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