

Mean AF = 

Variance OF2 

= 

0.273 N for linear detection 

N = number of independent samples 

Probability density function (p df) of FN = N-convolved Rayleigh pdf (cf. Fig. A-2) 

0.5 1.0 1.5 

FADING RANDOM VARIABLE FN 

Fig. A.2. Probability density functions for mean of N Rayleigh-distributed variables 

number of 

looks

The number of independent samples N, which often is referred to as the number of 

looks, is determined by the amount of spatial and/or frequency averaging incorporated in 

the processing employed in the generation of the radar image. The standard Seasat SAR, 

SIR-A, and SIR-13 image products provided by JPL were four-look images; the azimuth 

resolution was degraded by a factor of four to reduce the effects of fading fluctuations. 

However, the capability exists to process the signal data to produce images for any integer 

value of N. The same capability will be available for SIR-C.

A-3
A.5 Surface and Volume Scattering 

surface 

scattering

The signal backscattered from an area-extensive target may be the result of surface scattering, volume scattering, or both. The relative importance of surface and volume scattering is governed by the surface statistics of the target boundary, the inhomogeneity of the 

medium underneath the surface, and the penetration depth of the medium. All these factors 

are strong functions of the wavelength X. 

The penetration depth in sea water is only a few millimeters at microwave frequencies. 

Hence, the signal backscattered from the sea contains no scattering contributions from the 

subsurface water volume (cf. Fig. A-3), although it may contain volume-scattering contributions generated by inhomogeneous volumes of foam and other material riding over the 

water surface.

D€ NT INC 

DIFFUSE SPECUR 

MODERATE STRONG 

MODERATE 4 FORWARD WE FORWARD 

BACKSCATTER\ I /SCATTER BACKSCATTER SCATTER 

NO PENETRATION NO PENETRATION 

(a) ROUGH WATER SURFACE (b) CALM WATER SURFACE

(c) HIGH-LOSS CANOPY, NO (d) LOW-LOSS CANOPY, 

SIGNIFICANT GROUND SIGNIFICANT GROUND 

CONTRIBUTION CONTRIBUTION 

Fig. A-3. Surface scattering from (a) rough water surfaces and 

(b) calm water surfaces, and volume scattering from (c) high-loss 

vegetation canopies and (d) low-loss vegetation canopies 

volume 

scattering

By contrast, backscattering from a vegetation canopy is dominated by volume scattering. 

Because a vegetation canopy is typically more than 99 percent air by volume, the average 

relative permittivity of the canopy is only slightly larger than unity. Consequently, the 

reflection coefficient of the air-canopy boundary is approximately equal to zero, which in 

turn leads to a negligible surface scattering contribution. The canopy interior, however, is 

amenable to strong volume scattering because it is very inhomogeneous at the centimeterwavelength scale. If the penetration depth of the canopy is comparable to or smaller than 

the canopy slant height (along the direction of observation), contributions from the underlying ground surface may also be present in the backscattered signal. 

A-4
penetration 

depth

The penetration depth ô, of a medium is defined as the depth below the surface at 

which the magnitude of the power of the transmitted wave is 13.7 percent of its value just 

beneath the surface. In the majority of situations, the vertical extent (in the medium) of the 

region responsible for the majority of the backscattered energy received by the radar is on 

the order of one to three times the penetration depth 6 . 

The penetration depth is determined by both absorption and scattering losses. At centimeter and longer wavelengths, absorption losses exceed scattering losses for most natural 

media. If scattering losses are ignored, it is possible to calculate the penetration depth 

from the relative dielectric constant of the medium, € = - j €" where €' is the relative 

permittivity and €" is the dielectric loss factor. With the exception of liquid water, natural 

materials satisfy the condition €" / e' << 1, which allows the use of the following single 

expression:

o

P - 2r€" 

The curves in Fig. A-4 illustrate the variation of 6 as a function of liquid water content 

MV

for both soil and snow at various microwave frequencies. It should be emphasized that 

these curves may not be valid in the region around m = 0 because they were computed 

on the basis of the assumption that scattering losses may be ignored relative to absorption 

losses. This assumption may not be valid when the moisture content is very small.

(A-5) 

10-3

o0

SO I L SOIL TYPE: LOAM 

1.3GHz - 

c,I I

4.0 0Hz - 

10.0 CH. 

0 0.1 0.2 0.3 0.4

VOLUMETRIC MOISTURE CONTENT m (9 cm3)

0 I 2 3 4 5

VOLUMETRIC LIQUID WATER CONTENT,, pct 

E 

Z 

0 

Z

101 

100 

10-

Fig. A.4. Penetration depth of (a) loamy soil and (b) snow as a function of liquid water content 

[Al, Volume II, Section 11.51

A-5
An additional caution should be mentioned as related to vegetation. The simple expresion (A-5), which implies no polarization-dependence, is based on the assumption that the 

inhomogeneities in the medium are random in location and orientation. This is often true 

for inhomogeneities such as brine pockets, dust, air bubbles, etc., in polar sea ice. However, it is often not valid for vegetation. For example, stalks are oriented predominantly 

along the vertical direction. Consequently the penetration depth is dependent on both angle 

of incidence and the radar polarization configuration [A-2]. 

A.6 Surface Scattering Mechanisms 

The roughness of a surface refers to the statistical variations of the random component 

of surface height relative to a reference surface. The reference surface may be the unperturbed surface of a periodic pattern (Fig. A-5(a)), as in the case of row-tilled soil surfaces 

or a wind-driven sea surface, or may be the mean surface if only random variations exist 

(Fig. A-5(b)).

RANDOM SURFACE COMPONENT 

PERIODIC 

(a)

(REFERENCE) SURFACE 

(b)

RANDOM SURFACE COMPONENT 

MEAN (REFERENCE) SURFACE -' 

Fig. A•5. Two configurations of height variations: (a) random 

height variations superimposed on a periodic surface, and 

(b) random height variations superimposed on a flat surface 

scattering Several theoretical surface scattering models have been proposed in the literature and 

models have been reviewed in Chapter 12 of Ulaby et al. [A-i, Volume II]. The various models, 

which are applicable for different roughness scales (measured in wavelength units), relate 

the backscattering coefficient cr° to the surface properties through the dielectric constant e 

and the surface-height autocorrelation function p (x). 

Figure A-6 depicts two examples of the physical mechanisms that usually underlie the 

mathematics of the theoretical models. In the first one, the surface is approximated as a 

series of small planar facets, each tangential to the actual surface. Facet models treat the 

scattering or, more appropriately, reflection, from the assemblage of such facets by taking 

into account both their reradiation patterns and the distribution of their slopes. 

A-6
TANGENTIAL SCATTERING FACET 

(b)

L 

.................... .................. 

LL 

Fig. A.6. Surface scattering by (a) tangential facets and (b) 

Bragg-resonant sinusoidal ocean waves, where path length AR 

is an integral number of half wavelengths. The path-length 

difference is AR = L sin 0 where L is the ocean wavelength and 

0 is the angle of incidence 

Bragg 

scattering 

cross-polarized 

backscatter

Scattering from the ocean surface often is described in terms of Bragg resonance. The 

resonance takes place when the signals backscattered from the tiny capillary and short 

gravity waves (which ride on top of the large ocean waves) satisfy the condition 

—sin 0 = n, n = 0, 1, 2.... (A-6) 

where L is the spatial wavelength of the large ocean wave. The resonance phenomenon associated with Bragg scattering can result in strong backscattering from the ocean surface, 

even though the scattering is contributed by a small fraction of the total illuminated area, 

namely those points on the surface satisfying the condition given by equation (A-6). 

The variation of the scattering coefficient otr°(0) with the angle of incidence, 0, depends 

on the surface roughness and the polarization configuration of the transmit (t) and receive 

(r) antennas. The general behavior for a slightly rough surface is shown in Fig. A-7. The 

HH- and VV-polarized curves are identical at normal incidence and are approximately 

equal for 0 < 300. In the plateau region, a,q'° may exceed UHH° by several dB. 

The cross-polarized scattering coefficients cTJJI° and OIJ° (which, by reciprocity, are 

equal to each other) are second-order effects because they are generated by multiple scattering. Consequently, the cross-polarized backscatter is significantly lower in level than the 

like-polarized levels, particularly for slightly rough surfaces at angles in the neighborhood 

of normal incidence.

A-7
Iz 

u-i 

U 

UUu-i 

0 

0 

0 

Z 

LA 

LU 

IU

SLIGHTLY ROUGH SURFACE 

CT

VV

0 

°hh 

0,0 0,0 

vh hv

-

-S S 

-S S

-S 

0 30 60 90

ANGLE OF INCIDENCE 6, dog 

Fig. A.7. Typical angular variations of the polarized scattering 

coefficient for a slightly rough surface 

coherent scatter 

superimposed 

on incoherent 

scatter

The effect of surface roughness on a°(0) is illustrated in Fig. A-8. For a relatively 

smooth (slightly rough) surface, the backscattered signal consists of a strong coherent component that decays rapidly with increasing 0 and an incoherent component that exhibits a 

gentle variation with 0. The coherent component exists for the like-polarization configurations (HH and VV) only. A very rough surface gives rise to incoherent scattering only, 

thereby exhibiting a gentle angular variation across a wide range extending from normal 

incidence to 0 = 70° or higher. Because of the over 7:1 wavelength ratio covered by the 

SIR-C SARs, many surfaces that may appear (electromagnetically) slightly rough at L-band 

will appear quite rough at X-band. 

The level of 00(0) is governed primarily by the dielectric constant f of the scattering 

surface. For soils, € is strongly dependent on moisture content and, to a lesser extent, on 

soil type [A-3}. 

A-7 Volume Scattering Mechanisms 

dependence on Since volume scattering is caused mainly by dielectric discontinuities within a volume 

inhomogeneities and, in general, the spatial locations of discontinuities are random, intuitively we expect

the scattered waves (within the volume) to be in all directions (Fig. A-9). Correspondingly, 

the angular curve for a° exhibits a relatively flat response with increasing 0 up to about 

60°, and then decreases slowly with increasing 0. The exact shape and level of the curve 

- 

A-8
ICIDENT ILLUMINATION 

Iz 

'U 

U 

UU- 'U 

0 

U 

0 

Z 

'U

COHERENT COMPONENT OF 

SLIGHTLY ROUGH SURFACE 

MEDIUM ROUGH SURFACE 

j— NONCOHERENT COMPONENT OF / SLIGHTLY ROUGH SURFACE 

VERY ROUGH 

SURFACE 

NNI 

30 60 90 

ANGLE OF INCIDENCE 6, deg 

Fig. A.8. Angular variation of a° for surfaces of varying 

roughness 

ANTENNA

% '/ ' 

0 No

O1VOLUME ,' - 

O 0

'' 0 ' SCATTERERS 

0

'

c- o 0 0

— 2 SURFACE 

Fig. A.9. An illustration of volume scattering 

depend on several factors, including the shapes, sizes, orientations, and dielectric constants 

of the inhomogeneities present in the medium, and the spatial density of these inhomogeneities (or the variance of the fluctuating dielectric function for a continuous random medium). In modeling volume scattering by an inhomogeneous medium, these factors are 

represented by electromagnetic parameters, such as the scattering albedo and the optical

A-9
thickness, which presumably form the link between the physical properties of the scattering 

medium and its backscattering behavior [A-i, Volume II, Section 11-5 and Volume III, 

Chapter 13]. 

strong radar 

response to 

wavelength-sized 

objects

The wavelength plays a very important role in volume scattering. A radar is a quasiresonant bandpass filter that responds most strongly to objects whose dimensions are comparable to the radar wavelength X. Most natural media include inhomogeneities that span 

over a wide range of sizes; a forest canopy, for example, may have a size distribution 

similar to the hypothetical distribution shown in Fig. A-b. The shaded vertical bars identify the locations of the SIR-C wavelengths; the L-band channel (X = 23 cm) will probe 

tree branches that are tens of centimeters in length, the C-band channel (X = 5.7 cm) will 

be most sensitive to interactions with leaves and/or large needles, and the X-band channel 

(X = 3 cm) will respond to smaller leaves and/or needles. The wave penetration into the 

canopy also is influenced by the wavelength. The extinction coefficient of a canopy increases rapidly with decreasing wavelength, thereby providing a penetration depth of the 

order of one magnitude greater at L-band than at X-band. 

The vegetation canopy example is by no means unique; similar analogies may be drawn 

for snow, sea ice, and other media. 

SIZE DISTRIBUTION OF 

CANOPY SCATTERERS - 

1mm 1cm 10 CM 

SIZE OF SCATTERER 

TWIGS LEAVES BRANCHES

>-

cm 

z 

J 

Z

TRUNKS 

Fig. A. 10. Hypothetical size distribution of canopy scatterers 

A-b
Appendix B 

Radiometric Calibration of the SIR-C System 

The full scientific potential of an imaging radar is realized only when the processed 

images are in the form of radiometrically calibrated maps of the radar backscatter coefficients. The absolute and relative accuracies, as well as the repeatability of these maps, are 

critical factors in the utilization of these data. For the dual-frequency, quad-polarization 

SIR-C system, there are many possible channel combinations, each with a distinct set of 

contributors to calibration errors. 

Within a single channel (e.g., L-band HH) there are two main radiometric calibration 

specifications. The first, absolute calibration, refers to the uncertainty in the estimation of 

the backscatter coefficient from the SAR image intensity as a result of system-induced 

errors such as antenna gain, transmit power level, and range. The second, relative calibration, refers to the uncertainty in the ratio of two data values in the image products (e.g., 

in ratioing of data values within a single scene, spatial ratio, or ratioing data values from 

pass to pass or mission to mission). 

relative Relative calibration specifications may, therefore, be further subdivided into short term 

calibration (data values corresponding to different points on the earth within a single scene) or long 

term (data values for a single point on the earth being compared from pass to pass or mission to mission). A SAR image with good short-term calibration will have good radiometric fidelity across the image; this means that the image intensity will be a faithful analog 

to the actual radar backscattering coefficients across the scene, with no artifacts introduced 

by the antenna pattern or processor. A SAR with a good long-term calibration characteristic (over a period of days, months, or years) will produce repeatable images for multiple 

passes over identical scenes, as a result of good stability of the system gain, antenna pointing, and image processing. 

absolute The principal contributors to errors in the absolute accuracy of SIR-C are expected to 

calibration be the antenna gain, the antenna-pointing direction, the transmitter and receiver gains, and

Doppler errors in the image processor. Each of these error sources can be further subdivided into compensated and uncompensated errors, depending on whether systematic corrections can be applied to the data after acquisition. Table B-1 lists these primary error 

contributors which degrade the absolute accuracy of SIR-C by both compensated and uncompensated errors. The uncompensated error column assumes only nominal corrections 

for the radiometric distortions derived from preflight measurement and analysis. At the 

current stage of development, it is not meaningful to assign a number of standard deviations to these estimates except to say these are "best guesses" of the errors associated 

with each source. The antenna gain error assumes individual panel measurements and analysis to predict the full-array gain. The compensated error would utilize information from 

the active ground receivers and transmitters to refine the estimate during the mission. The 

antenna-pointing contribution derives from the pattern modulation; it is the mean absolute 

error across a 16-km swath evaluated for a 40° look angle with a 0.66° roll error. Table 

B-2 lists the factors contributing to the roll uncertainty. The compensated error value in 

Table B-1 assumes an echo-tracker in the ground processor to refine the look angle estimate by correlating the received pattern with the expected elevation pattern. The transmitter/ 

receiver variation given is the estimated net system-gain change from _20 0 to +80°C. 

The figures given in the compensated error column assume data available from temperature sensors on the antenna panels. These data would be used to derive a thermal map of

B-1
Table B. 1. Dominant error sources for absolute calibration of SIR•C 

Error source Uncompensated error Compensated error 

(dB) (dB) 

Antenna gain (2 way) ±1.4 ± 1.0 

Antenna pointing (2 way) 

(@ 400 with 0.660 roll error) ±1.0 ±0.4 

Transmitter/Receiver gain variations 

(over —20° to +80°C) —0.6. +0.9 ±0.2 

Processor Doppler error 

(5% processor bandwidth) —0.6, +0 ±0.6 

Root-Sum-Square total —1.92, +1.94 ±1.25 

Table B•2. Shuttle-pointing determination error (in roll axis) 

Error source Error (deg) 

Shuttle 

- Inertial pointing accuracy' (3a) ±0.45 

- Navigation base to trunnion misalignment 2 (3a) ±0.36 

- Zero gravity unloading (max. in roll axis) ±0.02 

- Thermal bending (max. in roll axis) ±0.05 

Antenna 

- Boresight misalignment (maximum) ±0.20 

- Beam-steering accuracy (maximum) ±0.25 

Root-Sum-Square Total ±0.661

Notes:

1. The drift error in the inertial measurement unit (IMU) system is 0.11°/hr, assuming no maneuvers since 

the previous alignment [B-i]. An assumption, an alignment, is made every 8 hours and the error is evaluated at the 4-hour point. 

2. This factor reflects the uncertainty in alignment of the attitude sensors in the shuttle nose to the trunnion 

in the payload bay. 

3. The calibration error resulting from an 0.66°-pointing uncertainty at each look angle is defined as the 

mean absolute error across a 16-km swath centered at the boresight. This is essentially a "best-case" analysis of the roll-error contribution. Table B-3 lists the peak error at the edge of a 16-km swath. This error 

obviously drives the overall system uncertainty. The worst-case scenario for relative calibration (pass to 

pass) is actually twice this peak value, assuming a positive roll on the first pass and a negative roll on the 

second pass, for a target area located 8 km off boresight. 

the antenna that could be used to modify the estimates of transmitter and receiver gain (of 

the receive/transmit modules) by using curves measured before flight. The last item in 

Table B-1 is the error resulting from Doppler estimation errors, here assumed to be 5% of 

the processor bandwidth, 

B-2
Table B.3. Worst-case radiometric error from pointing uncertainty 

(evaluated at edge of 16-km swath for roll uncertainty of 0.660) 

Look Angle Absolute (dB) Relative (dB) 

20 ±0.8 ±1.6 

40 ±1.9 ±3.8 

55 ±1.5 ±3.0

sources 

of 

errors

When the radiometric accuracy of a system is specified, scene-dependent errors such as 

speckle, ambiguity noise, and distortion noise (i.e., quantization and saturation errors) are 

typically not considered. The assumption is that the backscatter estimate includes sufficient 

independent samples to reduce the speckle contribution and that the thermal noise determines the noise floor, which can be estimated from the out-of-band power level. This assumes that noise contributions from range and azimuth ambiguities, bit errors, quantization, 

and saturation are small relative to thermal noise. 

In addition, the random phase and amplitude in each subsystem must be budgeted such 

that the integrated sidelobe energy is small (i.e., —15 dB) relative to the main lobe energy. 

If this condition is not met, ground calibration utilizing point targets such as active radar 

calibrators (ARCs) or corner reflectors will not provide an accurate estimate of the system 

gain. Also inherent in the assumption that point targets can be used for calibration is that 

the target phase history can be precisely tracked over the synthetic aperture. Data with 

large Doppler shifts (i.e., squint mode imaging) will require a secondary range compression [B-2] and an autofocus to insure smaller fractional errors in the Doppler-rate estimate. 

This may require a special high-precision processor to be developed separate from the 

ADSP to process data from the calibration site. 

The primary error sources for long-term relative calibration are the antenna-pointing 

direction, transmitter/receiver gain instabilities and thermal variations, and processor gain; 

while for short-term relative calibration it is necessary to know the antenna-pointing direction and the processor gain. These are summarized in Table B-4. Note that the antenna 

peak gain is not a factor in relative calibration, but antenna-pointing errors introduce errors in the antenna gain of one point (direction) in a scene relative to that of another 

point. The pointing error is assumed to be uncorrelated in the long-term but correlated in 

the short-term estimates. Also, the processor error is reduced for the short-term estimates 

due to the slow attitude drift of the shuttle (approximately 0.02°/sec). 

Table B-5 presents a summary of the error sources for relative channel-to-channel 

calibration for two cases: (1) comparison of L-band HH to C-band HH; and (2) comparison of C-band HH to C-band VV. The L-band HH versus C-band HH table includes the 

gain uncertainty for both antennas and both transmitter/ receiver networks. These errors are 

assumed to be independent, since the two antennas exhibit widely separated temperature 

profiles. The antenna-pointing contribution is small since both antennas are mechanically 

boresighted on the same structure, and the only pointing error derives from the phase 

shifters. In addition, the processor contributions are summed since the Doppler estimation 

error for each band is correlated. 

The error summaries have assumed that the system does not fail during the mission.

Until a failure analysis has been conducted for the components comprising the distributed

B-3 
Table B-4. Dominant error sources for relative calibration of SIR-C 

Error source Uncompensated error Compensated error 

(dB) (dB) 

Long Term (pass to pass) 

Antenna-pointing direction/gain 

(@ 40 ° with 0.66° roll error) ±1.41 ±0.58 

Transmitter/Receiver gain 

variations with temperature —0.6, +0.9 ±0.28 

Processor gain —0.6. +0 —0.6, +0 

Root-Sum-Square total —1.64, + 1.67 —0.88, +0.04 

Short Term (within a scene) 

Antenna-pointing direction/gain 

(worst case, cross swath) ±2.0 ±0.8 

Processor gain —0.2, +0 —0.2, +0 

Root-Sum-Square total ±2.0 —0.82, +0.80 

Table B-5. Relative multichannel calibration error sources for SIR.0 

Error source Uncompensated error Compensated error 

(dB) (dB) 

Relative errors (short term) 

L-band (HH) vs. C-band (HH) 

Antenna gain (2 way, 2 frequency) ± 1.98 ± 1.41 

Antenna pointing 

((& 40°, 0.1° pointing error) ±0.1 ±0.1 

Transmitter/Receiver gain variations ± 1.5 ±0.48 

Processor gain —1.2, +0 —1.2, +0 

Root-Sum-Square total —2.76, +2.48 —1.91, + 1.49 

C-band (HH) vs. C-band (VV) 

Antenna pointing (0.1° error) ±0.1 ±0.1 

Receiver gain variations —0.6, +0.9 ±0.2 

Root-Sum-Square total —0.63, +0.92 ±0.28

array, a quantitative estimate of these effects cannot be given. However, if it can be assumed that failures in the transmit/receive modules are random, that these do not cause an 

impedance mismatch in the feed network, and that all failures are detectable hard failures, 

then the resultant effect on performance can be predicted. Under this scenario, the failures 

are essentially analogous to array thinning [B-3] and a 10% failure of the distributed transmitter amplifiers (HPAs) would reduce the radiated power by only 0.5 dB with an additional 0.1-to-0.3-dB loss in directivity (i.e., an increase in sidelobe energy at the cost of 

main lobe energy [B-4]). If these failures were detectable by some type of power or current monitors in the array, then the resultant pattern could be simulated in the processor 

B-4
with negligible effects on calibration. If the transmit/receive unit failures do not follow the 

random scenario or if an impedance mismatch results, then the directivity degradation 

would be more severe. In addition, errors in the beam-pointing determination could result 

from a nondeterministic failure mode. 

Other sources that may contribute to a degradation of overall accuracy relate to transitory 

propagation effects. Neutral atmospheric effects and the effect of rainfall, fog, and clouds 

should be negligible (<0.05 dB) at these frequencies; however, ionospheric scintillation 

could have a significant effect on the data. This effect is limited both in the local time of 

day (1900 to 2400 hours) and the location (below 300 latitude); but, when it occurs, attenuations of several dB could result [B-5]. Attenuation in the propagation could also result 

from Faraday rotation. It has been estimated that this effect can cause variations of up to 1 

dB for mid-latitudes at noon, decreasing to less than 0. 1 dB at night. It may be possible to 

use ionoside data to compensate for significant Faraday rotation over the ground calibration sites.

B-S
Appendix C 

References 

2-1. Pravdo, S. H., B. Huneycutt, B. M. Halt, and D. N. Held, Seasat 

Synthetic-Aperture Radar Data User's Manual, JPL Publication 

82-90, Jet Propulsion Laboratory, Pasadena, California, March 1, 

1983. 

2-2. Ford, J. P., R. G. Blom, M. L. Bryan, M. I. Daily, T. H. Dixon, C. 

Elachi, and E. C. Xenos, Seasat Views North America, the 

Caribbean, and Western Europe With Imaging Radar, JPL 

Publication 80-67, Jet Propulsion Laboratory, Pasadena, 

California, November 1, 1980. 

2-3. Fu, L.-L., and B. Halt, Seasat Views Oceans and Sea Ice With 

Synthetic-Aperture Radar, JPL Publication 81-120, Jet 

Propulsion Laboratory, Pasadena, California, February 15, 1982. 

2-4. Cimino, J. B., and C. Elachi, Shuttle Imaging Radar-A (SIR-A) 

Experiment, JPL Publication 82-77, Jet Propulsion Laboratory, 

Pasadena, California, December 15, 1982. 

3-1. Soofi, K., Clutter Model for Land, Forest, Snow, Sea Ice, and 

Ocean, Remote Sensing Lab Report RSL RT 2923-2, 1978. 

3-2. Swanson, A., Radar Remote Sensing of Rocks: A Scatterometer 

Experiment, Master's Thesis, University of Kansas, 1983. 

4-1. Kahle, A. B., J. P. Schieldge, M. J. Abrams, A. E. Alley, and C. J. 

LeVine, Geologic Application of Thermal Inertia Imaging Using 

HCMM Data, JPL Publication 81-55, Jet Propulsion Laboratory, 

Pasadena, California, September 15, 1981. 

4-2. Kahle, A. B., and A. F. H. Goetz, "Mineralogic Information from 

a New Airborne Thermal Infrared Multispectral Scanner," 

Science, Vol. 222, No. 4619, pp. 24-27, October 7, 1983. 

4.3. McCauley, J. F., G. G. Schaber, C. S. Breed, M. J. Grolier, C. V. 

Haynes, B. Issawi, C. Elachi, and A. Blom, "Subsurface Valleys 

and Geoarcheology of the Eastern Sahara Revealed by Shuttle 

Radar," Science, Vol. 218, No. 4576, pp. 1004-1020, December 3, 

1982. 

4.4. Péwè, T.L., "Alpine Permafrost in the Contiguous United 

States," Journal of Alpha and Arctic Research, Vol. 15, pp. 

145-156, Instar, Department of Geology, University of Colorado, 

1983. 

4-5. Evans, D.L., T.G. Farr, J.P. Ford, T.W. Thompson, and C.L. 

Werner, "Multipolarization Radar Images for Geologic Mapping 

and Vegetation Discrimination," IEEE Transactions on 

Geoscience and Remote Sensing, Vol. GE-24, No. 2, pp. 

246-257, March 1986.

c-I
References 

4-6. Sabins, F. F., R. Blom, and C. Elachi, "Seasat Radar Image of 

San Andreas Fault, California," The American Association of 

Petroleum Geologists Bulletin, Vol. 64, No. 5, PP. 619-628, May 

1980. 

4-7. Elachi, C., L. E. Roth, and G. G. Schaber, "Spaceborne Radar 

Subsurface Imaging in Hyperarid Regions," IEEE Transactions 

on Geoscience and Remote Sensing, Vol. GE-22, No. 4, pp. 

383-388, July 1984. 

4-8. Ulaby, F. T., R. K. Moore, and A. K. Fung, Microwave Remote 

Sensing: Active and Passive, 3 vols., Addison-Wesley, Reading, 

Massachusetts, and Artech House, Dedham, Massachusetts, 

1981-1985. 

4-9. Ulaby, F. 1., and W. H. Stiles, "The Active and Passive 

Microwave Response to Snow Parameters, Part II: Water 

Equivalent of Dry Snow," Journal of Geophysical Research, Vol. 

85, pp. 1045-1049, 1980. 

4-10. Blom, R. G., R. E. Crippen, and C. Elachi, "Detection of 

Subsurface Features in SEASAT Radar Images of Means Valley, 

Mojave Desert, California," Geology, Vol. 12, pp. 346-349, June 

1984. 

4-11. Olhoeft, G. R., "Application and Limitations of Ground 

Penetrating Radar," Expanded Abstracts, 54th Annual 

International Meeting and Exposition of the Society of 

Exploratory Geophysics, Atlanta, Georgia, pp. 147-148, 

December 2-9, 1984. 

4-12. Ulaby, F. T., C. T. Allen, G. Eger Ill, and E. Kanemasu, "Relating 

the Microwave Backscattering Coefficient to Leaf Area Index," 

Remote Sensing Environments, Vol. 14, pp. 113-133, 1984. 

4-13. Jet Propulsion Laboratory, The SIR-B Science Plan, JPL 

Publication 82-78, Pasadena, California, December 1, 1982. 

4-14. Ulaby, F. T., "Radar Signatures of Terrain: Useful Monitors of 

Renewable Resources," Proceedings of the IEEE, Vol. 70, pp. 

1410-1428,1982. 

4-15. Hoogeboom, P., "Classification of Agricultural Crops in Radar 

Images," IEEE Transactions on Geoscience and Remote 

Sensing, Vol. GE-21, No. 3, pp. 329-336, July 1983. 

4-16. Kasischke, E. S., G. A. Meadows, and P. L. Jackson, Use of 

Synthetic Aperture Radar to Detect Hazards to Navigation, ERIM 

Report No. 169200-2-F, 1984. 

C-2
References 

A-i. Ulaby, F. 1., R. K. Moore, and A. K. Fung, Microwave Remote 

Sensing: Active and Passive, 3 vols., Addison-Wesley, Reading, 

Massachusetts, and Artech House, Dedham, Massachusetts, 

1981-1985. 

A-2. Allen, C. 1., and F. T. Ulaby, "Modeling the Polarization 

Dependence of the Attenuation in Vegetation Canopies," IEEE 

International Geoscience and Remote Sensing Symposium 

(IGARSS'84) Digest, Strasbourg, France, August 27-30, 1984. 

A-3. Hallikainen, M. T., F. T. Ulaby, M. C. Dobson, M. A. El-Rayes, 

and L.-K. Wu, "Microwave Dielectric Behavior of Wet Soil - 

Part I: Empirical Models and Experimental Observations," IEEE 

Transactions on Geoscience and Remote Sensing, Vol. GE-23, 

No. 1, pp. 25-34, January 1985. 

A-4. Dobson, M. C., F. T. Ulaby, M. T. Hallikainen, and M. A. 

El-Rayes, "Microwave Dielectric Behavior of Wet Soil - Part II: 

Dielectric Mixing Models," IEEE Transactions on Geoscience 

and Remote Sensing, Vol. GE-23, No. 1, pp. 35-46, January 

1985. 

B-i. Space Shuttle Systems Payload Accomodations Document, JSC 

07700, Vol. XIV, Rev. F, September 1978. 

B-2. Jin, M., and C. Wu, "SAR Correlation Technique - A modified 

Interpolation Algorithm," Digest 1983 IEEE International 

Geoscience and Remote Sensing Symposium, pp. FA-3/1, 1983. 

B-3. Hansen, A., "Communication Satellites Using Arrays," 

Proceedings of the IRE, pp. 1066-1074, June 1961. 

B-4. Jedlicka, A., and B. Blevins, Distributed SAR Architecture Study, 

Physical Science Laboratory, New State University, NASA 

Contract NAS9-95541, February 1984. 

B-5. Rino, C. L., and J. Owen, The Effects of Ionospheric 

Propagation Disturbances on Satellite-Borne Synthetic Aperture 

Radars, Defense Nuclear Agency, Contract DNA001-83C-01 31, 

October 1984.

C-3
TECHNICAL REPORT STANDARD TITLE PAGE 

1. Report NO.JPL 86-29 (2. Government Accession No. 3. Recipient's Catalog No. 

4. Title and Subtitle 5. Report Date 

September 1, 1986 

Shuttle Imaging Radar-C Science Plan 6. Performing Organization Code 

7. Author(s) S. Performing Organization Report No. 

SIR-c Science Working Group JPL 86-29 

9. Performing Organization Name and Address 10. Work Unit No. 

JET PROPULSION LABORATORY

11. Contract or Grant No. California Institute of Technology

NAS7-918 

4800 Oak Grove Drive

13. Type of Report and Period Covered Pasadena, California 91109

JPL Publication 

12. Sponsoring Agency Name and Address 

NATIONAL AERONAUTICS AND SPACE ADMINISTRATION 14. Sponsoring Agency Code 

Washington, D.C. 20546 

15. Supplementary Notes 

16. Abstract 

The Shuttle Imaging Radar-C (SIR-C) mission will yield new and advanced scientific 

studies of the earth. SIR-C will be the first instrument to simultaneously acquire 

images at L-band and C-band with RH, VV, HV, or VH polarizations, as well as images of 

the phase difference between HR and VV polarizations. These data will be digitally 

encoded and recorded using onboard high-density digital tape recorders and will later 

be digitally processed into images using the JPL Advanced Digital SAR Processor. 

There are a large number of potential SIR-C experiments. Geologic studies include 

cold-region geomorphology, fluvial geomorphology, rock weathering and erosional 

processes, tectonics and geologic boundaries, geobotany, and radar stereogrammetry. 

Hydrology investigations cover arid, humid, wetland, snow-covered, and high-latitude 

regions. Additionally, SIR-C will provide the data to identify and map vegetation 

types, interpret landscape patterns and processes, assess the biophysical properties of 

plant canopies, and determine the degree of radar penetration of plant canopies. 

In the field of oceanography, SIR-C will provide the information necessary to: 

forecast ocean directional wave spectra; better understand internal wave-current 

interactions; study the relationship of ocean-bottom features to surface expressions 

and the correlation of wind signatures to radar backscatter; and detect current-system 

boundaries, oceanic fronts, and inesoscale eddies. And, as the first spaceborne SAR 

with multi-frequency, multipolarization imaging capabilities, whole new areas of 

glaciology will be opened for study when SIR-C is flown in a polar orbit. 

17. Key Words (Selected by Author(s)) 18. Distribution Statement 

Geophysics and Oceanography (General)

Unlimited/Unclassified 

19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price 

Unclassified Unclassified