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 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:
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) 59.36395�N 115.40859�W
Northeast (1,1200) 61.01294�N 93.28553�W
Southwest (1200,1) 48.83387�N 110.25229�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
km.
The North American Datum of 1983 (NAD83) corner coordinates of the BOREAS region
are:
Latitude Longitude
-------- ---------
Northwest 59.979�N 111.000�W
Northeast 58.844�N 93.502�W
Southwest 51.000�N 111.000�W
Southeast 50.089�N 96.970�W
The NAD83 corner coordinates of the SSA are:
Latitude Longitude
-------- ---------
Northwest 54.319�N 106.227�W
Northeast 54.223�N 104.236�W
Southwest 53.513�N 106.320�W
Southeast 53.419�N 104.368�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.
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 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 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