# Presentation: 847767

## Landsat Data Gap Studies: Potential Data Gap Sources

**Greg Stensaas, USGS**
**Gyanesh Chander, SAIC**
**10 January 2007**

## Project Introduction

**USGS Remote Sensing Technologies (RST) Project**
- _[calval.cr.usgs.gov](file:///../../In%20Situ/EDC/UCalgary/ASPRS%20Spring%202005/calval.cr.usgs.gov)_
- Greg Stensaas - (605) 594-2569 - _[stensaas@usgs.gov](mailto:stensaas@usgs.gov)_
- Gyanesh Chander - (605) 594-2554 - _[gchander@usgs.gov](mailto:gchander@usgs.gov)_
- Project provides:
- characterization and calibration of _*aerial and satellite systems*_ in support of quality acquisition and understanding of remote sensing data,
- and verifies and validates the associated data products with respect to ground and atmospheric truth so that accurate value- added science can be performed.
- assessment of new remote sensing technologies
- Working with many organizations and agencies; US and International

## System/Product Characterization

**System Characterization is related to understanding the sensor system, how it produces data, and the quality of the produced data**
**Imagery attempts to accurately report the conditions of the Earth's surface at a given the time.   **
- _Assessed by __*product characterization *__categories:_
**Geometric/Geodetic: **The positional accuracy with which the image represents the surface (pixel coordinates vs. known ground points)
**Spatial: **The accuracy with which each pixel represents the image within its precise portion of the surface and no other portion
**Spectral: **The wavelengths of light measured in each spectral "band" of the image
**Radiometric: **The accuracy of the spectral data in representing the actual reflectance from the surface
**Dataset Usability: **The image data and understanding of the data is easily usable for science application

**Notes:**
Linearity 
Calibration Accuracy and Stability
Detector-to-Detector Uniformity
Dark Noise Artifacts (e.g. Banding, Stray Light)

## Landsat Importance to Science 

**Change is occurring at rates unprecedented in human history**
**The Landsat program provides the **_**only**_** inventory of the global land surface over time **
- at a scale where human vs. natural causes of change can be differentiated
- on a _seasonal_ basis
**No other satellite system is capable/committed to even **_**annual**_** global coverage at this scale**

- Amazonian Deforestation

*Courtesy TRFIC–MSU, Houghton et al, 2000.*

## U.S. Landsat Archive Overview(Marketable Scenes through September 25, 2006)

**ETM+: Landsat 7**
- 654,932 scenes
- 608TB RCC and L0Ra Data
- Archive grows by 260GB Daily
**TM: Landsat 4 & Landsat 5**
- 671,646 scenes
- 336TB of RCC and L0Ra Data
- Archive Grows by 40GB Daily
**MSS: Landsat 1 through 5**
- 641,555 scenes
- 14TB of Data

## Landsat Data Gap Study Team (LDGST)

**The Earth observation community is facing a probable gap in Landsat data continuity before LDCM data arrive in ~2011**
**A data gap will interrupt a 34+ yr time series of land observations**
**Landsat data are used extensively by a broad & diverse users **
- Landsat 5 limited lifetime/coverage
- Degraded Landsat 7 operations
- Either or both satellites could fail at any time: both beyond design life
**Urgently need strategy to reduce the impact of a Landsat data gap**
- Landsat Program Management must determine utility of alternate data sources to lessen the impact of the gap & feasibility of acquiring data from those sources in the event of a gap
- A Landsat Data Gap Study Team, chaired by NASA and the USGS, has been formed to analyze potential solutions

## Team Membership

- Edward Grigsby, NASA HQ, Co- Chair
- Ray Byrnes, USGS HQ, Co- Chair
- Garik Gutman, NASA HQ, Co- Chair
- Jim Irons, NASA GSFC, Community Needs Working Group Lead
- Bruce Quirk, USGS EDC, System Capabilities Working Group Lead
- Bill Stoney, Mitretek Systems, Needs-to-Capabilities Working Group Lead
- Vicki Zanoni, NASA HQ Detail, Team Coordinator and Synthesis Working Group Lead
- Mike Abrams, JPL
- Bruce Davis, DHS (NASA detailee)
- Brad Doorn, USDA FAS
- Fernando Echavarria, Dept. of State
- Stuart Frye, Mitretek Systems
- Mike Goldberg, Mitretek Systems
- Sam Goward, U. of Maryland
- Ted Hammer, NASA HQ
- Chris Justice, U. of Maryland
- Jim Lacasse, USGS EDC

- Martha Maiden, NASA HQ
- Dan Mandl, NASA GSFC
- Jeff Masek, NASA GSFC
- Gran Paules, NASA HQ
- John Pereira, NOAA/NESDIS
- Ed Sheffner, NASA HQ
- Tom Stanley, NASA SSC
- Woody Turner, NASA HQ
- Sandra Webster, NGA
- Diane Wickland, NASA HQ
- Darrel Williams, NASA GSFC

## Team Strategy

**Objective**
**Recommend options, using existing and near-term capabilities, to store, maintain, and upgrade science-quality data in the National Satellite Land Remote Sensing Data Archive**
- Consistent with the Land Remote Sensing Policy Act of 1992
**Approach**
**Identify data “sufficiently consistent in terms of acquisition geometry, spatial resolution, calibration, coverage characteristics, and spatial characteristics with previous Landsat data...” **
- Consistent with Management Plan for the Landsat Program
**Process**
**Identify acceptable gap-mitigation specifications**
**Identify existing and near-term capabilities**
**Compare capabilities to acceptable specifications**
**Synthesize findings and make recommendations**

## Team Assumptions

**Assume 2007 Landsat 7 failure for planning purposes**
**Assume limited lifetime and capability for Landsat 5**
**Focus on data acquisition vs. building a satellite**
**Address DOI responsibility to store, maintain, and upgrade science-quality data in the National Satellite Land Remote Sensing Data Archive (NSLRSDA)**
**OLI data available no earlier than 2010**
**LDCM data specification used to define team’s data quality and quantity goals**
**Landsat 7 unrestricted data policy will serve as the model for acquired data**

## TOOLS FOR OBSERVING THE LAND  Resolution and coverage for different needs....

**“****Moderate Resolution Land Imaging (5-120m)”**

**...****. PLUS RADAR, MAGNETICS, MICROWAVE, ETC., plus airborne and in situ methods**

## Requirements and Capabilities Analysis

**LDCM Data Specification (“Goal”) has been vetted by science and applications communities, and supports the full range of Landsat applications**
**Obtaining data identical to LDCM from existing systems is not possible**
**Minimum acceptable specifications were derived to support basic global change research given available sources of Landsat-like data**
- 2x Annual Global Coverage
- Spatial Resolution
- Spectral Coverage
- Data Quality

**Systems Considered**
- IRS ResourceSat – 1, 2 (India)
- CBERS – 2, 2A, 3, 4 (China & Brazil)
- Rapid Eye – 1, 2, 3, 4, 5 (Germany)
- DMC (Algeria, Nigeria, UK, China)
- Terra/ASTER (US & Japan)
- High-resolution U.S. commercial systems
- IKONOS, Quickbird, OrbView-3
- ALOS  (Japan)
- SPOT – 4, 5 (France)
- EO-1/ALI (US)

##    Landsat Synoptic Coverage

- Landsat

- ALI

- ALOS

- RapidEye

- CBERS IRMSS

- ResourceSat LISS III

- ResourceSat
- AWiFS

- DMC

- CBERS-3,4 WFI-2

- Note:  For purposes of scene size comparison only.  Locations do not represent actual orbital paths or operational acquisitions.

- CBERS MUXCAM

- ASTER/SPOT

**   ****Landsat Synoptic Coverage**

## Systems Considered

**Systems Considered**

## Landsat Data Gap Synopsis

**There is no substitute for Landsat**
- Single source of systematic, global land observations
- Alternate sources may _reduce the impact of a Landsat data gap_
**Data quality and operational capability of potential candidate systems is currently being verified**
- USGS currently working with ISRO ResourceSat-1 (India) and CAST/INPE CBERS (China Brazil)
**Landsat data gap mitigation efforts could serve as prototype for Integrated Earth Observing System (IEOS -- U.S. contribution to GEOSS)**
- Implementation plan correlates with IEOS Global Land Observing System concept
**Several systems could meet special **_**regional**_** acquisition needs during some or all of the data gap period **

## Data Gap Study Team Management

**Landsat Data Gap Study Team (LDGST)**** **
- Developing a strategy for providing data to National Satellite Land Remote Sensing Data Archive for 1-4 years
- Policy and Management Team – Ed Grigsby and Ray Byrnes
- Technical Team – Chaired by Jim Irons
**Data Characterization Working Group (DCWG)**
- Technical group from three field centers (USGS EROS, NASA GSFC, NASA SSC) to evaluated data from IRS-P6 and CBERS-2 sensors
**Tiger Team Charter **** **
- The tiger team is charged with developing & analyzing a set of technical & operational scenarios for receiving, ingesting, archiving, and distributing data from alternative, Landsat-like satellite systems.
- The tiger team will conduct trade studies & assess the risk of the various scenarios & provide rough order magnitude costs for the alternatives

## Overview of the CBERS-2 sensorsCross-Calibration of the L5 TM and  the CBERS-2 CCD sensor

## China Brazil Earth Resources Satellite -CBERS

**CBERS-1, was launched on Oct. 14, 1999**
- The spacecraft was operational for almost 4 years
- The CBERS-1 images were not used by user community
- On Aug. 13, 2003, CBERS-1 experienced an X-band malfunction causing an end of all image data transmissions
**CBERS-2 (or ZY-1B) was launched successfully on Oct. 21, 2003 from the Taiyuan Satellite Launch Center**** **
- The spacecraft carries the identical payload as CBERS-1
**CBERS Orbit**
- Sun synchronous
- Height: 778 km
- Inclination: 98.48 degrees
- Period: 100.26 min
- Equator crossing time: 10:30 AM
- Revisit: 26 days
- Distance between adjacent tracks: 107 km

## CBERS- Sensor Compliment

**CBERS satellite carries on-board a multi sensor payload with different spatial resolutions & collection frequencies**
- HRCCD (High Resolution CCD Camera)
- IRMSS (Infrared Multispectral Scanner)
- WFI (Wide-Field Imager)
**The CCD & the WFI camera operate in the VNIR regions, while the IRMSS operates in SWIR and thermal region**
**In addition to the imaging payload, the satellite carries a Data Collection System (DCS) and Space Environment Monitor (SEM)**

## Work Share (70% China, 30% Brazil)

**Pay load Module (16)**
- CCD (14)				China
- IRMSS (7)			China
- WFI (20)				Brasil
- Data Transmission			China
- Data collection			Brasil
**Service Module (1)**
- Structure				 Brasil
- Thermal Control	             		China
- Attitude and Orbit Control  		China
- Power supply			Brasil
- On-board computer			China
- Telemetry				Brasil

## High Resolution CCD (HRCCD)

**The HRCCD is the highest-resolution sensor offering a GSD of 20m at nadir (Pushbroom scanner)**
**Quantization: 8 bits**
**Ground swath is 113 km with 26 days repeat cycle**
- Steerable upto +/- 32o across track to obtain stereoscopic imagery
**Operates in five spectral bands - one pan & four VNIR **
- CCD has one focal plane assembly
- The signal acquisition system operates in two channels
- Channel 1 has Bands 2, 3, 4
- Channel 2 has Bands 1,3,5
- Four possible gain settings are 0.59, **1.0**, 1.69 & 2.86

## Infrared Multispectral Scanner (IRMSS)

**The IRMSS is a moderate-resolution sensor offering a GSD of 80m (pan/SWIR) & 160m (thermal)**
**Quantization: 8 bits**
**Ground swath is 120 km with 26 days repeat cycle**
**Operates in four spectral bands - one pan, two SWIR  & one thermal**
- The four spectral bands has eight detector staggered arrays mounted along track
- IRMSS has three focal plane assemblies
- The Pan band (Si photodiodes detectors) is located on the warm focal plane
- The SWIR bands & the thermal band (HgCdTe detectors) are located on cold focal planes with cryogenic temps of 148K & 101K respectively
- Four of eight thermal detectors are spare

## Wide-Field Imager (WFI)

**The WFI camera provides a synoptic view with spatial resolution of 260m**
**Ground swath is 885km with 3-5 days repeat cycle**
**Operates in two spectral bands – (Band 3 & 4)**
- 0.63 - 0.69 μm (red) and 0.77 - 0.89 μm (infrared)
- Similar bands are also present in the CCD camera providing complementary data

## Overview of the CBERS instruments

## Relative Spectral Response (RSR) Profiles

**Notes:**
Band 5 RSR was incomplete.  Now have full RSR curve.

## CBERS-2 CCD, Minas Gerais, Brazil

**CBERS-2 CCD, Minas Gerais, Brazil**

## CBERS-2 IRMSS

- CBERS-2 CCD image, Louisiana
- Obtained from on-board data recorder

- CB2-IRM-157/124, 24/3/2004, Catanduva (Brazil)

## Striping in the CCD data

**B1**

**B4**

**B3**

**B2**

## Independent studies are carried out by INPE & CRESDA
INPE used calibration sites in the west part of State Bahia
CRESDA used Gobi desert (Dunhuang) test site in China

- INPE used calibration sites in the west part of State Bahia
- CRESDA used Gobi desert (Dunhuang) test site in China

**L* = DNn / CCn**
- L* = spectral radiance at the sensors aperture W/(m2.sr.um)
- DN = Digital number extracted from the image in band n
- CCn = absolute calibration coefficient for band n

**Absolute Calibration Coefficients**

## CBERS-2 CCD absolute calibration accuracy relative to L5 TM

**Data continuity within the Landsat Program requires consistency in interpretation of image data acquired by different sensors**
- A critical step in this process is to put image data from subsequent generations of sensors onto a common radiometric scale
**To evaluate CBERS-2 CCD utility in this role, image pairs from the CBERS-2 CCD & L5 TM sensors were compared**
- The cross-calibration was performed using image statistics from large common areas observed by the two sensors
**It is very difficult to get coincident image pairs from the two satellites (different WRS)**

## L5 TM and CBERS-2 CCD Image Pairs

**Gobi (Dunhuang) desert test site**
**Data acquired on **
**Aug 25, 2004 (20 min apart)**

**L5 TM WRS Path = 137 Row = 032**
**Nadir looking**

- CBERS-2 CCD Path = 23 Row = 55**  **side-looking (off-nadir-look-angle=-6.0333)

**L5 TM WRS Path = 219 Row = 076**
**Nadir looking Acquisition Date:** **Dec 29,  2004**
**CBERS-2 CCD Path = 154 Row = 126**
** ****Acquisition Date: Dec 30, 2004**

**L5 TM WRS Path = 217 Row = 076**
**Nadir looking Acquisition Date:** **Nov 16, 2005**
**CBERS-2 CCD Path = 151 Row = 126**
** ****Acquisition Date: Nov 16, 2005**

## Slide 31

## Slide 32

## The first China-Brazil Earth Resources Satellite (CBERS-2) data downlink at USGS Center for EROS in support of the Landsat Data Gap Study

**The first China-Brazil Earth Resources Satellite (CBERS-2) data downlink at USGS Center for EROS in support of the Landsat Data Gap Study**

## “CBERS in a box” works - The CBERS-2 capture and processing system is a small computer that can perform the following tasks
ingest the raw data 
show the image data in a “moving window” display
record the raw data in the computer’s hard disk
process the raw data to level 1 products
generate quick looks to populate the Data Catalog of the system
make the level 1 data available to the users

**The USGS Center for EROS Director, R.J. Thompson, visiting with Jose Bacellar from Brazilian National Institute for Space Research (INPE) after a successful China-Brazil Earth Resources Satellite (CBERS-2) data downlink**

**“****CBERS in a box” works - The CBERS-2 capture and processing system is a small computer that can perform the following tasks**
- ingest the raw data
- show the image data in a “moving window” display
- record the raw data in the computer’s hard disk
- process the raw data to level 1 products
- generate quick looks to populate the Data Catalog of the system
- make the level 1 data available to the users

## Challenges and Future Plans

**CBERS-2 High Density Data Recorder (HDDR) is not in use due to power limitations**
**The IRMSS stopped working in Apr 2005 due to power supply failure**
**Limited coincident Landsat/CBERS image-pairs**
- Limited data distribution policies outside the country
- Limited documentation available
- No L7 data downlink in Brazil
**CBERS-2B test downlink at USGS EROS (CBERS cal visit to EROS 2/20/07)**
**Analyze IRMSS data**
**Evaluate the raw data (artifacts, noises)**
- Evaluate the relative calibration of the CCD data
- Evaluate Bias estimates
- Night time acquisitions
**Perform similar cross-calibration experiment**
- Data processed from INPE
- Data processed from CRESDA
- Same datasets processed at INPE and CRESDA
- Temporal scale (image pairs from 2003-2005)
**Perform joint field Vicarious calibration campaign**

## Overview of the IRS-P6 SensorsCross Calibration of the L7 ETM+ and L5 TM with the IRS-P6 AWiFS and LISS-III Sensors

## Resourcesat-1 (IRS P6)

**The RESOURCSAT-1 satellite was launched in to the polar sun-synchronous orbit (altitude of 817 km) by PSLV-C5 launch vehicle on October 17, 2003 with a design life of 5 years**
**RESOURCSAT-1 is also called IRS-P6 **
- Most advanced Remote Sensing Satellite built by ISRO
- Tenth satellite of ISRO in IRS series
- Other ISRO operational satellites are IRS 1-C, IRS 1-D, IRS P-2, IRS P-3

## ResourceSat-1 Overview

**RESOURCESAT-1 carries three sensors**
- High Resolution Linear Imaging Self-Scanner **(LISS-IV)**
- Medium Resolution Linear Imaging Self-Scanner **(LISS-III)**
- Advanced Wide Field Sensor **(AWiFS)**
**All three cameras are “push broom” scanners using linear arrays of CCDs**
**RESOURCESAT-1 also carries an On-board Solid State Recorder (OBSSR) with a capacity of 120 Giga-Bits to store the images**

## Slide 39

## Advanced Wide Field Sensor (AWiFS)

**The AWiFS with twin cameras is a moderate-resolution sensor offering a GSD of 56m at nadir**
**Quantization: 10 bits**
**Combined ground swath is 740km with five day repeat cycle**
**Operates in four spectral bands – three VNIR one SWIR**

**VITAL FACTS:**
**Instrument: Pushbroom**
**Bands (4): 0.52-0.59, 0.62-0.68, 0.77-0.86, 1.55-1.70 μm**
**Spatial Resolution: 56 m (near nadir), 70 m (near edge)**
**Radiometric Resolution: 10 bit**
**Swath: 740 km**
**Repeat Time: 5 days**
**Design Life: 5 years**

## AWiFS Sensor Collection Mode

**The AWiFS camera is split into two separate electro-optic modules (AWiFS-A and AWiFS-B) tilted by 11.94 degrees with respect to nadir**

## Medium Resolution Linear Imaging Self-Scanner (LISS-III)

**Medium Resolution Linear Imaging Self-Scanner (LISS-III)**

**The LISS-III is a medium resolution sensor offering a GSD of 23.5m **
**Quantization: 7 bits (SWIR band 10 bits – selected 7 transmitted)**
**Ground swath is 141 km with 24 day repeat cycle**
**Operates in four spectral bands - three VNIR one SWIR**
**Each band consists of a separate lens assembly & linear array CCD**
- The VNIR bands use a 6000 element CCD with pixel size 10x7 microns
- The SWIR band uses a 6000 element CCD with pixel size 13x13 microns
- The data from the VNIR bands are digitized to 7 bits while the data from SWIR band are digitized to 10 bit
- The VNIR bands could be operated in any one of the four selectable gains by command, while the SWIR band is configured with single gain setting covering the full dynamic range

## IRS-P6 Sensor Specifications

## Relative Spectral Response (RSR) Profiles

**Notes:**
Band 5 RSR was incomplete.  Now have full RSR curve.

## Conversion to Radiance

- L* = _(Lmax-Lmin) _Qcal + Lmin
- 		    Qcalmax
**Where**
**L* = spectral radiance at the sensors aperture W/(m****2****.sr.um)**
**Qcal = Calibrated Digital Number**
**Qcalmax = maximum possible DN value**
- 255 for LISS-IV & LISS-III products,
- 1023 for 10-bit AWiFS and 255 for 8-bit AWiFS products
**Lmax & Lmin = scaled spectral radiance (provided in the header file)**
**For GeoTIFF products, these values are found in the Image Description field of the GeoTIFF header**
**For Fast Format products, values are in the HEADER.DAT **
**For LGSOWG products, values are in the leader file**

**Notes:**
Equation Lmax Lmin is in headre info

## Header File Information (Lmax & Lmin)

**LISS-IV Mono Band 3:**
-  On board gain number for band 3 ......................... 3
-  Minimum / maximum radiance for band 3 [mw/cm2/str/um] ...  0.00000   9.92230
**LISS-III:**
-  On board gain number for band 2 ......................... 3
-  On board gain number for band 3 ......................... 3
-  On board gain number for band 4 ......................... 3
-  On board gain number for band 5 ......................... 2
-  Minimum / maximum radiance for band 2 [mw/cm2/str/um] ...  0.00000  12.06400
-  Minimum / maximum radiance for band 3 [mw/cm2/str/um] ...  0.00000  15.13100
-  Minimum / maximum radiance for band 4 [mw/cm2/str/um] ...  0.00000  15.75700
-  Minimum / maximum radiance for band 5 [mw/cm2/str/um] ...  0.00000   3.39700
-  **AWiFS-A camera (A&C quadrant scenes):**
-  On board gain number for band 2 ......................... 8
-  On board gain number for band 3 ......................... 9
-  On board gain number for band 4 ......................... 8
-  On board gain number for band 5 ......................... 9
-  Minimum / maximum radiance for band 2 [mw/cm2/str/um] ...  0.00000  52.34000
-  Minimum / maximum radiance for band 3 [mw/cm2/str/um] ...  0.00000  40.75000
-  Minimum / maximum radiance for band 4 [mw/cm2/str/um] ...  0.00000  28.42500
-  Minimum / maximum radiance for band 5 [mw/cm2/str/um] ...  0.00000   4.64500
-  **AWiFS-B camera (B&D quadrant scenes):**
-  On board gain number for band 2 ......................... 8
-  On board gain number for band 3 ......................... 9
-  On board gain number for band 4 ......................... 8
-  On board gain number for band 5 ......................... 9
-  Minimum / maximum radiance for band 2 [mw/cm2/str/um] ...  0.00000  52.34000
-  Minimum / maximum radiance for band 3 [mw/cm2/str/um] ...  0.00000  40.75000
-  Minimum / maximum radiance for band 4 [mw/cm2/str/um] ...  0.00000  28.42500
-  Minimum / maximum radiance for band 5 [mw/cm2/str/um] ...  0.00000   4.64500

**Notes:**
Liss III data is 8bit.  Qcalmax is 255.
AwiFs can be 8 or 10 bit.  10 bit Qcalmax is 1023.

## Cross-Calibration Methodology

**Co-incident image pairs from the two sensors were compared**
**The cross-cal was performed using image statistics from large common areas observed by the two sensors**
- Define Regions of Interest over identical homogenous regions
- Calculate the mean and standard deviation of the ROIs
- Convert the satellite DN to reflectance
**Perform a linear fit between the satellites to calculate the cross-calibration gain and bias**

## Image boundaries of scenes used

## Comparison Scenes Used -- Mesa, AZ

| Mesa, Arizona collection, June 29, 2005
 |  |  |  |  |
| --- | --- | --- | --- | --- |
| Instrument | Product ID | Path | Row | Solar Elevation |
| Landsat 7 ETM+ | L71036035_03520050629 | 36 | 35 | 65.21 ° |
| Landsat 7 ETM+ | L71036036_03620050629 | 36 | 36 | 65.53 ° |
| Landsat 7 ETM+ | L71036037_03720050629 | 36 | 37 | 65.77 ° |
| Landsat 7 ETM+ | L71036038_03820050629 | 36 | 38 | 65.94 ° |
| Landsat 7 ETM+ | L71036039_03920050629 | 36 | 39 | 66.02 ° |
| AWiFS Quad A | AW257047A001 | 257 | 47 | 69.50 ° |
| AWiFS Quad B | AW257047B001 | 257 | 47 | 72.60 ° |
| AWiFS Quad C | AW257047C001 | 257 | 47 | 70.30 ° |
| AWiFS Quad D | AW257047D001 | 257 | 47 | 73.60 ° |
| LISS-III | L32570470101 | 257 | 47 | 71.48 ° |

## Comparison Scenes Used -- SLC, UT

| Salt Lake City, Utah collection, June 19, 2005
 |  |  |  |  |
| --- | --- | --- | --- | --- |
| Instrument | Product ID | Path | Row | Solar Elevation |
| Landsat 5 TM | LT5038030000517010 | 38 | 30 | 62.95 ° |
| Landsat 5 TM | LT5038031000517010 | 38 | 31 | 63.59 ° |
| Landsat 5 TM | LT5038032000517010 | 38 | 32 | 64.18 ° |
| AWiFS Quad A | 000010491201 | 255 | 40 | 65.50 ° |
| AWiFS Quad B | 000010491301 | 255 | 40 | 68.10 ° |
| AWiFS Quad C | 000010491401 | 255 | 40 | 67.50 ° |
| AWiFS Quad D | 000010491501 | 255 | 40 | 70.30 ° |
| LISS-III | 000010491601 | 255 | 41 | 68.64 ° |

## Regions of Interest (ROI)

**Regions of Interest (ROI)**

**ROI were selected in both AWiFS and Landsat data**
**Mesa, AZ collection --**
- Five WRS-2 L7 scenes
- 27 ROIs
**SLC, UT collection --**
- Three WRS-2 L5 scenes
- 34 ROIs
**All AWiFS quadrants were represented in both collections**
**ROIS were selected over homogenous regions (standard deviation < 10 DN)**
**Gaps in L7 data were discarded**

- AWIFS

- L5

- L7

- AWIFS

## Band 2 Reflectance

**Band 2 Reflectance**
- Gain	1.0001
- Bias	0.0036
- R2	0.9957

**Band 3 Reflectance**
- Gain	0.9454
- Bias	-0.0005
- R2	0.9968

**Band 4 Reflectance**
- Gain	0.9541
- Bias	0.0018
- R2	0.9974

**Band 5 Reflectance**
- Gain	0.9634
- Bias	0.0261
- R2	0.9944

**Band 2 Reflectance**
- Gain	0.9127
- Bias	0.0127
- R2	0.9919

**Band 3 Reflectance**
- Gain	0.9787
- Bias	0.0029
- R2	0.9932

**Band 4 Reflectance**
- Gain	1.0159
- Bias	0.0061
- R2	0.9989

**Band 5 Reflectance**
- Gain	1.0989
- Bias	0.0036
- R2	0.9992

**Band 2 Reflectance**
- Gain	1.1642
- Bias	0.0015
- R2	0.9979

**Band 3 Reflectance**
- Gain	1.0553
- Bias	-0.0028
- R2	0.9990

**Band 4 Reflectance**
- Gain	1.0283
- Bias	-0.0032
- R2	0.9997

**Band 5 Reflectance**
- Gain	1.0290
- Bias	-0.0045
- R2	0.9984

## Band 2 Reflectance

**Band 2 Reflectance**
- Gain	0.9008
- Bias	-0.0034
- R2	0.9771

**Band 3 Reflectance**
- Gain	0.9296
- Bias	-0.0167
- R2	0.9887

**Band 4 Reflectance**
- Gain	0.8834
- Bias	-0.0203
- R2	0.9942

**Band 5 Reflectance**
- Gain	0.8927
- Bias	-0.0198
- R2	0.9942

**Band 2 Reflectance**
- Gain	0.8778
- Bias	0.0099
- R2	0.9993

**Band 3 Reflectance**
- Gain	0.8847
- Bias	0.0079
- R2	0.9995

**Band 4 Reflectance**
- Gain	0.8968
- Bias	0.0132
- R2	0.9997

**Band 5 Reflectance**
- Gain	0.9228
- Bias	0.0426
- R2	0.9973

**Band 2 Reflectance**
- Gain	1.1144
- Bias	0.0069
- R2	0.9980

**Band 3 Reflectance**
- Gain	1.0366
- Bias	-0.0006
- R2	0.9981

**Band 4 Reflectance**
- Gain	1.0361
- Bias	-0.0040
- R2	0.9998

**Band 5 Reflectance**
- Gain	1.0048
- Bias	0.0078
- R2	0.9976

## Cross-Cal Summary

**An initial cross calibration of the L7 ETM+ and L5 TM with the IRS-P6 AWiFS and LISS-III Sensors was performed**
**The approach involved calibration of nearly simultaneous surface observations based on image statistics from areas observed simultaneously by the two sensors **
**The results from the cross calibration are summarized in the table below**
- The IRS-P6 sensors are within 5.5% of each other in all bands except Band 2 (16.4% difference)
- Differences due to the Relative Spectral Responses (RSR) were not taken into account
- Atmospheric changes between the two image-pairs were not accounted
- acquisition time between the two sensors were 30-min apart
- Registration problems while selecting the regions of interest (ROI)

|  | ETM+ | TM | AWiFS | LISS-III |
| --- | --- | --- | --- | --- |
| ETM+ |  | - | 8-12% | 8-13% |
| TM | - |  | 0-6% | 2-10% |
| AWiFS | 8-12% | 0-6% |  | 1-16% |
| LISS-III | 8-13% | 2-10% | 1-16% |  |

**Differences between Sensors**

| Sensor | Band |  |  |  |
| --- | --- | --- | --- | --- |
|  | 2 | 3 | 4 | 5 |
| L5 | 1.00 | 1.06 | 1.05 | 1.04 |
| L7 | 1.11 | 1.08 | 1.13 | 1.12 |
| AWiFS | 1.00 | 1.00 | 1.00 | 1.00 |
| LISS-III (Mesa) | 0.90 | 0.96 | 0.97 | 1.00 |
| LISS-III (SLC) | 0.86 | 0.95 | 0.97 | 0.97 |

**Cross-calibration results normalized to the AWiFS sensor**

**Notes:**
One 8 bit and one 10 bit scene.
Mesa is 10 bit.  SLC is a 8 bit scene.

## LDGST Qs

## Landsat Data Gap Studies: Summary

## June 10-20, 2006 

**NASA/USGS LDSGT technical group with Dr. Navalgund, the director of ISRO SAC, Ahmedabad, India**

**NASA/USGS LDSGT technical group at IRSO HQ in Bangalore, India**

**June 10-20, 2006 **

## Oct 23-26, 2006 

**NASA/USGS technical group with Dr. Camara, the director of INPE, Brazil**

**USGS Deputy Director and NASA Program Executive with INPE Director**

**Oct 23-26, 2006 **

## AWiFS USDA Data Holdings

## CEOS Calibration-Validation Sites

**World-wide Cal/Val Sites for**
- Monitoring various sensors
- Cross calibration
- Integrated science applications
**Prime Sites for data collection**
- Site description
- Surface Measurements
- FTP access via Cal/Val portals

**Landsat Super sites**

**ALOS Cal/Val sites**

**African Desert Sites**

## USGS Recommendations to CEOS

**Coordinate and provide world-wide Cal/Val sites**
- Coordinate and provide ground control points
- Coordinate and plan vicarious calibration field campaigns
**Maintain a fully accessible Cal/Val portal to provide**
- instrument characteristics of current & future systems,
- seamless access of Cal/Val site data for users
- database of in-situ data, documentation of best practices
- Info regarding co-incident imagery
**Reinvigorate IVOS subgroup**
- Workshop at ESA ESTEC (2004) was a great success!
- Coordinate and schedule regular communication between IVOS sub-group members
- Members provide monthly Cal/Val Status on action items
**Update CEOS WGCV IVOS web pages with membership information, IVOS presentations, and technical links**

## On-going Cross-cal work at USGS

**L7 ETM+ and L5 TM sensor**
**L5 TM and L4 TM sensor**
**L7 ETM+ (L5 TM) and EO-1 ALI sensor**
**L7 ETM+ (L5 TM) and Terra MODIS and ASTER sensors**
**L7 ETM+ (L5 TM) and CBERS-2 CCD sensor**
**L7 ETM+ (L5 TM) and IRS-P6 AWiFS and LISS-III sensor**
**L7 ETM+ (L5 TM) and ALOS AVNIR-2 sensor**
**L7 ETM+ (L5 TM) and DMC SurreySat**

## Joint Agency Commercial Imagery Evaluation (JACIE) Team

**JACIE team formed in 2000 - NASA, NGA, USGS (added USDA this year!)**
**USGS is chair of JACIE; preparing to host 6****th**** Annual Conference on March 20-22, 2007 in Fairfax, VA **
_**[http://www.usm.edu/ncpc/jacie/index.html](http://www.usm.edu/ncpc/jacie/index.html)**_
**Demonstrate relevance of JACIE to US role in terrestrial monitoring**
**Enhanced scope to Satellite & Aerial sensors useful to the remote sensing community – U.S. and International systems**
**Provide imagery users with an independent assessment with respect to product quality and usability**
**Support new applications and understanding of remotely sensed data**
**Provides government/industry communication/cooperation model **

## NLCD Viability Sample test - Salt Lake Land Cover, AWiFS, LISS-III & L5 Combined - 2006

- Landsat 5 was markedly better than AWiFS/LISS-III with these classes: evergreen,
- shrub/scrub, woody wetlands,  emergent wetlands.
- Landcover class differences most likely due to lack of Bands 1&7 on IRS-P6.
- AWiFS temporal benefits are exceptional.
- Experimental results w/limited data – more testing required!

## Multiple Satellites Used in Science

**2006 Data included:**
- Landsat-5
- Landsat-7
- EO-1 ALI
- EO-1 Hyperion
- ASTER
- IRS AWiFS
- IRS LISS-III
- Surrey DMC
- DG Quickbird
**To support Sagebrush study in Wyoming, USA**

**Notes:**
This shows the approximate footprints of data used by Collin Homer & Mike Coan in their study of sagebrush cover in Wyoming.  In some cases more than one instance of the each particular scene was collected.  Note that the Quickbird collects, due to their relatively small footprint, only show up as small square “dots” at this scale, they are hard to see. The Quickbird footprints also have been cut back to the size of a quarter-quad, reducing them to about one-fourth the footprint of a full QB scene.

## The result is three scales of models, grounded to field measurements

- Landsat TM (30m)

- Quickbird (2.4m)

- IRS AWIFS (56m)

- Proposed products include models of
- % shrub, % sagebrush,
- % herbaceous, % bare ground, % litter,
- shrub height, and % shrub species

**Notes:**
This shows sample imagery from three sensors, Quickbird, TM, and AWiFS and illustrates their respective resolution. 

## LDGST Information Resources

**Briefing Slides – current presentation**
**DCWG Slides – available**
**DMC Report – bring finalized for JACIE**
**ResourceSat report – technical report completed, waiting for combined report – est. availability Feb 07**
**CBERS report - technical report completed, waiting for combined report – est. availability Feb 07**
**LDGST Qs Answers**
**ISRO trip report - complete**
**INPE trip report – being finalized**

## Characterization & Data Gap Summary

- There are many instruments providing image data for civil science purposes
- GEOSS, GEO, CEOS, Future of Land Imaging Team, LDGST
- Some instruments may be able to meet _at least some_ of the Landsat user community needs
- Technical advances have enabled the creation of many multi-spectral satellites
- 20+ countries medium to high resolution satellites and 66 Civil Land Imaging Satellites by 2010
- All the data has value but it needs to be well understood
- Calibration/Validation required
- Stable base mission (LANDSAT/LDCM) with cross band coverage
- USGS continues to assess Landsat Data Gap mission and future technologies
- USGS is interested in datasets for assessment purposes, please contact USGS if interested
- Precise high resolution data provides a great compliment to global science assessment and is a must for ER

## LDGST Summary

**There is no substitute for Landsat**
- Single source of systematic, global land observations
- Alternate sources may _reduce the impact of a Landsat data gap_
**We are characterizing  multiple systems to understand which  data sets may be compatible with the Landsat data record and can potentially supplement the Landsat data archive, **_**but no decisions have been made yet**_
**Landsat Data Gap Study Team will:**
- Finalize recommendations and strategy for implementation
- Present findings to U.S. civil agency management and the White House Office of Space and Technology Policy
- Implement recommendations