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

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.

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-4 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.

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

Staff Science Satellite Data Acquisition Program

2.3 Contact Information

Contact 1
----------
Josef Cihlar  
Canada Centre for Remote Sensing
Ottawa, Ontario  
Canada  
(613) 947-1265   
(613) 947-1406 (fax)  
Josef.Cihlar@geocan.emr.ca


Contact 2 
----------
Jaime Nickeson 
Raytheon STX Corporation
NASA/GSFC
Greenbelt, MD.
(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                       Primary Use
              [micrometers]
-------    -------------------    ---------------------------------------------
   1*         0.57  -  0.69       Daytime Cloud and Surface Mapping
   2          0.72  -  0.98       Surface Water Delineation, Vegetation Cover
   3          3.52  -  3.95       Sea Surface Temperature (SST), Nighttime 
                                  Cloud Mapping
   4**       10.3   - 11.4        Surface Temperature, Day/Night Cloud Mapping
   5***      11.4   - 12.4        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, -10, 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-11           NOAA-12           NOAA-14
 ----  ---------------   ---------------   ---------------   ---------------
  1     0.570 -  0.699    0.572 -  0.698    0.571 -  0.684    0.570 -  0.699
  2     0.714 -  0.983    0.716 -  0.985    0.724 -  0.984    0.714 -  0.983
  3     3.525 -  3.931    3.536 -  3.935    3.554 -  3.950    3.525 -  3.931
  4    10.334 - 11.252   10.338 - 11.287   10.601 - 11.445   10.330 - 11.250
  5    11.395 - 12.342   11.408 - 12.386   10.601 - 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).

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 are 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 km.  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-Jul-1983 to 30-Dec-1984
NOAA-8       28-Mar-1983      24-Jul-1983 to 13-Aug-1985
NOAA-9       12-Dec-1984      16-Sep-1985 to 19-Mar-1995
NOAA-10      17-Sep-1986      11-Oct-1986 to 15-Nov-1993
NOAA-11      24-Sep-1988      28-Jun-1989 to 13-Sep-1994
NOAA-12      14-May-1991      11-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.

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          1.1 km
ALTITUDE            833 km
SCAN RATE           360 scans/min (1.362 samples per IFOV)
SCAN RANGE          -55.4 to 55.4 degrees
SAMPLES/SCAN        2,048 samples 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 Laboratorys (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: 

1) Telemetry data are extracted and unpacked.
2) Ramp calibration data for each of the five channels are decommutated.
3) A single Platinum Resistor Thermometer (PRT) count is extracted.
4) Ten samples of internal target, or blackbody, data are decommutated and 
   filtered.
5) 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 the Calibration Parameter Input 
                 Dataset (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:

INDEX = 10.0 * PRT TEMPERATURE 1798.5  

The blackbody radiances for infrared channels are extracted from the table, 
which was generated from CPIDS. From the decommutated blackbody data, the mean 
and standard deviation of the internal target are computed. This computation is 
also done for the mean and standard deviation of space view data. The slopes and 
intercepts are then calculated using the previously computed data. The slope and 
intercept for the visible channels are assigned constants. For each of the 
infrared channels, the slope and intercept are calculated using the formula:

            SPACEVIEW RADIANCE - BLACKBODY RADIANCE
SLOPE  =   ----------------------------------------
               SPACEVIEW MEAN - BLACKBODY MEAN


INTERCEPT = SPACEVIEW RADIANCE SLOPE * SPACEVIEW MEAN 

The slopes and intercepts for all five channels are then stored in each scan 
line in the given block. The calibration overlay then begins this process again 
for the next block. The final function of the calibration overlay is to 
determine ramp linearity or nonlinearity. This process reverses the ramp on 
infrared channels from descending to ascending. The ramp values are then 
adjusted according to data type (i.e., LAC or Global Area Coverage [GAC]).

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 1200 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. Observations

6.1 Data Notes

None.

6.2 Field Notes

None.

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 1200 pixels in each of the 1200 
lines and cover the entire 1000 km by 1000 km BOREAS region.  This includes both 
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 (1,1)           59.36395N    115.40859W
Northeast (1,1200)        61.01294N     93.28553W
Southwest (1200,1)        48.83387N    110.25229W
Southeast (1200,1200)     50.02993N     93.73857W

The northwest corner has a distance (1109.76 km west,  7900.04 km north) from 
the origin (95W and 0N) of the LCC coordinate.  The pixel size is exactly 1 
km.  

The North American Datum of 1983 (NAD83) corner coordinates of the BOREAS region 
are:
             Latitude     Longitude
             --------     ---------
Northwest    59.979N     111.000W
Northeast    58.844N      93.502W
Southwest    51.000N     111.000W
Southeast    50.089N      96.970W

The NAD83 corner coordinates of the SSA are:

             Latitude     Longitude
             --------     ---------
Northwest    54.319N     106.227W
Northeast    54.223N     104.236W
Southwest    53.513N     106.320W
Southeast    53.419N     104.368W

The NAD83 corner coordinates of the NSA are:

             Latitude     Longitude
             --------     ---------
Northwest    56.249N      98.824W
Northeast    56.083N      97.241W
Southwest    55.542N      99.045W
Southeast    55.379N      97.489W

7.1.2 Spatial Coverage Map

Not available.

7.1.3 Spatial Resolution

Before any geometric corrections, the spatial resolution varies from 1.1 km at 
nadir to approximately 2.5 x 6.8  km at the extreme edges of the scan.  The 
level-4b composite AVHRR-LAC images have had geometric corrections applied so 
that the pixel size is 1 km 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 49N and 77N, respectively and the meridian at 95W.

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 9-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              11 - 20, 21 - 30
May        1 - 10, 11 - 20, 21 - 31
June       1 - 10, 11 - 20, 21 - 30
July       1 - 10, 11 - 20, 21 - 31
August     1 - 10, 11 - 20, 21 - 30
September  1 - 10

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 


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.


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
----  -----------------------
  1   AVHRR channel 1 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  
 10   Mask of missing data  

The image files contain 1200 pixels in each of 1200 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 file record is 2400 bytes in 
length.  Files 9 and 10 (the masks) for each period are single-byte images with 
each file record being 1200 bytes in length.
 
The images are oriented such that pixel 1, line 1 is in the upper left-hand 
corner (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 corner. 


8.2.2 Compressed CD-ROM Files

On the BOREAS CD-ROMs, the image files 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 websites (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.

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. (1996a, 1996b).

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 postlaunch 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:

C1(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).

NDVImax(i,j,t) and NDVIa(i,j,t) were calculated using the FASIR model of Sellers 
et al. (1994), which approximates the seasonal NDVI curve with a third-order 
Fourier transform.  Before the computation, missing NDVI values between first 
and last measurements were replaced through linear interpolation after finding 
the seasonal peak for each pixel, using the rationale and algorithm of Cihlar 
and Howarth (1994).  A constant value of 0.30 was used for C1.  The upper and 
lower limits for R and Z were determined separately for each composite period 
using R and Z histograms (Cihlar, 1996).  Using these thresholds, a cloud mask 
was prepared for each composite period.

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 + a1*(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 AVHRR channels 4 and 5 

Coefficients a0 = 1.29, a1 = 0.28 alpha = 45 K, beta = 40 K.

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., [1996a] and Cihlar, et al. 
[1996b] for discussion): 

C1(md)  = 0.04 + 0.26*C1(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:

C1(md)   = 0.03 + 0.48 * C1 (sd);   r2 = 0.10, se = 0.06
C2(md)   = 0.06 + 0.90 * C2(sd);    r2 = 0.69, se = 0.017
NDVI(md) = 0.17 + 0.74 * NDVI (sd); r2 = 0.55, se = 0.024

10.2.2 Confidence Level/Accuracy Judgment

An evaluation of the resulting data set (Cihlar, et al., 1996a) 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.

10.2.3 Measurement Error for Parameters

Refer to level-3b and level-4b product specification

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. 
(1996a). 

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.

12. Application of the Data Set

None given.

13. Future Modifications and Plans

None given.

14. Software

None.

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:

1) 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

2) Reading the ASCII disk file and logging the level-4c AVHRR-LAC image products 
   into the Oracle data base tables.

3) 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 websites across the net (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 

15.1 Contact Information

Ms. Beth Nelson
BOREAS Data Manager
NASA/GSFC
Greenbelt, MD 
(301) 286 4005
(301) 286 0239 (fax)
Elizabeth.Nelson@gsfc.nasa.gov

15.2 Data Center Identification

See Section 15.1.

15.3 Procedures for Obtaining Data

Users may place requests by telephone, electronic mail, or fax.

15.4 Data Center Status/Plans

The AVHRR level-4c image data are available from the Earth Observing System Data 
and Information System (EOSDIS). Oak Ridge National Laboratory (ORNL), 
Distributed Active Archive Center (DAAC).  The BOREAS contact at ORNL is:

ORNL DAAC User Services
Oak Ridge National Laboratory
(865) 241-3952
ornldaac@ornl.gov
ornl@eos.nasa.gov

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

None.

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. 1996a. 
Multitemporal, multichannel data sets for land biosphere studies: artifacts and 
corrections. Remote Sensing of Environment (in press).

Cihlar, J., J. Chen, and Z. Li, 1996b.  Seasonal AVHRR multi-channel data sets 
and products for scaling up biospheric processes.  Journal of Geophysical 
Research, Special BOREAS Issue (submitted).

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.

Teillet, P.M. and B.N. Holben. 1994. Towards operational radiometric calibration 
of NOAA AVHRR imagery in the visible and near-infrared channels. Canadian 
Journal of Remote Sensing 20: 1-10. 

Welch, T.A. 1984, A Technique for High Performance Data Compression, IEEE 
Computer, 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).

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(D18): 20,455-20,468. 

Sellers, P.J., Los, S.O., Tucker, C.J., Justice C.O., Dazlich, D.A., Collatz, 
J.A., and Randall, D.A.  1994.  A global 1 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.

Sellers, P. and F. Hall. 1994. Boreal Ecosystem-Atmosphere Study: Experiment 
Plan. Version 1994-3.0, NASA BOREAS Report (EXPLAN 94). 

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., F. Hall, and K.F. Huemmrich. 1996. Boreal Ecosystem-Atmosphere 
Study: 1994 Operations. NASA BOREAS Report (OPS DOC 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. 1997. Boreal Ecosystem-Atmosphere 
Study: 1996 Operations. NASA BOREAS Report (OPS DOC 96). 

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 
(JGR), BOREAS Special Issue, 102(D24), Dec. 1997, pp. 28731-28770.  

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 Archive/DBMS Usage Documentation

The raw data are archived by CCRS at PASS. Processed level-4c data are currently 
archived at NASA GSFC. 

18. Glossary of Terms

None.

19. List of Acronyms

    ABC3    - Atmosphere, Bidirectional and Contamination Corrections of CCRS
    AEAC    - Albers Equal Area Conic
    APT     - Automatic Picture Transmission
    ASCII   - American Standard Code for Information Interchange
    AVHRR   - Advanced Very High Resolution Radiometer
    BOREAS  - BOReal Ecosystem-Atmosphere Study
    BORIS   - BOREAS Information System
    BPI     - Bytes per inch
    BRDF    - Bidirectional Reflectance Factor
    BSQ     - Band Sequential
    CECANT  - Cloud Elimination from Composites using Albedo and NDVI Trend
    CCRS    - Canada Centre for Remote Sensing
    CCT     - Computer Compatible Tape
    CD-ROM  - Compact Disk-Read-Only Memory
    CPIDS   - Calibration Parameter Input Dataset
    DAAC    - Distributed Active Archive Center
    DAT     - Digital Archive Tape
    DN      - Digital Number
    EOS     - Earth Observing System
    EOSDIS  - EOS Data and Information System
    EROS    - Earth Resources Observation System
    FASIR   - Fourier-Admustment, Solar Zenith Angle Corrected, Interpolated,
              Reconstructed
    FPAR    - Fraction of Photosynthetically Active Radiation
    GAC     - Global Area Coverage.
    GEOCOMP - Geocoding and Compositing System
    GSFC    - Goddard Space Flight Center
    HRPT    - High-Resolution Picture Transmission
    IFC     - Intensive Field Campaign
    I/O     - Input/Output
    IFOV    - Instantaneous Field-of-View
    ISLSCP  - International Satellite Land Surface Climatology Project
    LAI     - Leaf Area Index
    LAC     - Local Area Coverage
    LCC     - Lambert Conformal Conic
    MRSC    - Manitoba Remote Sensing Centre
    NAD83   - North American Datum of 1983
    NASA    - National Aeronautics and Space Administration
    NDVI    - Normalized Difference Vegetation Index
    NEdT    - Noise Equivalent Differential Temperature
    NOAA    - National Oceanic and Atmospheric Administration
    NRL     - Naval Research Laboratory
    NSA     - Northern Study Area
    ORNL    - Oak Ridge National Laboratory
    PANP    - Prince Albert National Park
    PASS    - Prince Albert Satellite Station
    PRT     - Platinum Resistor Thermometer   
    SMAC    - Simplified Method for Atmospheric Correction
    SSA     - Southern Study Area
    SST     - Sea Surface Temperature
    TIROS   - Television and Infrared Observation Satellite
    TOA     - top-of-the-Atmosphere
    URL     - Uniform Resource Locator
    UTM     - Universal Transver Mercator
    
20. Document Information

20.1 Document Revision Date 

     Written:         25-Jul-1995
     Last Updated:    14-Sep-1998

20.2 Document Review Date(s)

     BORIS Review:    14-Jan-1998
     Science Review:  12-Sep-97

20.3 Document ID 

20.4 Citation 

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.

20.5 Document Curator

20.6 Document URL 


Keywords:
    AVHRR-LAC
    TEMPERATURE
    NOAA
    REFLECTANCE
    NDVI

AVHRR_L4c.doc
09/14/98