BOREAS Level-3b AVHRR-LAC Imagery: Scaled At-sensor Radiance in LGSOWG Format
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. Data acquired from the AVHRR
instrument on the NOAA-9, -11, -12, and -14 satellites were processed and
archived for the BOREAS region by the MRSC and BORIS. The data were acquired by
CCRS and were provided for use by BOREAS researchers. A few winter acquisitions
are available, but the archive contains primarily growing season imagery. These
gridded, at-sensor radiance image data cover the period of 30-Jan-1994 to 18-
Sep-1996. Geographically, the data cover the entire 1000 km x 1000 km BOREAS
Region. The data are stored in binary image format files.
Note that the level-3b AVHRR-LAC images are not contained on the BOREAS CD-ROM
set. An inventory listing of files is supplied on the CD-ROM to inform users of
the data that are available. See section 15.1 for information about how to
acquire the data.
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-3b AVHRR-LAC Imagery: Scaled At-sensor Radiance in LGSOWG Format
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) instrument 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 were provided for use by BOREAS
researchers.
1.3 Objective/Purpose
For BOREAS, the level-3b AVHRR-Local Area Coverage (LAC) images, along with the
other remotely sensed images, were collected in order to provide spatially
extensive information over the 1,000-km x 1,000-km BOREAS region at varying
spatial scales. This information includes detailed land cover and biophysical
parameter maps such as Fraction of Photosynthetically Active Radiation (fPAR)
and Leaf Area Index (LAI).
The Manitoba Remote Sensing Centre (MRSC) and the BOREAS Information System
(BORIS) processed and archived the five-band level-3b AVHRR-LAC image products.
1.4 Summary of Parameters
Level-3b NOAA AVHRR-LAC data in the BORIS contain the following parameters:
Original image header information; subset coordinates; summary information for
the subset area; geographic position, view angle, and solar angle
information; image bands 1 to 5.
1.5 Discussion
Level-3b data sets are single-date images produced by the CCRS GEOCOMP Geocoding
and Compositing (GEOCOMP) system specifically for BOREAS. The major
differences, when compared to the processing for the AVHRR level-4 products are:
1) Projection. The level-3b data are in the Albers Equal-Area Conic (AEAC)
projection; the level-4 data are in the Lambert Conformal Conic (LCC)
projection.
2) Calibration coefficients. For the NOAA-14 data from 1995, the calibration
coefficients used for level-3b are different from those used for level-4c (but
are identical to those used for level-4b).
The remainder of the processing is the same; i.e., each single-date image is
registered to a map projection using high-resolution image chips, the image is
then resampled, and output channels are produced. There is no compositing
involved for the level-3b product. Details of the level-3b processing are
described in Section 9.
BORIS staff processes the Level-3b AVHRR-LAC images by: 1) extracting pertinent
header information from the Level-3b image product and placing it in an American
Standard Code for Information Interchange (ASCII) file on disk, and 2) reading
the information in the disk file and loading the online data base with
information.
1.6 Related Data Sets
BOREAS Level-4b AVHRR-LAC Ten-Day Composite Images: At-sensor Radiance
BOREAS Level-4c AVHRR-LAC Ten-Day Composite Images: Surface Parameters
2. Investigator(s)
2.1 Investigator(s) Name and Title
Josef Cihlar
Canada centre for Remote Sensing
2.2 Title of Investigation
BOREAS Staff Science Satellite Data Acquisition Program
2.3 Contact Information
Contact 1
---------
Josef Cihlar
Canada Centre for Remote Sensing
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, -12, and -14 polar orbiting platforms. The
radiometers measured emitted and reflected radiation in one visible, one near-
infrared, one middle-infrared, and one or two thermal channels (on some
platforms the thermal channels were identical).
The primary use of each channel and spectral regions and bandwidths on the
respective NOAA platforms are given in the following tables:
Channel Wavelength Primary Use
[�m]
------- ------------------- ---------------------------------------------
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 - 11.40 Surface Temperature, Day/Night Cloud Mapping
5*** 11.4 - 12.40 Surface Temperature
-------------------------------------------------------------------------------
* Channel 1 wavelength for the Television and Infrared Observation Satellite
(TIROS)-N flight model was 0.55-0.90 �m.
** For NOAA-7 and -9, channel 4 was 10.3-11.3 �m.
*** For TIROS-N and NOAA-6, -8, -10, and -12, channel 5 duplicates channel 4.
The wavelength ranges at 50 percent relative spectral response (�m)
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 can operate 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.
4. Equipment
4.1 Sensor/Instrument Description
The AVHRR is a cross-track scanning system featuring one visible, one near-
infrared, one middle-infrared, and two thermal channels. The analog data output
from the sensors is digitized onboard the satellite at a rate of 39,936 samples
per second per channel. Each sample step corresponds to an angle of scanner
rotation of 0.95 milliradians. At this sampling rate, there are 1.362 samples
per instantaneous field of view (IFOV). A total of 2,048 samples is obtained per
channel per Earth scan, which spans an angle of +/-55.4 degrees from nadir.
4.1.1 Collection Environment
The NOAA satellites orbit Earth at an altitude of 833 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 -14
polar orbiting platforms.
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
than of Earth. A two-stage radiant cooler is used to maintain a constant
temperature of 95 K for the infrared detectors. The operating temperature is
selectable at either 105 or 110 degrees 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 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
ITT Aerospace
P.O. Box 3700
Fort Wayne, IN 46801-3700
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 4 PRT counts whose values are greater than 10. After
decommutation, the PRT counts are filtered, and the mean and standard deviation
of each PRT are computed. The mean PRT counts are then converted to temperature
using the formula:
T(1) = C(0) + C(1)M(j) + C(2)[M(j)2] + C(3)[M(j)3] + C(4)[M(j)4]
where: T(1) = the temperature of each of the four PRTs
C(i) = the PRT coefficients from CPIDS
M(j) = the mean count of each of the four PRTs
The mean of the four PRT temperatures is then computed to get the temperature of
the blackbody. The blackbody temperature is used to calculate the index of the
temperature-to-radiance lookup table using the formula:
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 slopes 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-3b 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 (AEAC projection). A full Level-3b
AVHRR-LAC image for the BOREAS region contains approximately 1,000 pixels in
each of approximately 1000 lines. Before geometric corrections, the ground
resolution ranges from 1.1 km at nadir to 5 km x 6.8 km at the scanning extreme
of 55.4 degrees. The raw pixel values in the images can range from 0 to 1,024.
The Level-3b image pixel values are scaled radiances stored in 16-bit (2-byte)
fields and can range from -32,768 to 32,767. The level-3b images were processed
through the CCRS GEOCOMP system, which applies both radiometric and spatial
corrections to the imagery. Because of data volume and pervasive cloudiness,
only a limited number of single-date Level-3b images were placed into BORIS. 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
five spectral channels. The 110.8-degree scan equates to a swath of 27.2 degrees
in longitude (at the Equator) centered on the sub-satellite 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-3b AVHRR-LAC images essentially cover the entire 1,000-km by
1,000-km BOREAS region. This contains both the Northern Study Area (NSA), the
Southern Study Area (SSA), the transect region between the SSA and NSA, and some
surrounding area. The actual coverage of each image depends on the position of
the sub-satellite track.
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 at this time.
7.1.3 Spatial Resolution
Before any geometric corrections, the spatial resolution varies from 1.1 km at
nadir to approximately 4.5 km at the extreme edges of the scan. The Level-3b
AVHRR-LAC images have had geometric corrections applied so that the size for all
pixels is 1 km in all bands.
7.1.4 Projection
The established BOREAS grid system is based on the ellipsoidal version of the
AEAC projection as defined within the NAD83. The origin of the grid is at 111�
W, 51� N, and the standard parallels are set to 52.5� N and 58.5� N as
prescribed in "Map Projections - A Working Manual," USGS Professional Paper
1395, John P. Snyder, 1987. All of the projection equations used to calculate
the BOREAS grid coordinates were taken from this manual.
7.1.5 Grid Description
The level-3b images are projected into the AEAC projection described in Section
7.1.4 at a grid cell size of 1.0 km per pixel in both the X and Y directions.
7.2 Temporal Characteristics
7.2.1 Temporal Coverage
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-11 daytime) and are archived at PASS. Only mostly cloud-free images
were processed and included in BORIS.
The overall time period of data acquisition for BOREAS in 1994 was from 30-Jan
through 6-Oct. CCRS acquired most AVHRR-LAC daytime images from NOAA-9 and -11
for each satellite pass; i.e., two images in each 24-hour cycle.
The overall time period of data acquisition for BOREAS in 1995 was from 5-Jan
through 27-Sep. CCRS acquired most AVHRR-LAC daytime images from NOAA-9 and -14
for each satellite pass; i.e., two images in each 24-hour cycle.
The overall data holdings for BOREAS in 1996 are currently just two winter
dates, 6-Mar and 22-Mar. CCRS acquired the AVHRR-LAC daytime images from NOAA-
14 for each satellite pass; i.e., two images in each 24-hour cycle.
BORIS contains relatively complete AVHRR-LAC coverage from NOAA-11 of central
Canada during the snow-free periods in 1994 and 1995. Scenes covering all or a
significant part of the BOREAS region were included in BORIS.
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 Normalized Difference Vegetation Index (NDVI) imagery. Contact the
Statistics Canada Crop Condition Assessment Program office for more information.
7.2.2 Temporal Coverage Map
Not available.
7.2.3 Temporal Resolution
There are generally two overpasses per day per satellite at approximately 0200
or 0900 and 1400 or 2100 Greenwich Mean Time (GMT). However, not all of these
data are processed and distributed because of cloud cover and other data
problems. Adjacent orbits can cause double coverage at an interval of 90
minutes, increasing the number of scenes on some days.
Each scan of the AVHRR views Earth for a period of 51.282 msec. During this
period each channel of the analog data output is digitized to obtain a total of
2048 samples at intervals of 25.0 microseconds (the sampling rate of the AVHRR
sensors is 39,936 samples/sec/channel). Successive scans occur at the rate of 6
per second, or at intervals of 167 msec. These data provide LAC and HRPT.
For BOREAS, the level-3b scenes that are available were selected based on the
amounts of cloud cover and image quality.
7.3 Data Characteristics
Data characteristics are defined in the companion data definition file
(avhrrl3b.def).
7.4 Sample Data Record
Sample data format shown in the companion data definition file (avhrrl3b.def).
8. Data Organization
8.1 Data Granularity
The smallest unit of data for level-3b AVHRR-LAC is an image. The level-3b
AVHRR-LAC images from CCRS are stored in band interleaved by line (BIL) form.
General information on this format is provided in the subsequent sections.
Detailed information on this can be obtained from the CCRS documents referenced
in Section 17.1.
8.2 Data Format(s)
The AVHRR-LAC level-3b data are supplied in Landsat Ground Station Operational
Working Group (LGSOWG) BIL format.
File 1 Physical Volume Directory
File 2 Logical Volume Directory
File 3 Leader File Bands 1-5
File 4 Image Data File for AVHRR-LAC Bands 1-5
File 5 Trailer
File 6 Null Volume File
If there are multiple scenes on a tape, the subsequent scene would occupy files
7-11 (five files), as files 2-6 above (there is only one physical volume
directory per physical tape). The image files in BIL format contain image data
for all five spectral bands.
8.2.1 BIL Logical Volume Directory File
This file contains:
1) Volume descriptor record
2) File pointer records for the leader, image data, and trailer files
3) Text record
8.2.2 BIL Leader Files
The contents of leader files have been defined in detail by the LGSOWG Technical
Working Group (LTWG). The contents of the leader files are as follows:
1) File descriptor record
2) Scene header record
3) Ancillary records (map projection, ground control points, ephemeris, and
radiometric transformation)
All leader files contain fixed-length records of 2,520 bytes and contain both
ASCII and binary data. For specific details, see the CCRS documentation
referenced in Section 17.1.
8.2.3 BIL Imagery File
The single BIL image file has 5,001 records, with each record containing 2,808
bytes. The first record in the file is the file descriptor record, followed by
5,000 image records for a total of 10,00 lines of the scene for all five bands
(1,000 lines x 5 bands = 5,000 records). In a BIL image file, the first five
image records are line 1, bands 1-5, respectively; the next five image records
are line 2, bands 1-5, respectively; and so on. Each image record contains 36
bytes (18 pixels) of prefix data, 2,000 bytes (1,000 pixels) of image data, and
772 bytes of suffix data (36 + 2,000 + 772 = 2,808 bytes).
The image is oriented so 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. Each pixel value is contained in a 2-byte (16-bit) field ordered as
most significant (high-order) byte first.
8.2.4 BIL Trailer File
The trailer file contains information associated with the image data that is not
always available before writing the image data, such as data and recording
quality and data summaries. Each trailer file contains a file descriptor record
and trailer records for all bands of imagery in the associated imagery file.
All trailer files contain fixed length records of 4,140 bytes and contain both
ASCII and binary data. For specific details, see the CCRS documentation
referenced in Section 17.1.
8.2.5 BIL Null Volume File
The null volume file contains one record that designates the end of the data
volume. The BOREAS level-3b AVHRR-LAC tapes contain null volume files after
each image because multiple scenes were copied to a tape from several original
tapes.
9. Data Manipulations
9.1 Formulae
9.1.1 Derivation Techniques and Algorithms
The AVHRR-LAC processing is carried out by GEOCOMP (Robertson et al., 1992).
Designed to produce AVHRR-LAC composite images over continental areas, GEOCOMP
operates in two steps. First, individual images are registered and resampled to
coregister with one another and with a baseline map. Second, the images are
composited to find the most cloud-free pixels for the period of interest. Level-
3b images are the result of step 1. The requirement for high throughput was
handled in GEOCOMP by giving the operator an option to divide the orbit into
smaller scenes (thus reducing the number of empty pixels after geometric
correction). Buffam (1994) provides detailed documentation of the GEOCOMP
products from the user viewpoint.
All five AVHRR-LAC channels are calibrated by GEOCOMP. Channels 3-5 are
calibrated using onboard calibration data (Planet, 1979). Data for the
reflective channels i (i = 1,2) are calibrated in two steps (Teillet and Holben,
1994): first by converting the raw digital signal level (DSL) Di(raw) into
apparent sensor radiance L*i, and then by representing the resulting L*i on a
fixed 10-bit output scale as calibrated DSL Di(cal). The formulas used are:
Li* = (Di(raw)-D0i(d))/Gi(d) [1]
Di(cal) = Gi(cal) * (Li*) + D0i(cal) [2]
Gi(cal) = 1023/(Li*max - Li*min) [3]
D0i(cal) = -Gi(cal) * Li*min [4]
where:
Li* is the radiance at the top-of-the-atmosphere in channel i (i=1,2)
[(W/(m2 sr �m)].
Di(raw) is the measured value for channel i (in 10 bits) [counts].
D0i(d) is the calibration offset coefficient on day d [counts].
Gi(d) is the calibration gain coefficient on day d [(counts m2 sr �m)/W].
Di(cal) is the final digital signal level (DSL) on GEOCOMP product for channel
i.
Gi(cal) is time-independent calibration gain coefficient [(counts m2 sr �m)/W].
D0i(cal) is time-independent calibration offset coefficient [counts].
Li*max, Li*min are the (time-independent) maximum and minimum Li* values.
The values of Li* used in GEOCOMP are [W/(m2 sr �m)])
L1*min = -25
L2*min = -15
L1*max = 600
L2*max = 400
GEOCOMP uses time-dependent (defined as days since launch) correction of the
AVHRR-LAC gain Gi and offset D0i of each of the channels 1 and 2 (Teillet and
Holben, 1994) as seen above, and onboard blackbody calibration targets for
channels 3, 4 and 5. The resulting values are in radiance units [W/(m2 sr �m)]
for channels 1 and 2, and mW/(m2 sr cm) for channels 3-5. Thus, for channel i,
i=1,2 the gain and offset are:
Gi(d) = A*d + B [5]
D0i(d) = D*d + E [6]
where A, B, D, E are channel-dependent coefficients.
The coefficients A, B, D, and E in equations [5] and [6] describing the temporal
dependence of Gi(d) and D0i(d) are stored in a separate GEOCOMP data base. The
values used for processing 1994 AVHRR-LAC data for BOREAS by Cihlar and Teillet
(1995) for NOAA-9 and -11 are reproduced below. Coefficients for NOAA-14 were
based on pre-launch calibration supplied by NOAA. Rws A1-D1 represent channel
1, and rows A2-D2 represent Channel 2.
Calibration coefficients used to produce level-3 and products:
NOAA-9 1994 NOAA-11 NOAA-14 1995 NOAA-14 1995 NOAA-14 1996
Level-3b Levels-3,-4 Levels-3b,-4b Level-4c Levels-3,-4
----------- ---------- ------------ ------------ ------------
A1 -1.721E-04 -5.601E-05 0 -3.527E-04 -3.047E-04
B1 1.6376157 1.815337 1.81 1.795 1.778
C1 0 0 0 0 0
D1 37 40 35.8 41.0 41.0
A2 -1.828E-04 -1.331E-0 0 -6.16E-04 -5.088E-04
B2 2.503063 2.700631 2.80 2.364 2.324
C2 0 0 0 0 0
D2 39.6 40 33.7 41.0 41,0
Note: For NOAA-14 in 1995, a distinction needs to be made between data
processed as level-3b, which used prelaunch calibration, and levels-4b and -4c,
which used postlaunch with sensor degradation.
Angular information is encoded in the GEOCOMP format to allow calculation of the
solar zenith, view zenith, and relative azimuth angles for each resampled pixel.
This information is located in the suffix of the image file. In each image line,
65 tie-points are encoded for the four angles: solar zenith, solar azimuth,
satellite zenith, and satellite azimuth. After extracting these angles on tie-
point pixels (65 pixels within each image line), linear interpolation is applied
to get the angles for each pixel within the line. The relative azimuth angle is
given by:
Relative Azimuth = abs(Solar Zenith - Satellite Zenith)
9.2 Data Processing Sequence
9.2.1 Processing Steps
GEOCOMP created the level-3b HRPT image by:
1) Inputing the geocoding work order and associated auxiliary data
2) Inputing raw image data from 8-mm tape
3) Viewing the input image and defining products interactively (optional)
4) Generating a spacecraft model
5) Generating image correction parameters
6) Correcting imagery (sensor calibration, three-pass image resampling)
7) Estimating quality or allowing the image to be viewed
8) Outputing imagery
BORIS processed a level-3b AVHRR-LAC image by:
1) Extracting pertinent header information from the level-3 image product and
writing it to a disk file
2) Reading the information in the disk file and loading the online data base
with needed information
9.2.2 Processing Changes
None.
9.3 Calculations
9.3.1 Special Corrections/Adjustments
None.
9.3.2 Calculated Variables
None.
9.4 Graphs and Plots
None.
10. Errors
10.1 Sources of Error
There has been a serious noise problem caused by a spacecraft malfunction with
data from channel 3 on the TIROS-N series spacecraft. This problem is especially
obvious when the satellite is in daylight, and may render some data unusable.
See Section 4.2.
Users of LAC/HRPT data should be aware that the satellite's onboard clock
experiences a small drift in time over a period of several months.
Specifically, that time drift may be defined by ?t, where ?t is the spacecraft
clock time minus the actual GMT. Satellite Operations Control Center (SOCC)
monitors this time error and corrects ?t to +0.5 second when it reaches -0.5
second. The Earth data that are appended to the level-0 data are based on the
spacecraft clock time. Therefore, an error in dt will be reflected as an error
in Earth location. The error in Earth location caused by this timing error
could be as much as 4 kilometers at the satellite subpoint. SOCC applies the
correction to dt just before an orbital recording begins, so a user would never
see a jump in the Earth location of a particular data set. This does not
influence the accuracy of the level-3b data; the effect is taken out during
GEOCOMP registration and processing.
Some uncertainties remain in the geometric location of the level-3b resampled
pixels. The root mean square (rms) error in the location of control points is
most often less than 1,000 meters (typically 600-800 meters rms).
10.2 Quality Assessment
10.2.1 Data Validation by Source
Not available.
10.2.2 Confidence Level/Accuracy Judgment
The AVHRR reflective channels 1 and 2 are designed to accommodate a dynamic
range of 200 to 1. A full-scale signal corresponds to 100 percent albedo, that
is, the radiance from a diffuse (Lambertian) reflector (a bright cloud) under
full solar illumination. A minimum detectable signal corresponds to 0.5 percent
albedo with a signal-to-noise ratio of at least 3 to 1. The thermal channels 3,
4, and 5 are calibrated in-flight using a view of a stable blackbody and space
as a reference. These channels are designed to measure emitted thermal
radiation with an accuracy better than 0.14 �C for a source blackbody
temperature of 300 K.
10.2.3 Measurement Error for Parameters
The sensor view zenith and azimuth angles calculated for use in atmospheric
correction have a resolution of 0.01 degrees.
10.2.4 Additional Quality Assessments
GEOCOMP uses the information embedded in the downlinked data stream to perform a
partial evaluation of input data quality. The operator checks the general
quality of the input and output images.
Band quality is judged and the quality level is included in the BORIS database
inventory table. Images are screened for cloud cover, and different levels of
cover are assigned in processing.
10.2.5 Data Verification by Data Center
BORIS has extracted header information and inventoried the AVHRR data
acquisition information in the data base. BORIS has also viewed some of the
imagery and confirmed the use of scaling information provided in section 7.3.2.
11. Notes
11.1 Limitations of the Data
None.
11.2 Known Problems with the Data
None.
11.3 Usage Guidance
None.
11.4 Other Relevant Information
None.
12. Application of the Data Set
These data could be used to investigate regional land cover and land cover
change over the BOREAS time period.
13. Future Modifications and Plans
Not available.
14. Software
14.1 Software Description
The GEOCOMP software is written in Pascal and FORTRAN and runs on Digital's VAX
computers. Special code also exists for the GEOCOMP array processor. The
GEOCOMP software is proprietary.
BORIS staff has developed software and command procedures for:
1) Extracting header information from level-3 AVHRR-LAC images on tape and
writing it to ASCII files on disk
2) Reading the ASCII disk file and logging the level-3 AVHRR-LAC image products
into the Oracle data base tables
3) Converting between the geographic systems of (latitude, longitude),
Universale 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 Goddard Space Flight Center (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 developed for BOREAS (BOR_CORD) has
been tested and used on Macintosh, IBM PC, VAX, Silicon Graphics, and Sun
workstations.
14.2 Software Access
Most of the GEOCOMP software is proprietary. For further information, contact:
MacDonald Dettwiler and Associates
13800 Commerce Parkway
Richmond, BC VGV2J3
(604) 278-3411
All the software described above is available upon request. BORIS staff would
appreciate knowing of any problems discovered with the software, but cannot
promise to fix them.
15. Data Access
15.1 Contact for Data Center/Data Access Information
These BOREAS data are available from the Earth Observing System Data and
Information System (EOS-DIS) 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
15.2 Procedures for Obtaining Data
BOREAS data may be obtained through the ORNL DAAC World Wide Web site at
http://www-eosdis.ornl.gov/ or users may place requests for data by telephone, electronic mail, or fax.
15.3 Output Products and Availability
Requested data can be provided electronically on the ORNL DAAC's anonymous FTP
site or on various media including, CD-ROMs, 8-MM tapes, or diskettes.
The complete set of BOREAS data CD-ROMs, entitled "Collected Data of the Boreal
Ecosystem-Atmosphere Study", edited by Newcomer, J., et al., NASA, 1999, are
also available.
16. Output Products and Availability
16.1 Tape Products
The level-3b AVHRR imagery can be made available on 8-mm magnetic 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. and F. Huang. 1993. User guide for the 1993 GEOCOMP products. NBIOME
Internal Report, Canada Centre for Remote Sensing, Ottawa, Ontario. 9 p.
Hussey, J.W. 1977. The TIROS-N NOAA Operational Satellite System. U.S.
Department of Commerce, NOAA/NESS.
Kidwell, K. 1991. NOAA Polar Orbiter Data User's Guide, NCDC/SDSD. (Updated from
original 1984 edition.)
Lauritson, et al. 1979. Data Extraction and Calibration of TIROS N/NOAA
Radiometers. NOAA Technical Memorandum NESS 107, U.S. Department of Commerce,
NOAA/NESS.
17.2 Journal Articles and Study Reports
Brown, O.B., J.W. Brown, and R.H. Evans. 1985. Calibration of Advanced Very High
Resolution Radiometer Infrared Observations. J. of Geoph. Res., 90:11667-11677.
Brown, R.J., Bernier, and G. Fedosejevs. l982. Geometric and Radiometric
Considerations of NOAA AVHRR Imagery. Proc. of the 8th International
Symposium on Machine Processing of Remotely Sensed Data. Purdue University,
Indiana. p. 374-381.
Cicone, R.C. and M.D. Metzer. 1982. Comparisons of Landsat MSS, Nimbus-7 CZCS,
and NOAA-6/7 AVHRR sensors for Land Use Analysis. Proc. of the 8th International
Symposium on Machine Processing of Remotely Sensed Data. Purdue University,
Indiana. p. 291-297.
Cihlar, J. and F. Huang. 1994. Effect of atmospheric correction and viewing
angle restriction on AVHRR composites. Canadian Journal for Remote Sensing 20:
132-137.
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.
Duggin, M.J., D. Piwinshi, V. Whitehead, and G. Tyland. 1982. Evaluation of
NOAA-AVHRR Data for Crop Assessment. Appl. Opt. 21:1873-1875.
Gray, T.I. and D.G. McCrary. 1981. Meteorological Satellite Data - A Tool to
Describe the Health of the World's Agriculture. AgRISTARS Report EW-N1-04042.
NASA/JSC. Houston, Texas. 7 p.
Greegor, D.H. and J. Norwine. 1981. A Gradient Model of Vegetation and Climate
Utilizing NOAA Satellite Imagery - Phase I: Texas Transect. AgRISTARS Report
JSC-17435. FC-J1-04176. NASA/JSC. Houston, Texas. 58 p.
Inoue, T. 1987. A Cloud Type Classification with NOAA-7 Split-Window
Measurements. J. Geophys. Res. 92:3991-4000.
Ormsby, J.P. 1982. Classification of Simulated and Actual NOAA-6 AVHRR Data for
Hydrological Land-Surface Feature Definition. IEEE Transactions on Geoscience
and Remote Sensing. GE-20:262-268.
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.
Schneider, S.R. and D.F. McGinnis. 1982. The NOAA/AVHRR: A New Satellite Sensor
for Monitoring Crop Growth. Proc. of the 8th International Symposium on Machine
Processing of Remotely Sensed Data. Purdue University, Indiana. p. 281-290.
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.
Taconet, O., R. Bernard, and D. Vidal-Madja. 1986. Evapotranspiration Over an
Agricultural Region Using a Surface Flux/Temperature Model Based on NOAA-AVHRR
Data. J. Climate Appl. Meteor. 25:284-307.
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.
Townshend, J. (Ed.). 1995. Global data sets for the land from AVHRR.
International Journal of Remote Sensing 15: 3315-3639 (special issue).
Townshend, J.R.G. and C.J. Tucker. 1981. Utility of AVHRR of NOAA-6 and -7 for
Vegetation Mapping. In Matching Remote Sensing Technologies and their
Applications Proceedings. Remote Sensing Society. London. p. 97-109.
Yates, H.W. and J.D. Tarpley. 1982. The Role of Meteorological Satellites in
Agricultural Remote Sensing. Proc. of the 8th International Symposium on
Machine Processing of Remotely Sensed Data. Purdue University, Indiana. p. 23-
32.
17.3 Archive/DBMS Usage Documentation
None.
18. Glossary of Terms
None.
19. List of Acronyms
AEAC - Albers Equal-Area Conic
APT - Automatic Picture Transmission
ASCII - American Standard Code for Information Interchange
AVHRR - Advanced Very High Resolution Radiometer
BIL - Band Interleaved by Line
BOREAS - BOReal Ecosystem-Atmosphere Study
BORIS - BOREAS Information System
BPI - Bytes Per Inch
CCRS - Canada Centre for Remote Sensing
CCT - Computer Compatible Tape
CD-ROM - Compact Disk-Read-Only Memory
DAAC - Distributed Active Archive Center
DAT - Digital Archive Tape
DSL - Digital Signal Level
EOS - Earth Observing System
EOSDIS - EOS Data and Information System
EROS - Earth Resources Observation System
fPAR - Fraction of Photosynthetically Active Radiation
GAC - Global Area Coverage
GEOCOMP - Geocoding and Compositing System
GMT - Greenwich Mean Time
GSFC - Goddard Space Flight Center
HRPT - High-Resolution Picture Transmission
IFC - Intensive Field Campaign
IFOV - Instantaneous Field-Of-View
I/O - Input/Output
LAC - Local Area Coverage
LAI - Leaf Area Index
LCC - Lambert Conformal Conic
LGSOWG - Landsat Ground Station Operational Working Group
LTWG - LGSAWG Technical Working Group
MRSC - Manitoba Remote Sensing Centre
NAD83 - North American Datum of 1983
NASA - National Aeronautics and Space Administration
NDVI - Normalizes 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
RMS - Root Mean Square
SOCC - Satellite Operations Control Center
SSA - Southern Study Area
SST - Sea Surface Temperature
TIROS - Television and Infrared Observation Satellite
URL - Uniform Resource Locator
UTM - Universal Transverse 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: 11-Sep-1997
Science Review: 05-Jan-1998
20.3 Document ID
20.4 Citation
The AVHRR-LAC level-3b images resulted from a joint development and processing
effort between BOREAS staff at CCRS and NASA GSFC. The data were acquired by
CCRS and processed by MRSC in Winnipeg, Manitoba. 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
EMITTED RADIATION
NOAA
REFLECTED RADIATION
AVHRR_L3b.doc
09/14/98