NASA/TMm2000-209891, Vol. 103

Technical Report Series on the

Boreal Ecosystem-Atmosphere Study (BOREAS)

Forrest G. Hall, Editor

Volume 103

BOREAS Level-4c AVHRR-LAC Ten-Day

Composite Images: Surface Parameters

Josef Cihlar and Jing Chen, Canada Centre for Remote Sensing, Ottawa, Ontario, Canada

Jaime Nickeson and Jeffrey A. Newcomer, Raytheon ITSS, NASA Goddard Space Flight Center,

Greenbelt, Maryland

Fengting Huang, Canada Centre for Remote Sensing, Ottawa, Ontario, Canada

National Aeronautics and

Space Administration

Goddard Space Flight Center

Greenbelt, Maryland 20771

September 2000

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NASA/TMm2000-209891, Vol. 103

Technical Report Series on the

Boreal Ecosystem-Atmosphere Study (BOREAS)

Forrest G. Hall, Editor

Volume 103

BOREAS Level-4c AVHRR-LAC Ten-Day

Composite Images: Surface Parameters

Josef Cihlar and Jing Chen, Canada Centre for Remote Sensing, Ottawa, Ontario, Canada

Jaime Nickeson and Jeffrey A. Newcomer, Raytheon ITSS, NASA Goddard Space Flight Center,

Greenbelt, Maryland

Fengting Huang, Canada Centre for Remote Sensing, Ottawa, Ontario, Canada

National Aeronautics and

Space Administration

Goddard Space Flight Center

Greenbelt, Maryland 20771

September 2000
NASA Center for AeroSpace Information

7121 Standard Drive

Hanover, MD 21076-1320

Price Code: A17

Available from:

National Technical Information Service

5285 Port Royal Road

Springfield, VA 22161

Price Code: A10
BOREAS Level-4c AVHRR-LAC Ten-Day Composite Images: Surface

Parameters

Josef Cihlar, Jing Chen, Jaime Nickeson, Jeffrey A. Newcomer, Fengting Huang

Summary

The BOREAS Staff Science Satellite Data Acquisition Program focused on providing the research

teams with the remotely sensed satellite data products they needed to compare and spatially extend

point results. MRSC and BORIS personnel acquired, processed, and archived data from the AVHRR

instruments on the NOAA-11 and -14 satellites. The AVHRR data were acquired by CCRS and were

provided to BORIS for use by BOREAS researchers. These AVHRR level-4c data are gridded, 10-day

composites of surface parameters produced from sets of single-day images. Temporally, the 10-day

compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire

BOREAS region. The data are stored in binary image format files.

Note: that some of the data files on the BOREAS CD-ROMs have been compressed using the

Gzip program. See section 8.2 for details.

Table of Contents

1) Data Set Overview

2) Investigator(s)

3) Theory of Measurements

4) Equipment

5) Data Acquisition Methods

6) Observations

7) Data Description

8) Data Organization

9) Data Manipulations

10) Errors

11) Notes

12) Application of the Data Set

13) Future Modifications and Plans

14) Software

15) Data Access

16) Output Products and Availability

17) References

18) Glossary of Terms

19) List of Acronyms

20) Document Information

1. Data Set Overview

1.1 Data Set Identification

BOREAS Level-4c AVHRR-LAC Ten-Day Composite Images: Surface Parameters

1.2 Data Set Introduction

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science effort covered those activities

that were BOREAS community-level activities or required uniform data collection procedures across

sites and time. These activities included the acquisition of the relevant satellite data. Data from the

Advanced Very High Resolution Radiometer (AVHRR) instruments on the National Oceanic and

Atmospheric Administration (NOAA)-9, -11, -12, and -14 satellites were acquired by the Canada

Centre for Remote Sensing (CCRS) and provided for use by BOREAS researchers.

Page 1
1.3 Objective/Purpose

For BOREAS, the level-4c 10-day composite AVHRR-Local Area Coverage (LAC) image

product, along with the other remotely sensed images, was prepared to provide spatially extensive

information over the BOREAS region at varying spatial scales. This information includes detailed land

cover and biophysical parameter maps such as Fraction of Photosynthetically Active Radiation

(FPAR), surface reflectance, surface temperature, and Leaf Area Index (LAI). The CCRS processed

the level-4c 10-day composite AVHRR-LAC imagery products.

1.4 Summary of Parameters

The level-4c composite AVHRR-LAC data in the BOREAS Information System (BORIS) contain

the following parameters: image header and compositing information; geographic position information:

view, solar zenith, and relative azimuth angle information; surface reflectance and temperature;

Normalized Difference Vegetation Index (NDVI); and missing data, cloud contamination, and water

masks.

1.5 Discussion

The level-4c product is based on level-4b, which is further processed to remove or mitigate some

artifacts caused by the input data or the compositing process. The artifacts of concern are atmospheric

contamination and bidirectional reflectance effects for AVHRR channels 1 and 2, and atmospheric and

surface emissivity effects for AVHRR channel 4. The processing was carried out at CCRS using

specifically designed software and procedures (see Section 9 for details). The spatial and temporal

coverage of the level-4c product is identical to that of the level-4b product.

1.6 Related Data Sets

BOREAS Level-3b AVHRR-LAC Imagery: Scaled At-sensor Radiance in LGSOWG Format

BOREAS Level-4b AVHRR-LAC Ten-Day Composite Images: At-sensor Radiance

2. Investigator(s)

2.1 Investigator(s) Name and Title

Josef Cihlar

Canada Centre for Remote Sensing

2.2 Title of Investigation

BOREAS Staff Science Satellite Data Acquisition Program

2.3 Contact Information

Contact 1:

Josef Cihlar

Canada Centre for Remote Sensing

588 Booth Street, 4th Floor

Ottawa, Ontario

K1AOY7 Canada

(613) 947-1265

(613) 947-1406 (fax)

Josef.Cihlar@geocan.emr.ca

Page 2
Contact 2:

Jaime Nickeson

Raytheon ITSS

NASA GSFC

Code 923

Greenbelt, MD 20771

(301) 286-3373

(301) 286-0239 (fax)

Jaime.Nickeson@ gsfc.nasa.gov

3. Theory of Measurements

The AVHRR is a four- or five-channel scanning radiometer capable of providing global daytime and

nighttime information about ice, snow, vegetation, clouds, and the sea surface. These data are obtained

on a daily basis primarily for use in weather analysis and forecasting; however, a variety of other

applications are possible. The AVHRR-LAC data collected for the BOREAS project were from

instruments onboard NOAA-9, - 11, and - 12 polar orbiting platforms. The radiometers measured

emitted and reflected radiation in the visible, near-infrared, one middle-infrared, and one or two

thermal channels.

The primary use of each channel and the spectral regions and bandwidths on the respective NOAA

platforms are given in the following tables:

Channel Wavelength [_m] Primary Use

i* 0.57 - 0.69

2 0.72 - 0.98

3 3.52 - 3.95

4** 10.3

5*** 11.4

- 11.4

- 12.4

Daytime Cloud and Surface Mapping

Surface Water Delineation, Vegetation Cover

Sea Surface Temperature (SST), Nighttime

Cloud Mapping

Surface Temperature, Day/Night Cloud Mapping

Surface Temperature

* Channel 1 wavelength for the Television and Infrared Observation Satellite

(TIROS)-N flight model was 0.55-0.90 micrometers.

** For NOAA-7 and -9, channel 4 was 10.3-11.3 micrometers.

*** For TIROS-N, NOAA-6, -8, -i0, and -12, channel 5 duplicates channel 4.

The wavelength ranges at 50% relative spectral response (in micrometers) of the bands for the

platform-specific instruments are:

Band NOAA-9 NOAA-II NOAA-12 NOAA-14

1 0.570 - 0.699 0.572 - 0.698

2 0.714 - 0.983 0.716 - 0.985

3 3.525 - 3.931 3.536 - 3.935

4 10.334 - 11.252 10.338 - 11.287

5 11.395 - 12.342 11.408 - 12.386

0 571 -

0 724 -

3 554 -

i0 601 -

i0 601 -

0.684 0.570 - 0.699

0.984 0.714 - 0.983

3.950 3.525 - 3.931

11.445 10.330 - 11.250

11.445 11.390 - 12.340

The AVHRR is capable of operating in both real-time and recorded modes. Direct readout data were

transmitted to ground stations of the automatic picture transmission (APT) class at low resolution (4 x

4 km) and to ground stations of the high-resolution picture transmission (HRPT) class at high

resolution (1 x 1 km). AVHRR HRPT data were received for the BOREAS region by the CCRS

Prince Albert Satellite Station (PASS).

Page 3
4. Equipment

4.1 Sensor/Instrument Description

The AVHRR is a cross-track scanning system featuring one visible, one near-infrared, one

middle-infrared, and two thermal channels. The analog data output from the sensors is digitized

onboard the satellite at a rate of 39,936 samples per second per channel. Each sample step corresponds

to an angle of scanner rotation of 0.95 milliradians. At this sampling rate, there are 1.362 samples per

instantaneous field of view (IFOV). A total of 2,048 samples is obtained per channel per Earth scan,

which spans an angle of +/-55.4 degrees from nadir.

4.1.1 Collection Environment

The NOAA satellites orbit Earth at an altitude of 833 kin. From this space platform, the data are

transmitted to a ground receiving station.

4.1.2 Source/Platform

Launch and available dates for the TIROS-N series of satellites from CCRS are:

Satellite Launch Date Date Range

TIROS-N 13-Oct-1978 19-Oct-1978 to 30-Jan-1980

NOAA-6 27-Jun-1979 21-Aug-1984 to 23-Jan-1986

NOAA-B 29-May-1980 Failed to achieve orbit

NOAA-7 23-Jun-1981 24-Jui-1983 to 30-Dec-1984

NOAA-8 28-Mar-1983 24-Jui-1983 to 13-Aug-1985

NOAA-9 12-Dec-1984 16-Sep-1985 to 19-Mar-1995

NOAA-10 17-Sep-1986 ii-Oct-1986 to 15-Nov-1993

NOAA-II 24-Sep-1988 28-Jun-1989 to 13-Sep-1994

NOAA-12 14-May-1991 ll-Aug-1993 to present

NOAA-14 30-Dec-1994 15-May-1995 to present

AVHRR-LAC data used in BOREAS were collected onboard the NOAA-9, -11, and -12 polar orbiting

platforms. Only NOAA-11 and -14 data were processed as level-4c products.

4.1.3 Source/Platform Mission Objectives

The AVHRR is designed for multispectral analysis of meteorologic, oceanographic, and

hydrologic parameters. The objective of the instrument is to provide radiance data for investigation of

clouds, land water boundaries, snow and ice extent, ice or snow melt inception, day and night cloud

distribution, temperatures of radiating surfaces, and SST. It is an integral member of the payload on

the advanced TIROS-N spacecraft and its successors in the NOAA series, and as such contributes data

required to meet a number of operational and research-oriented meteorological objectives.

4.1.4 Key Variables

Emitted radiation, reflected radiation.

4.1.5 Principles of Operation

The AVHRR is a four- or five-channel scanning radiometer that detects emitted and reflected

radiation from Earth in the visible, near-, middle-, and thermal-infrared regions of the electromagnetic

spectrum. A fifth channel was added to the follow-on instrument designated AVHRR/2 and flown on

NOAA-7, -9, -11, and -14 to improve the correction for atmospheric water vapor. Scanning is

provided by an elliptical beryllium mirror rotating at 360 rpm about an axis parallel to that of Earth. A

two-stage radiant cooler is used to maintain a constant temperature for the infrared detectors of 95 K.

The operating temperature is selectable at either 105 or 110 K. The telescope is an 8-inch afocal,

all-reflective Cassegrain system. Polarization is less than 10 percent. Instrument operation is controlled

by 26 commands and monitored by 20 analog housekeeping parameters.

Page 4
4.1.6 Sensor/Instrument Measurement Geometry

The AVHRR is a cross-track scanning system. The IFOV of each sensor is approximately 1.4

milliradians, giving a spatial resolution of 1.1 km at the satellite subpoint. There is about a 36-percent

overlap between IFOVs (1.362 samples per IFOV). The scanning rate of the AVHRR is six scans per

second, and each scan spans an angle of +/55.4 degrees from the nadir.

4.1.7 Manufacturer of Sensor/Instrument

Not available at this revision.

4.2 Calibration

The thermal-infrared channels are calibrated in-flight using a view of a stable blackbody and space

as a reference. No in-flight visible channel calibration is performed. Channel 3 data are noisy because

of a spacecraft problem and may not be usable, especially when the satellite is in daylight (Kidwell,

1991).

4.2.1 Specifications

IFOV 1.4 mrad

RESOLUTION i.i km

ALTITUDE 833 km

SCAN RATE 360 scans/min

SCAN RANGE -55.4 to 55.4

SAMPLES/SCAN 2,048 samples

(1.362 samples per IFOV)

degrees

per channel per Earth scan

4.2.1.1 Tolerance

The AVHRR infrared channels were designed for a Noise Equivalent Differential Temperature

(NEdT) of 0.12 K (at 300 K) and a signal-to-noise ratio of 3:1 at 0.5-percent albedo.

4.2.2 Frequency of Calibration

The Naval Research Laboratory's (NRL's) TIROS-N calibration overlay performs the calibration

on blocks of telemetry data. For LAC/HRPT acquisitions, a block consists of 20 scan lines.

Calibration begins by reading the calibration parameters into memory. For each scan line of telemetry

in a block, the following process takes place:

• Telemetry data are extracted and unpacked.

• Ramp calibration data for each of the five channels are decommutated.

• A single Platinum Resistor Thermometer (PRT) count is extracted.

• Ten samples of internal target, or blackbody, data are decommutated and filtered.

• Ten samples of space view data are decommutated and filtered.

After the entire block has been decommutated, the PRTs are checked for pattern correctness. A valid

PRT pattern consists of a PRT reference count whose value is less than 10 followed by four PRT

counts whose values are greater than 10. After decommutation, the PRT counts are filtered, and the

mean and standard deviation of each PRT are computed. The mean PRT counts are then converted to

temperature using the formula:

T(1) : C(0) + C(1)M(j) + C(2)[M(j)2] + C(3)[M(j)3] + C(4)[M(j)4]

where: T(1) = the temperature of each of the four PRTs

C(i) = the PRT coefficients from CPIDS

M(j) = the mean count of each of the four PRTs

The mean of the four PRT temperatures is then computed to get the temperature of the blackbody. The

blackbody temperature is used to calculate the index of the temperature-to-radiance lookup table using

the formula:

Page 5
INDEX = 10.0* PRTTEMPERATURE1798.5

Theblackbodyradiancesforinfraredchannelsareextractedfrom thetable,whichwasgeneratedfrom

CPIDS.Fromthedecommutatedblackbodydata,themeanandstandarddeviationof theinternaltarget

arecomputed.Thiscomputationis alsodonefor themeanandstandarddeviationof spaceview data.

Theslopesandinterceptsarethencalculatedusingthepreviouslycomputeddata.Theslopeand

interceptfor thevisiblechannelsareassignedconstants.Foreachof theinfraredchannels,theslope

andinterceptarecalculatedusingtheformula:

SPACEVIEWRADIANCE- BLACKBODY RADIANCE

SLOPE......................................................................

SPACEVIEWMEAN - BLACKBODY MEAN

INTERCEPT= SPACEVIEWRADIANCESLOPE* SPACEVIEWMEAN

Theslopesandinterceptsfor all five channelsarethenstoredin eachscanline in thegivenblock.The

calibrationoverlaythenbeginsthisprocessagainforthenextblock.Thefinal functionof the

calibrationoverlayis to determineramplinearityornonlinearity.Thisprocessreversestherampon

infraredchannelsfrom descendingto ascending.Therampvaluesarethenadjustedaccordingto data

type(i.e.,LAC or GlobalAreaCoverage[GAC]).

4.2.3 Other Calibration Information

None given.

5. Data Acquisition Methods

The BOREAS level-4c AVHRR-LAC images were acquired through the CCRS. Some radiometric

corrections along with geometric corrections are applied to produce the imagery in a spatially corrected

form (Lambert Conformal Conic [LCC] projection). A full level-4c AVHRR-LAC image contains

approximately 1,200 pixels in each of approximately 1,200 lines. Before any geometric corrections,

the ground resolution ranges from 1.1 km at nadir to 2.5 km x 6.8 km at the scanning extremes. Each

pixel value is stored in a 2-byte field starting with level-4b products. The level-4c images were

processed through software developed at CCRS. The raw data are available from the CCRS PASS.

6.1 Data Notes

None.

6.2 Field Notes

None.

6. Observations

Page 6
7. Data Description

7.1 Spatial Characteristics

7.1.1 Spatial Coverage

The AVHRR provides a global (pole-to-pole) onboard collection of data from all spectral channels.

The 110.8-degree scan equates to a swath 27.2 degrees in longitude (at the Equator) centered on the

subsatellite track. This swath width is greater than the 25.3-degree separation between successive

orbital tracks and provides overlapping coverage (side-lap) anywhere on the globe.

The BOREAS level-4c AVHRR-LAC images contain 1,200 pixels in each of the 1,200 lines and

cover the entire 1,000-kin x 1,000-kin BOREAS region. This includes the Northern Study Area

(NSA), the Southern Study Area (SSA), and the transect between the SSA and NSA.

The corners of the AVHRR images are:

Latitude Longitude

Northwest (i,i) 59.36395°N I15.40859°W

Northeast (1,1200) 61.01294°N 93.28553°W

Southwest (1200,1) 48.83387°N II0.25229°W

Southeast (1200,1200) 50.02993°N 93.73857°W

The northwest corner has a distance (1109.76 km west, 7900.04 km north) from the origin (95°W and

0°N) of the LCC coordinate. The pixel size is exactly 1 kin.

The North American Datum of 1983 (NAD83)

corner coordinates of the BOREAS region are

Latitude Longitude

Northwest 59.979°N III.000°W

Northeast 58.844°N 93.502°W

Southwest 51.000°N III.000°W

Southeast 50.089°N 96.970°W

The NAD83 corner coordinates of the SSA are

Latitude Longitude

Northwest 54.319°N I06.227°W

Northeast 54.223°N I04.236°W

Southwest 53.513°N I06.320°W

Southeast 53.419°N I04.368°W

The NAD83 corner coordinates of the NSA are

Latitude Longitude

Northwest 56.249°N 98.824°W

Northeast 56.083°N 97.241°W

Southwest 55.542°N 99.045°W

Southeast 55.379°N 97.489°W

7.1.2 Spatial Coverage Map

Not available.

Page 7
7.1.3 Spatial Resolution

Beforeanygeometriccorrections,thespatialresolutionvariesfrom 1.1km atnadirto

approximately2.5x 6.8km at theextremeedgesof thescan.Thelevel-4bcompositeAVHRR-LAC

imageshavehadgeometriccorrectionsappliedsothatthepixel sizeis 1km in all bands. Only data

with view zenith angles 57 degrees or less are used in the level-4c product.

7.1.4 Projection

The coordinate system is the Lambert Conformal Conic (LCC) with the two standard parallels at

49°N and 77°N, respectively, and the meridian at 95°W.

7.1.5 Grid Description

The level-4 images are projected into the LCC projection at a resolution of 1.0 km per pixel (grid

cell) in both the X and Y directions.

7.2 Temporal Characteristics

7.2.1 Temporal Coverage

Historical AVHRR-LAC data have been acquired by CCRS routinely since 1991 and are kept in

the CCRS archive. These data can be obtained by contacting CCRS. Statistics Canada also has a

historical composite data set of visible, infrared, and NDVI imagery. Contact the Statistics Canada

Crop Condition Assessment Program Office for more information.

At BOREAS latitudes, at least daily coverage is provided by a given sensor. Virtually all raw data

from daytime overpasses were recorded during the BOREAS period (NOAA-9, - 11, - 14 daytime) and

are archived at PASS. Most scenes were processed for inclusion in the level-4b and -4c products.

The overall time period of data acquisition in 1994 was from 09-Apr through 10-Sep. CCRS

acquired most AVHRR-LAC daytime images from NOAA-9, -11, and -12 for each satellite pass; i.e.,

two images in each 24-hour cycle.

7.2.2 Temporal Coverage Map

The 1994 compositing periods in this data set are as follows:

April ii - 20, 21

May 1 - i0, ii - 20, 21

June 1 - i0, ii - 20, 21

July 1 - i0, ii - 20, 21

August 1 - i0, ii - 20, 21

September 1 - i0

- 30

- 31

- 30

- 31

- 30

7.2.3 Temporal Resolution

AVHRR-LAC data used in the creation of the level-4c composite products were daytime images

(afternoon passes). Most useful daily images (i.e., those containing some clear-sky regions) are used

to produce the level-4b product. The daily images are composited into nominally cloud-free images

over 10-day periods.

7.3 Data Characteristics

7.3.1 Parameter/Variable

• Surface reflectance (channels 1 and 2)

• Bidirectional Reflectance Distribution Function (BRDF) (channels 1 and 2)

• NDVI (3 versions)

• Surface temperature

• Cloud mask

• Missing data mask

Page 8
7.3.2 Variable Description/Definition

Surface reflectance: After atmospheric correction, for channels 1 and 2. Based on top of the

atmosphere reflectance and the atmospheric correction program called Simplified Method for

Atmospheric Correction (SMAC) (Rahman and Dedieu, 1994).

BRDF corrected, interpolated reflectance for channels 1 and 2. Based on surface reflectance (after

atmospheric corrections) and BRDF model (channel and land cover specific). Normalized to a solar

zenith angle of 45 degrees and view zenith of 0 degrees.

NDVI: The ratio of the difference of the near-infrared and the visible bands and the sum of the two

bands [(VIS - IR) / VIS + IR)]. It is an indication of the amount and vigor of vegetation present. Three

NDVI channels have been provided:

• NDVI from BRDF corrected interpolated channel 1 and 2 reflectances

• NDVI from the Fourier-Adjustment, Solar zenith angle corrected, Interpolated, Reconstructed

(FASIR) model (final corrected, linear interpolated). This NDVI was produced using the

FASIR approach of Sellers, et al. For more information, see Cihlar, et al., 1996a.

• NDVI-smoothed FASIR product. Using a smoothing/sliding filter in a 5-day window

centered on the date of interest, the highest and lowest values are dropped and the remaining

three are averaged.

Surface temperature: Final surface temperature, interpolated, and cut at 330 K. Temperature from

channel 4 corrected for atmospheric and surface emissivity effects, with missing/cloudy pixels

interpolated. The interpolation used a 330 K cutoff to eliminate 'runaway' cases (e.g., when not

enough values were available; it assumed that the temperature would not exceed that value anywhere in

Canada).

Cloud mask: A binary image indicating location of cloud contaminated and clear pixels. Produced

with the Cloud Elimination from Composites using Albedo and NDVI Trend (CECANT) procedure,

see Cihlar, 1996.

Missing data mask: A binary image indicating location of pixels of good and missing data.

7.3.3 Unit of Measurement

• Surface reflectance and BRDF are unitless. To calculate the reflectance values from the scaled

integers provided, use reflectance = DN/1000.

• NDVI is unitless. To calculate NDVI values from the scaled integers provided, use NDVI =

(DN/10000) -1.

• Surface temperature is measured in K. To convert from scaled to actual temperatures, use

Temperature = DN/100.

• Cloud mask is unitless. This is a binary image containing values of either 0 or 255. A value of

0 is a cloudy pixel; 255 indicates a clear pixel.

• Missing data mask is unitless. This is a binary image containing values of either 0 or 255. A

values of 0 is a good pixel; 255 indicates a missing pixel.

7.3.4 Data Source

These NOAA AHVRR data were processed and provided by CCRS.

7.3.5 Data Range

No data ranges were given for any of the surface reflectance channels.

• NDVI values range between 0 and 20,000.

• NDVI corrected, linear interpolated: same as above.

• NDVI corrected, linear interpolated, smoothed: same as above.

• No data ranges were given for the surface temperature data.

• Cloud mask values are 0 or 255.

• Missing data mask values are 0 or 255.

7.4 Sample Data Record

Not applicable for image data.

Page 9
8. Data Organization

8.1 Data Granularity

The smallest unit of data for the level-4c AVHRR-LAC composite is the set of parameters for a

given compositing period.

8.2 Data Format(s)

8.2.1 Uncompressed Data Files

A single level-4c AVHRR-LAC composite image product produced by CCRS contains the

following 10 files:

File Description

i AVHRR channel i surface reflectance

2 AVHRR channel 2 surface reflectance

3 AVHRR channel 1 BRDF-corrected interpolated surface reflectance

4 AVHRR channel 2 BRDF-corrected interpolated surface reflectance

5 NDVI from channel 1,2 BRDF-corrected, interpolated surface reflectance

6 NDVI, FASIR model (final corrected, linearly interpolated)

7 NDVI, FASIR model, smoothed

8 Surface temperature, linearly interpolated

9 Cloud mask

i0 Mask of missing data

The image files contain 1,200 pixels in each of 1,200 lines. Each pixel value in files 1 through 8 is

contained in a 2-byte (16-bit) field ordered as most significant (high-order) byte first. Thus, each

image line (file record) is 2,400 bytes in length. Files 9 and 10 (the masks) for each period are

single-byte images with each line containing 1,200 bytes of data.

The images are oriented such that pixel 1, line 1 is in the upper left-hand comer (i.e., northwest) of

the screen display. Pixels and lines progress from left to right and top to bottom so that pixel n, line n

is in the lower right-hand comer.

8.2.2 Compressed CD-ROM Files

On the BOREAS CD-ROMs, the image files have been compressed with the Gzip (GNU zip)

compression program (file_name.gz). These data have been compressed using gzip version 1.2.4 and

the high compression (-9) option (Copyright (C) 1992-1993 Jean-loup Gailly). Gzip uses the

Lempel-Ziv algorithm (Welch, 1994) also used in the zip and PKZIP programs. The compressed files

may be uncompressed using gzip (with the -d option) or gunzip. Gzip is available from many Web

sites (for example, the ftp site prep.ai.mit.edu/pub/gnu/gzip-*.*) for a variety of operating systems in

both executable and source code form. Versions of the decompression software for various systems

are included on the CD-ROMs.

Page 10
9. Data Manipulations

9.1 Formulae

9.1.1 Derivation Techniques and Algorithms

Using the BOREAS level-4b AVHRR-LAC product as input, the data are processed to correct

radiometric artifacts. These include atmospheric and bidirectional effects in channels 1 and 2, and

atmospheric end emissivity effects in AVHRR channel 4. For channel 1 and 2, the atmospheric effects

of concern are absorption and scattering by cloud-free atmosphere as well as the presence of variable

amounts of clouds (full pixels or subpixel) or snow on the ground. In channel 4, atmospheric water

vapor and surface emissivity are the main effects to be corrected for. The rationale and processing

sequence are described in Cihlar, et al. (1996).

The major difference between the BOREAS level-3b product and the input data for this product is

the projection (the input data for the level-4c product are in the LCC projection). Daily level-3b

products were combined to select the most cloud-free pixel during the 10-day compositing period. By

definition, this is the pixel with the maximum NDVI value. Once a pixel is selected, it is retained in the

composite image, as are the three associated angles, NDVI, and the date when the pixel was imaged.

The level-4b data are further processed to create the level-4c data set, as described in Section 9.2.

9.2 Data Processing Sequence

The level-4c processing sequence is called Atmosphere, Bidirectional and Contamination

Corrections of CCRS (ABC3) and is described in more detail in Cihlar, et al. (1996, 1997).

9.2.1 Processing Steps

Step 1: Top-of-the-Atmosphere (TOA) reflectance

TOA reflectance for channel 1 or 2 is calculated from the corrected TOA radiance, L*(new), with

the formula given by Teillet (1992). Values of gain G and offset O were calculated with consideration

of postlannch sensor degradation (Teillet and Holben, 1994).

Step 2: Atmospheric correction of AVHRR channels 1 and 2

The SMAC algorithm was used in the processing. The processing was carried out assuming water

content of 2.3 g/cm2 and ozone content 0.319 cm-atm. A constant value of 0.05 was used for optical

depth at 550 nm. The corrections were computed on a pixel basis using solar zenith, view zenith, and

relative azimuth channels.

Step 3: Identification of contaminated pixels

A new procedure called CECANT was developed to identify the 'contaminated' pixels; i.e., pixels

where the surface vegetation or soil signal is obscured (Cihlar, 1996). The procedure is based on the

high sensitivity of NDVI to the presence of clouds, aerosol and snow. Three features of the annual

surface reflectance trend are used: the high contrast between the albedo (represented by AVHRR

channel 1) of land, especially when fully covered by green vegetation and clouds or snow/ice; the

average NDVI value (expected value for that pixel and compositing period); and the monotonic trend in

NDVI. Four thresholds are required in CECANT to identify partially contaminated pixel (i,j,t) where i

and j are pixel coordinates and t is the compositing period:

• Cl(t): the maximum channel 1 reflectance of a clear-sky, snow- or ice-free land pixel in the

data set.

• Rmin(t): the maximum acceptable deviation of the measured value NDVI(i,j,t) below the

estimated NDVIa(i,j,t).

• Rmax(t): the maximum acceptable deviation of the measured value NDVI(i,j,t) above the

estimated NDVIa(i,j,t).

• Zmax(t): the maximum acceptable deviation of the measured value NDVI(i,j,t) above the

estimated NDVImax(i,j,t).

Page 11
NDVImax(i,j,t) andNDVIa(i,j,t) werecalculatedusingtheFASIRmodelof Sellerset al.(1994),

whichapproximatestheseasonalNDVI curvewith athird-orderFouriertransform.Beforethe

computation,missingNDVI valuesbetweenfirst andlastmeasurementswerereplacedthroughlinear

interpolationafterfindingtheseasonal peakfor eachpixel, usingtherationaleandalgorithmof Cihlar

andHowarth(1994).A constantvalueof 0.30wasusedfor C1.Theupperandlowerlimits for R and

Z weredeterminedseparatelyfor eachcompositeperiodusingR andZ histograms(Cihlar,1996).

Usingthesethresholds,acloudmaskwaspreparedfor eachcompositeperiod.

Step 4: Corrections for bidirectional reflectance effects in channels 1 and 2

The model of Roujean, et al. (1992) as modified by Wu, et al. (1995) was used to characterize the

seasonal BRDF for each cover type. Land cover-dependent model coefficients were derived (Li, et al.,

1995) using a map of Canada with a pixel size of 1 km prepared with AVHRR data (Pokrant, 1991).

Only cloud-free pixels were included in the derivation of the model coefficients, and no bidirectional

corrections for snow- or ice-covered areas were made. The resulting models were used to compute

channel 1 and 2 reflectance for view zenith of 0 degrees and solar zenith of 45 degrees.

Step 5: Replacement of contaminated pixels for AVHRR channels 1 and 2

Two cases were recognized: pixels contaminated either during or at the end of the growing season.

For pixels contaminated during the growing season, the new values were found through linear

interpolation for both channels 1 and 2. At the end of the growing season, it was assumed that the

annual trajectory for individual channels as well as for NDVI could be approximated by a

second-degree polynomial. The polynomial was fitted to the plot of corrected reflectance for all

clear-sky periods, starting with the first clear-sky composite period after 1-Aug. After determining the

best fit coefficients, the new values were calculated using the polynomial coefficients to replace

contaminated pixels in each channel prior to the first clear pixel or after the last such pixel.

Step 6: NDVI processing

Because of imperfections in the bidirectional corrections of channels 1 and 2, the NDVI computed

from atmospherically corrected NDVI were also retained. However, corrections for solar zenith angle

were desirable in view of the known dependence of the NDVI on the solar zenith angle. The

coefficients of Sellers, et al. (1994) were used for the various land cover classes. The new set of

NDVI values was then computed for a reference solar zenith angle of 45 degrees based on the

equations of Sellers, et al. (1994). The NDVI values for the missing or contaminated pixels were

interpolated as in Step 5 above.

Step 7: Channel 4 correction

The modified split window method of Coll, et al. (1994) was used which accounts for both

atmospheric and surface emissivity effects. Coefficients estimating atmospheric effects were derived

by Coll, et al. (1994), alpha and beta were obtained from Figure 2 in Coll, et al.. Surface emissivity

was estimated using a log-linear relationship between NDVI and emissivity; the emissivity coefficients

were derived from literature data. The formulas and coefficients were:

Ts = T4 + (a0 + al*(T4-T5))*(T4-T5) + B(eps)

B(eps) = alpha * (1-eps4) - beta * (eps4 - eps5)

eps4 = 0.98968 + 0.0288 * ln(final_NDVI)

eps4-eps5 = 0.010185 - 0.013443 * ln(final_NDVI)

where: Ts is surface temperature.

T4, T5 are brightness temperatures TOA in AVHRR channels 4,5

eps4, eps5 are emissivities in in AVHRR channels 4 and 5

Coefficients a0 = 1.29, al = 0.28, alpha = 45 K, beta = 40 K.

Page 12
BORISstaffprocessedthedataby:

• Developingandusingsoftwareto verify thecontentof andextractneededinformationfrom

theimagefiles,

• Compressingthebinaryfiles forreleaseonCD-ROM.

9.2.2 Processing Changes

None.

9.3 Calculations

See Section 9.2.1.

9.3.1 Special Corrections/Adjustments

See Section 9.2.1.

9.3.2 Calculated Variables

See Section 9.2.1.

9.4 Graphs and Plots

None.

10. Errors

10.1 Sources of Error

The major sources of error are due to the imprecise knowledge of atmospheric conditions during

image acquisition (and thus the use of nominal values for atmospheric corrections) and imperfect

modeling of the bidirectional effects.

The level-4c product also suffers from errors in the level-3b and 4-b products (see level-3b product

documentation).

10.2 Quality Assessment

10.2.1 Data Validation by Source

Comparing the composite image data (md) with a single-date, near-nadir, cloud-free image (sd) in

midsummer, the following equations were obtained for channels 1 and 2 on a per-pixel basis (see

Cihlar et al., 1996 and 1997, for discussion):

Cl(md) = 0.04 + 0.26*Cl(sd) ; r2 =0.06, s.e. = 0.014

C2(md) = 0.09 + 0.74"C2(sd) ; r2 =0.45, s.e. = 0.04

NDVI(md) = 0.27 + 0.60*NDVI(sd); r2 =0.33, s.e. = 0.066

For 5 x 5 pixel mean values, the following relations were obtained:

Cl(md) = 0.03 + 0.48 * C1 (sd); r2 = 0.10, s.e. = 0.06

C2(md) = 0.06 + 0.90 * C2(sd); r2 = 0.69, s.e. = 0.017

NDVI(md) = 0.17 + 0.74 * NDVI (sd); r2 = 0.55, s.e. = 0.024

10.2.2 Confidence Level/Accuracy Judgment

An evaluation of the resulting data set (Cihlar et al., 1996) showed significant improvement in the

consistency and reduced noise in the data compared to level-4b. However, the level-4c data set does

not approximate a single-date image closely enough and is therefore not a sound substitute for

single-date, near-nadir images where such uncontaminated images are available and where neither

timeliness nor the multitemporal observations are required.

Page 13
10.2.3 Measurement Error for Parameters

Refer to level-3b and level-4b product specifications.

10.2.4 Additional Quality Assessments

Level-4c products are also assessed through seasonal statistics (comparison of mean values per

compositing period of various parameters); see Cihlar, et al. (1996).

10.2.5 Data Verification by Data Center

BORIS personnel viewed randomly selected images on a video display. No anomalous items were

found. In addition, BORIS personnel compressed the data files for distribution on CD-ROM.

11. Notes

11.1 Limitations of the Data

None given.

11.2 Known Problems with the Data

None.

11.3 Usage Guidance

Two primary NDVI data sets were provided to BOREAS, BRDF-corrected and FASIR approach,

because there was uncertainty about the BRDF corrections at the time. The BRDF-corrected NDVI

(produced the same way as those provided to BOREAS) is now used in BOREAS work because it

corrects for all angular effects, not just view zenith angle, and it was found to increase the NDVI

somewhat, as it should. However, there are still questions about the accuracy of the 1994

BRDF-corrected channel 1 and 2 reflectances. The very late local overpass time may have affected both

the compositing and the BRDF corrections. Because the solar zenith angle was greater than 55 degrees

in most cases and is normalized to 45 degrees, small BRDF correction errors would be magnified in

the process of deriving NDVI. Of course, these problems would affect both of the NDVI products.

Before uncompressing the Gzip files on CD-ROM, be sure that you have enough disk space to

hold the uncompressed data files. Then use the appropriate decompression program provided on the

CD-ROM for your specific system.

11.4 Other Relevant Information

None.

None given.

12. Application of the Data Set

None given.

13. Future Modifications and Plans

Page 14
14. Software

14.1 Software Description

The ABC3 software for level-4c products was written in-house using C, FORTRAN, and the

visualization package pvWave. The CECANT algorithm used software provided by S. Los from the

University of Maryland and is written in C.

BORIS staff developed software and command procedures for:

• Extracting header information from level-4c AVHRR-LAC images on tape and writing it to

American Standard Code for Information Interchange (ASCII) files on disk.

• Reading the ASCII disk file and logging the level-4c AVHRR-LAC image products into the

Oracle data base tables.

• Converting between the geographic systems of (latitude, longitude), Universal Transverse

Mercator (UTM) (northing, easting), and BOREAS (x,y) grid locations.

The software mentioned under items 1 and 2 is written in C and is operational on VAX 6410 and

MicroVAX 3100 systems at GSFC. The primary dependencies in the software are the tape input/output

(I/O) library and the Oracle data base utility routines.

The geographic coordinate conversion utility (BOR_CORD) has been tested and used on

Macintosh, IBM PC, VAX, Silicon Graphics, and Sun workstations.

Gzip (GNU zip) uses the Lempel-Ziv algorithm (Welch, 1994) used in the zip and PKZIP

commands.

14.2 Software Access

The software used by CCRS is not available for distribution, but the algorithms can be found in the

published literature.

Gzip is available from many Web sites across the Internet (for example, ftp site

prep.ai.mit.edu/pub/gnu/gzip-*.*) for a variety of operating systems in both executable and source

code form. Versions of the decompression software for various systems are included on the

CD-ROMs.

15. Data Access

The level-4c AVHRR-LAC 10-day composite images are available from the Earth Observing System

Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active

Archive Center (DAAC).

15.1 Contact Information

For BOREAS data and documentation please contact:

ORNL DAAC User Services

Oak Ridge National Laboratory

P.O. Box 2008 MS-6407

Oak Ridge, TN 37831-6407

Phone: (423) 241-3952

Fax: (423) 574-4665

E-mail: ornldaac@ornl.gov or ornl@eos.nasa.gov

15.2 Data Center Identification

Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory

(ORNL) Distributed Active Archive Center (DAAC) for Biogeochemical Dynamics

http://www-eosdis.ornl.gov/.

Page 15
15.3 Procedures for Obtaining Data

Users may obtain data directly through the ORNL DAAC online search and order system

[http://www-eosdis.ornl.gov/] and the anonymous FTP site [ftp://www-eosdis.ornl.gov/data/] or by

contacting User Services by electronic mail, telephone, fax, letter, or personal visit using the contact

information in Section 15.1.

15.4 Data Center Status/Plans

The ORNL DAAC is the primary source for BOREAS field measurement, image, GIS, and

hardcopy data products. The BOREAS CD-ROM and data referenced or listed in inventories on the

CD-ROM are available from the ORNL DAAC.

16. Output Products and Availability

16.1 Tape Products

The AVHRR-LAC HRPT level-4c data can be made available on 8-mm media.

16.2 Film Products

None.

16.3 Other Products

These data are available on the BOREAS CD-ROM series.

17. References

17.1 Platform/Sensor/Instrument/Data Processing Documentation

Buffam, A. 1994. GEOCOMP User Manual. Internal Report, Canada Centre for Remote Sensing,

Ottawa, Ontario.

Cihlar, J. 1996. Identification of contaminated pixels in AVHRR composite images for studies of land

biosphere. Remote Sensing of Environment (in press).

Cihlar, J. and J. Howarth. 1994. Detection and removal of cloud contamination from AVHRR

composite images. IEEE Transactions on Geoscience and Remote Sensing 32: 427-437.

Cihlar, J., H. Ly, Z. Li, J. Chen, H. Pokrant, and F. Huang. 1996. Multitemporal, multichannel data

sets for land biosphere studies: artifacts and corrections. Remote Sensing of Environment (in press).

Cihlar, J., J. Chen, and Z. Li, 1997. Seasonal AVHRR multichannel data sets and products for

studies of surface-atmosphere interactions. Journal of Geophysical Research

102(D24):29,625-29,640.

Coll, C., V. Caselles, J.A. Sobrino, and E. Valor. 1994. On the atmospheric dependence of the

split-window equation for land surface temperature. International Journal for Remote Sensing 15(1):

105-122.

Kidwell, K. 1991. NOAA Polar Orbiter Data User's Guide, NCDC/SDSD. (Updated from original

1984 edition.)

Teillet, P.M. 1992. An algorithm for the radiometric and atmospheric correction of AVHRR data in the

solar reflective channels. Remote Sensing of Environment 41:185-195.

Page 16
Teillet,P.M.andB.N. Holben.1994.Towardsoperationalradiometriccalibrationof NOAA AVHRR

imageryin thevisibleandnear-infraredchannels.CanadianJournalof RemoteSensing20: 1-10.

Welch,T.A. 1984.A Techniquefor High PerformanceDataCompression.IEEEComputer,Vol. 17,

No. 6, pp. 8-19.

17.2 Journal Articles and Study Reports

Cihlar, J. and P.M. Teillet. 1995. Forward piecewise linear calibration model for quasi-real time

processing of AVHRR data. Canadian Journal of Remote Sensing 21: 22-27.

Li, Z., J. Cihlar, X. Zheng, L. Moreau, and H. Ly. 1996. The bidirectional effects of AVHRR

measurements over northern regions. IEEE Transactions on Geoscience and Remote Sensing

(accepted).

Newcomer, J., D. Landis, S. Conrad, S. Curd, K. Huemmrich, D. Knapp, A. Morrell, J. Nickeson,

A. Papagno, D. Rinker, R. Strub, T. Twine, F. Hall, and P. Sellers, eds. 2000. Collected Data of The

Boreal Ecosystem-Atmosphere Study. NASA. CD-ROM.

Pokrant, H. 1991. Land cover map of Canada derived from AVHRR images. Manitoba Remote

Sensing Centre, Winnipeg, Manitoba, Canada.

Rahman, H. and G. Dedieu. 1994. SMAC: a simplified method for the atmospheric correction of

satellite measurements in the solar spectrum. International Journal for Remote Sensing 15: 123-143.

Robertson, B., A. Erickson, J. Friedel, B. Guindon, T. Fisher, R. Brown, P. Teillet, M. D'Iorio, J.

Cihlar, and A. Sancz. 1992. GEOCOMP, a NOAA AVHRR geocoding and compositing system.

Proceedings of the ISPRS Conference, Commission 2, Washington, DC, 223-228.

Roujean, J.-L., M. Leroy, and P.-Y. Deschamps. 1992. A bidirectional reflectance model of the

Earth's surface for the correction of remote sensing data. Journal of Geophysical Research 97(D 18):

20,455-20,468.

Sellers, P. and F. Hall. 1994. Boreal Ecosystem-Atmosphere Study: Experiment Plan. Version

1994-3.0, NASA BOREAS Report (EXPLAN 94).

Sellers, P. and F. Hall. 1996. Boreal Ecosystem-Atmosphere Study: Experiment Plan. Version

1996-2.0, NASA BOREAS Report (EXPLAN 96).

Sellers, P., F. Hall, and K.F. Huemmrich. 1996. Boreal Ecosystem-Atmosphere Study: 1994

Operations. NASA BOREAS Report (OPS DOC 94).

Sellers, P., F. Hall, and K.F. Huemmrich. 1997. Boreal Ecosystem-Atmosphere Study: 1996

Operations. NASA BOREAS Report (OPS DOC 96).

Sellers, P., F. Hall, H. Margolis, B. Kelly, D. Baldocchi, G. den Hartog, J. Cihlar, M.G. Ryan, B.

Goodison, P. Crill, K.J. Ranson, D. Lettenmaier, and D.E. Wickland. 1995. The boreal

ecosystem-atmosphere study (BOREAS): an overview and early results from the 1994 field year.

Bulletin of the American Meteorological Society. 76(9): 1549-1577.

Sellers, P.J., F.G. Hall, R.D. Kelly, A. Black, D. Baldocchi, J. Berry, M. Ryan, K.J. Ranson, P.M.

Crill, D.P. Lettenmaier, H. Margolis, J. Cihlar, J. Newcomer, D. Fitzjarrald, P.G. Jarvis, S.T.

Gower, D. Halliwell, D. Williams, B. Goodison, D.E. Wickland, and F.E. Guertin. 1997. BOREAS

in 1997: Experiment Overview, Scientific Results and Future Directions. Journal of Geophysical

Research 102(D24): 28,731-28,770.

Page 17
Sellers,P.J.,S.O.Los, C.J.Tucker,C.O.Justice,D.A. Dazlich,J.A. Collatz,andD.A. Randall.

1994.A global1° by 1 ° NDVI data set for climate studies. Part 2: The generation of global fields of

terrestrial biophysical parameters from the NDVI. International Journal of Remote Sensing 15:

3519-3545.

Townshend, J. (Ed.). 1995. Global data sets for the land from AVHRR. International Journal of

Remote Sensing 15:3315-3639 (special issue describing several programs generating composite

AVHRR image data sets).

Wu, A., Z. Li, and J. Cihlar. 1995. Effects of land cover type and greenness on advanced very high

resolution radiometer bidirectional reflectances: analysis and removal. Journal of Geophysical

Research 100(D): 9179-9192.

17.3 Arehive/DBMS Usage Documentation

None.

None.

18. Glossary of Terms

ABC3

AEAC

APT

ASCII

AVHRR

BOREAS

BORIS

BPI

BRDF

BSQ

CCRS

CCT

CD-ROM

CECANT

CPIDS

DAAC

DAT

DN

EOS

EOSDIS

EROS

FASIR

FPAR

GAC

GEOCOMP

GIS

GSFC

HRPT

I/O

19. List of Acronyms

- Atmosphere, Bidirectional and Contamination Corrections of CCRS

- Albers Equal Area Conic

- Automatic Picture Transmission

- American Standard Code for Information Interchange

- Advanced Very High Resolution Radiometer

- BOReal Ecosystem-Atmosphere Study

- BOREAS Information System

- Bytes per inch

- Bidirectional Reflectance Factor

- Band Sequential

- Canada Centre for Remote Sensing

- Computer Compatible Tape

- Compact Disk-Read-Only Memory

- Cloud Elimination from Composites using Albedo and NDVI Trend

- Calibration Parameter Input Dataset

- Distributed Active Archive Center

- Digital Archive Tape

- Digital Number

- Earth Observing System

- EOS Data and Information System

- Earth Resources Observation System

- Fourier-Adjustment, Solar Zenith Angle Corrected, Interpolated,

Reconstructed

- Fraction of Photosynthetically Active Radiation

- Global Area Coverage.

- Geocoding and Compositing System

- Geographic Information System

- Goddard Space Flight Center

- High-Resolution Picture Transmission

- Input/Output

Page 18
IFC

IFOV

ISLSCP

LAC

LAI

LCC

LGSOWG

MRSC

NAD83

NASA

NDVI

NEdT

NOAA

NRL

NSA

ORNL

PANP

PASS

PRT

SMAC

SSA

SST

TIROS

TOA

URL

UTM

- Intensive Field Campaign

- Instantaneous Field-of-View

- International Satellite Land Surface Climatology Project

- Local Area Coverage

- Leaf Area Index

- Lambert Conformal Conic

- Landsat Ground Station Operational Working Group

- Manitoba Remote Sensing Centre

- North American Datum of 1983

- National Aeronautics and Space Administration

- Normalized Difference Vegetation Index

- Noise Equivalent Differential Temperature

- National Oceanic and Atmospheric Administration

- Naval Research Laboratory

- Northern Study Area

- Oak Ridge National Laboratory

- Prince Albert National Park

- Prince Albert Satellite Station

- Platinum Resistor Thermometer

- Simplified Method for Atmospheric Correction

- Southern Study Area

- Sea Surface Temperature

- Television and Infrared Observation Satellite

- Top-of-the-Atmosphere

- Uniform Resource Locator

- Universal Transverse Mercator

20. Document Information

20.1 Document Revision Date

Written: 25-Jul- 1995

Last Updated: 16-Ju1-1999

20.2 Document Review Date(s)

BORIS Review: 14-Jan-1998

Science Review: 12-Sep-97

20.3 Document ID

20.4 Citation

When using these data, please include the following acknowledgment as well as citations of

relevant papers in Section 17.2:

This level-4c product was created by CCRS staff using the ABC3 method developed at CCRS.

The respective contributions of the above individuals and agencies to completing this data set are

greatly appreciated.

If using data from the BOREAS CD-ROM series, also reference the data as:

Cihlar, J., "BOREAS Staff Science Satellite Data Acquisition Program." In Collected Data of The

Boreal Ecosystem-Atmosphere Study. Eds. J. Newcomer, D. Landis, S. Conrad, S. Curd, K.

Huemmrich, D. Knapp, A. Morrell, J. Nickeson, A. Papagno, D. Rinker, R. Strub, T. Twine, F.

Hall, and P. Sellers. CD-ROM. NASA, 2000.

Page 19
Also,citetheBOREASCD-ROMsetas:

Newcomer,J.,D. Landis,S.Conrad,S.Curd,K. Huemmrich,D. Knapp,A. Morrell, J.

Nickeson,A. Papagno,D. Rinker,R.Strub,T. Twine,F. Hall, andP.Sellers,eds.CollectedDataof

TheBorealEcosystem-AtmosphereStudy.NASA. CD-ROM.NASA, 2000.

20.5 Document Curator

20.6 Document URL

Page 20
REPORT DOCUMENTATION PAGE FormApproved

OMB No. 0704-0188

Public reporting burden for this collection of informationis estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources,

gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this

collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson

Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188), Washington, DC 20503.

1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE 3. REPORT TYPE AND DATES COVERED

September 2000 Technical Memorandum

4. TITLE AND SUBTITLE 5. FUNDING NUMBERS

Technical Report Series on the Boreal Ecosystem-Atmosphere Study (BOREAS)

BOREAS Level-4c AVHRR-LAC Ten-Day Composite hnages:

Surface Parameters

6. AUTHOR(S)

Josef Cihlar, Jing Chen, Jaime Nickeson, Jeffrey A. Newcomer,

and Fengting Huang

Forrest G. Hall_ Editor

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS (ES)

Goddard Space Flight Center

Greenbelt, Maryland 20771

9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS (ES)

National Aeronautics and Space Administration

Washington, DC 20546-0001

923

RTOP: 923-462-33-01

8. PEFORMING ORGANIZATION

REPORT NUMBER

2000-03136-0

10. SPONSORING / MONITORING

AGENCY REPORT NUMBER

TM--2000-209891

Vol. 103

11. SUPPLEMENTARY NOTES

J. Cihlar, J. Chen, and F. Huang: Canada Centre for Remote Sensing, Ottawa, Ontario, Canada;

J. Nickeson and J.A. Newcomer: Raytheon ITSS, NASA Goddard Space Flight Center,

Greenbel L Maryland

12a. DISTRIBUTION / AVAILABILITY STATEMENT

Unclassifie_Unlimited

Subject Category: 43

Report available from the NASA Center for AeroSpace Information,

7121 Standard Drive, Hanover, MD 21076-1320. (301) 621-0390.

12b. DISTRIBUTION CODE

13. ABSTRACT (Maximum 200 words)

The BOREAS Staff Science Satellite Data Acquisition Program focused on providing the research

teams with the remotely sensed satellite data products they needed to compare and spatially extend

point results. MRSC and BORIS personnel acquired, processed, and archived data from the AVHRR

instruments on the NOAA-11 and -14 satellites. The AVHRR data were acquired by CCRS and were

provided to BORIS for use by BOREAS researchers. These AVHRR level-4c data are gridded, 10-day

composites of surface parameters produced from sets of single-day images. Temporally, the 10-day

compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire

BOREAS region. The data are stored in binary image format files.

Note: Some of the data files on the BOREAS CD-ROMs have been compressed using the Gzip program. See section 8.2 for details.

14. SUBJECT TERMS

BOREAS, remote sensing science, AVHRR.

17. SECURITY CLASSIFICATION

OF REPORT

Unclassified

NSN 7540-01-280-5500

18. SECURITY CLASSIFICATION

OF THIS PAGE

Unclassified

19. SECURITY CLASSIFICATION

OF ABSTRACT

Unclassified

15. NUMBER OF PAGES

2O

16. PRICE CODE

20. LIMITATION OF ABSTRACT

UL

Standard Form 298 (Rev. 2-89)

Prescribed by ANSI Std. Z39.18

298-102