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100 results for “AVHRR”
Daily surface all-wave net radiation over global land (2018-2019) from AVHRR data
<p>Surface net radiation, representing surface radiation energy balance, is closely related to several land processes, such as evapotranspiration, photosynthesis, and turbulent and conductive heat fluxes. Reanalysis products can provide a long-term surface net radiation; however, their coarse spatial resolution and large uncertainties hinder us from well applicating the data at a regional scale. Satellite products also include surface net radiation retrievals with high accuracy. The short time span of satellite products (i.e., GLASS product) makes these satellite products not suitable for long-term climate change study. Therefore, we used a deep learning method to upscale in situ measurements collected from global-distributed sites to generate a daily surface net radiation product with 0.05° spatial resolution from AVHRR data (2018-2019). </p> <p>After comprehensive validation, the RMSE of AVHRR net radiation product was ~26 Wm<sup>-2</sup>, which is generally better than some current reanalysis and satellite products.</p>
Daily surface all-wave net radiation over global land (1995-2006) from AVHRR data
<p>Surface net radiation, representing surface radiation energy balance, is closely related to several land processes, such as evapotranspiration, photosynthesis, and turbulent and conductive heat fluxes. Reanalysis products can provide a long-term surface net radiation; however, their coarse spatial resolution and large uncertainties hinder us from well applicating the data at a regional scale. Satellite products also include surface net radiation retrievals with high accuracy. The short time span of satellite products (i.e., GLASS product) makes these satellite products not suitable for long-term climate change study. Therefore, we used a deep learning method to upscale in situ measurements collected from global-distributed sites to generate a daily surface net radiation product with 0.05° spatial resolution from AVHRR data (1995-2006). </p> <p>After comprehensive validation, the RMSE of AVHRR net radiation product was ~26 Wm<sup>-2</sup>, which is generally better than some current reanalysis and satellite products.</p>
Daily surface all-wave net radiation over global land (1981-1994) from AVHRR data
<p>Surface net radiation, representing surface radiation energy balance, is closely related to several land processes, such as evapotranspiration, photosynthesis, and turbulent and conductive heat fluxes. Reanalysis products can provide a long-term surface net radiation; however, their coarse spatial resolution and large uncertainties hinder us from well applicating the data at a regional scale. Satellite products also include surface net radiation retrievals with high accuracy. The short time span of satellite products (i.e., GLASS product) makes these satellite products not suitable for long-term climate change study. Therefore, we used a deep learning method to upscale in situ measurements collected from global-distributed sites to generate a daily surface net radiation product with 0.05° spatial resolution from AVHRR data (1981-1994). </p> <p>After comprehensive validation, the RMSE of AVHRR net radiation product was ~26 Wm<sup>-2</sup>, which is generally better than some current reanalysis and satellite products.</p>
Daily surface all-wave net radiation over global land (2007-2017) from AVHRR data
<p>Surface net radiation, representing surface radiation energy balance, is closely related to several land processes, such as evapotranspiration, photosynthesis, and turbulent and conductive heat fluxes. Reanalysis products can provide a long-term surface net radiation; however, their coarse spatial resolution and large uncertainties hinder us from well applicating the data at a regional scale. Satellite products also include surface net radiation retrievals with high accuracy. The short time span of satellite products (i.e., GLASS product) makes these satellite products not suitable for long-term climate change study. Therefore, we used a deep learning method to upscale in situ measurements collected from global-distributed sites to generate a daily surface net radiation product with 0.05° spatial resolution from AVHRR data (2007-2017). </p> <p>After comprehensive validation, the RMSE of AVHRR net radiation product was ~26 Wm<sup>-2</sup>, which is generally better than some current reanalysis and satellite products.</p>
Daily surface all-wave net radiation over global land from AVHRR data (1981—2019)
<p>Surface net radiation, representing surface radiation energy balance, is closely related to several land processes, such as evapotranspiration, photosynthesis, and turbulent and conductive heat fluxes. Reanalysis products can provide a long-term surface net radiation; however, their coarse spatial resolution and large uncertainties hinder us from well applicating the data at a regional scale. Satellite products also include surface net radiation retrievals with high accuracy. The short time span of satellite products (i.e., GLASS product) makes these satellite products not suitable for long-term climate change study. Therefore, we used a deep learning method to upscale in situ measurements collected from global-distributed sites to generate a daily surface net radiation product with 0.05° spatial resolution from AVHRR data (1981-2019). After comprehensive validation, the RMSE of AVHRR net radiation product was ~26 Wm-2, which is generally better than some current reanalysis and satellite products.</p> <p> </p> <p> </p>
GHRSST NOAA/STAR Metop-B AVHRR FRAC ACSPO v2.80 0.02 L3U Dataset (GDS v2)
This L3U (Level 3 Uncollated) dataset contains global daily Sea Surface Temperature (SST) on a 0.02 degree grid resolution. It is produced by the National Oceanic and Atmospheric Administration (NOAA) Advanced Clear Sky Processor for Ocean (ACSPO) using L2P (Level 2 Preprocessed) product acquired from the Meteorological Operational satellite B (Metop-B) Advanced Very High Resolution Radiometer 3 (AVHRR/3) (https://podaac.jpl.nasa.gov/dataset/AVHRRF_MB-STAR-L2P-v2.80 ) in Full Resolution Area Coverage (FRAC) mode as input. It is distributed as 10-minute granules in netCDF-4 format, compliant with the Group for High Resolution Sea Surface Temperature (GHRSST) Data Specification version 2 (GDS2). There are 144 granules per 24-hour interval. Fill values are reported in all invalid pixels, including land pixels with >5 km inland. For each valid water pixel (defined as ocean, sea, lake or river), and up to 5 km inland, the following major layers are reported: SSTs and ACSPO clear-sky mask (ACSM; provided in each grid as part of l2p_flags, which also includes day/night, land, ice, twilight, and glint flags). Only input L2P SSTs with QL=5 were gridded, so all valid SSTs are recommended for the users. Per GDS2 specifications, two additional Sensor-Specific Error Statistics layers (SSES bias and standard deviation) are reported in each pixel with valid SST. Ancillary layers include wind speed and ACSPO minus reference Canadian Meteorological Centre (CMC) Level 4 (L4) SST. The ACSPO Metop-B AVHRR FRAC L3U product is monitored and validated against iQuam in situ data (Xu and Ignatov, 2014) in the NOAA SST Quality Monitor (SQUAM) system (Dash et al, 2010). SST imagery and clear-sky mask are evaluated, and checked for consistency with L2P and other satellites/sensors SST products, in the NOAA ACSPO Regional Monitor for SST (ARMS) system. More information about the dataset is found at AVHRRF_MB-STAR-L2P-v2.80 and in (Pryamitsyn et al., 2021).
GHRSST Level 2P Global Sea Surface Temperature v2.0 from the AVHRR on the MetOp-A satellite produced by NAVO
A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P data set containing multi-channel Sea Surface Temperature (SST) retrievals derived in real-time from the Advanced Very High Resolution Radiometer (AVHRR) level-1B data from the Meteorological Operational-A (MetOp-A) satellite. The SST data in this data set are used operationally in oceanographic analyses and forecasts by the US Naval Oceanographic Office (NAVO). The MetOp satellite program is a European multi-satellite program to provide weather data services for monitoring climate and improving weather forecasts. MetOp-A, MetOp-B and Metop-C were respectively launched on 19 Oct 2006, 17 September 2012 and 7 November 2018. The program was jointly established by the European Space Agency (ESA) and the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) with the US National Oceanic and Atmospheric Administration (NOAA) contributing the AVHRR sensor. AVHRR instruments measure the radiance of the Earth in 5 (or 6) relatively wide spectral bands. The first two are centered around the red (0.6 micron) and near-infrared (0.9 micron) regions, the third one is located around 4 (3.6) micron, and the last two sample the emitted thermal radiation, around 11 and 12 micron, respectively. The legacy 5 band instrument is known as AVHRR/2 while the more recent version, the AVHRR/3 (first carried on the NOAA-15 platform), acquires data in a 6th channel located at 1.6 micron. Typically, the 11 and 12 micron channels are used to derive SST sometimes in combination with the 3.5 micron channel. The swath of the AVHRR sensor is a relatively large 2400 km. All MetOp platforms are sun synchronous and generally view the same earth location twice a day (latitude dependent). The ground native resolution of the AVHRR instruments is approximately 1.1 km at nadir and degrades off nadir. This particular data set is produced from legacy Global Area Coverage (GAC) data that are derived from a sample averaging of the full resolution global AVHRR data. Four out of every five samples along the scan line are used to compute on average value and the data from only every third scan line are processed, yielding an effective 4 km spatial resolution at nadir. The v2.0 is the updated version from current v1.0 with extensive algorithm improvements and upgrades. The major improvements include: 1) Significant changes in contaminant/cloud detection; 2) Increased the spatial resolution from 9 km to 4 km; 3) Updated compliance with GDS2, ACDD 1.3, and CF 1.6; and 4) Removed the dependency on the High-resolution Infrared Radiation Sounder (HIRS) sensor (only available to MetOp-A/B), thus allowing for the consistent inter-calibration and the processing of MetOp-A/B/C data
ABoVE: AVHRR-Derived Forest Fire Burned Area-Hot Spots, Alaska and Canada, 1989-2000
This dataset provides annual forest fire burned area and daily hotspot products developed using data acquired from the Advanced Very-High-Resolution Radiometer (AVHRR) instruments carried aboard two NOAA polar-orbiting satellites (NOAA-11 and NOAA-14). The fire products were generated over 12 fire seasons (1st May - 31st October) from 1989-2000 across North America at 1-km resolution and subset to the ABoVE spatial domain of Alaska and Canada.
GHRSST Level 3C North Atlantic Regional Subskin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on NOAA-19 (GDS2 version)
A Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 platform (launched 6 Feb 2009). This particular dataset is produced by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), Ocean and Sea Ice Satellite Application Facility (OSI SAF) in France. The AVHRR is a space-borne scanning sensor on the National Oceanic and Atmospheric Administration (NOAA) family of Polar Orbiting Environmental Satellites (POES) having a operational legacy that traces back to the Television Infrared Observation Satellite-N (TIROS-N) launched in 1978. AVHRR instruments measure the radiance of the Earth in 5 (or 6) relatively wide spectral bands. The first two are centered around the red (0.6 micrometer) and near-infrared (0.9 micrometer) regions, the third one is located around 3.5 micrometer, and the last two sample the emitted thermal radiation, around 11 and 12 micrometers, respectively. The legacy 5 band instrument is known as AVHRR/2 while the more recent version, the AVHRR/3 (first carried on the NOAA-15 platform), acquires data in a 6th channel located at 1.6 micrometer. Typically the 11 and 12 micron channels are used to derive sea surface temperature (SST) sometimes in combination with the 3.5 micron channel. The highest ground resolution that can be obtained from the current AVHRR instruments is 1.1 km at nadir. The NOAA-19 platform is sun synchronous generally viewing the same earth location twice a day (latitude dependent) due to the relatively large AVHRR swath of approximately 2400 km. The NAR products are SST fields derived from 1km AVHRR data that are re-mapped onto a 0.02 degree equal angle grid. In the processing chain, global AVHRR level 1b data are acquired at Centre de Meteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. A cloud mask is applied and SST is retrieved from the AVHRR infrared (IR) channels by using a multispectral technique. This dataset adheres to the GHRSST Data Processing Specification (GDS) version 2 format specifications.
SAFARI 2000 Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)
This data set consists of a southern African subset of the University of Maryland (UMD) 8-km Global Land Cover product in ASCII GRID and binary image files formats. Over the past several years, researchers have increasingly turned to remotely sensed data to improve the accuracy of data sets that describe the geographic distribution of land cover at regional and global scales. To develop improved methodologies for global land cover classifications as well as to provide global land cover products for immediate use in global change research, researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland (UMD) have employed the NASA/NOAA Pathfinder Land (PAL) data set with a spatial resolution of 8 km. This data set has a length of record of 14 years (1981-1994), providing the ability to test the stability of classification algorithms. Furthermore, this data set includes red, infrared, and thermal bands in addition to the Normalized Difference Vegetation Index (NDVI). Inclusion of these additional bands improves discrimination between cover types. The project aim is to develop and validate global land cover data sets and to develop advanced methodologies for more realistically describing the vegetative land surface based on satellite data. The 8-km global land cover product was derived by testing several metrics that describe the temporal dynamics of vegetation over an annual cycle. These metrics were applied to 1984 PAL data at 8-km resolution to derive a global land cover classification product using a decision tree classifier. The final product contains 13 land cover classes. The original 8-km global land cover product is available for download from the Global Land Cover Facility (GLCF) web site. Additional information and references on this data set can be found at the GLCF web site as well as at the LGRSS web site (link provided at the GLCF web site ). More information can be found at: ftp://daac.ornl.gov/data/safari2k/vegetation_wetlands/land_cover_data_8km/comp/glcf8km_readme.pdf.
SAFARI 2000 Land Cover from AVHRR, 1-Deg, 1987 (Defries and Townshend)
This data set consists of a southern African subset of the University of Maryland (UMD) 1-degree Global Land Cover product in ASCII GRID and binary image formats. The UMD 1-degree Global Land Cover product was produced by researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at UMD. The product is based on Advanced Very High Resolution Radiometer (AVHRR) maximum monthly composites for 1987 of Normalized Difference Vegetation Index (NDVI) values at approximately 8-km resolution, averaged to one-by-one degree resolution. This coarse- resolution data set was used as the basis for a supervised classification of eleven cover types that broadly represent the major biomes of the world. Because of missing values at high latitudes, the Pathfinder AVHRR data set for 1987 for summer monthly NDVI and red reflectance values were used to distinguish the following cover types: tundra, high latitude deciduous forest and woodland, coniferous evergreen forest and woodland. The 1-degree global land cover product is available for download from the Global Land Cover Facility (GLCF) web site. The data are available as a global coverage in both binary and ASCII format. Additional information and references on this data set can be found at the GLCF web site as well as at the LGRSS web site (link provided at the GLCF web site ) and in the readme file found along with the data [ ftp://daac.ornl.gov/data/safari2k/vegetation_wetlands/land_cover_data_1deg/comp/glcf1deg_readme.pdf].
GHRSST L3C global sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-A) (GDS V2) produced by OSI SAF
A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) on the European Meteorological Operational-A (MetOp-A) platform (launched 19 Oct 2006). The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), Ocean and Sea Ice Satellite Application Facility (OSI SAF) is producing SST products in near real time from Metop/AVHRR. Global AVHRR level 1b data are acquired at Meteo-France/Centre de Meteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. SST is retrieved from the AVHRR infrared channels (3.7, 10.8 and 12.0 micrometer) using a multispectral algorithm. Atmospheric profiles of water vapor and temperature from a numerical weather prediction model, together with a radiatiave transfer model, are used to correct the multispectral algorithm for regional and seasonal biases due to changing atmospheric conditions. This global L3C product isderived from full resolution AVHRR l1b data that are re-mapped onto a 0.05 degree grid twice daily. The product format is compliant with the GHRSST Data Specification (GDS) version 2.
LBA Regional Land Cover from AVHRR, 1-km, Version 1.2 (IGBP)
The data set consists of a LBA study area subset of the IGBP DISCover Data Set. The DISCover data set is one data set contained within the Global Land Cover Characteristics Data Base. The U.S. Geological Survey (USGS), the University of Nebraska-Lincoln (UNL), and the European Commission's Joint Research Centre (JRC) have generated a 1-km resolution global land cover characteristics data base for use in a wide range of environmental research and modeling applications. The global land cover characteristics data base was developed on a continent-by-continent basis. All continental data bases share the same map projections (Interrupted Goode Homolosine and Lambert Azimuthal Equal Area), have 1-km nominal spatial resolution, and are based on 1-km Advanced Very High Resolution Radiometer (AVHRR) data spanning April 1992 through March 1993. Each data base contains unique elements based on the geographic aspects of the specific continent. In addition, a core set of derived thematic maps produced through the aggregation of seasonal land cover regions are included in each continental data base. The continental data bases are combined to make six global data sets, each representing a different landscape based on a particular classification legend. The following derived data sets are included in the global land cover data base: * Global Ecosystems (Olson, 1994a, 1994b) * IGBP Land Cover Classification (Belward, 1996) * U.S. Geological Survey Land Use/Land Cover System(Anderson & others, 1976) * Simple Biosphere Model (Sellers and others, 1986) * Simple Biosphere 2 Model (Sellers and others, 1996) * Biosphere-Atmosphere Transfer Scheme (Dickinson and others, 1986) The legends for each of these derived data sets can be found in the documentation accompanying the data. For a description of the methodology for the global data base, see the global readme file found under the EROS Data Center DAAC home page (http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html).
BOREAS RSS-07 Regional LAI and FPAR Images From Ten-Day AVHRR-LAC Composites
The BOREAS RSS-07 team focused their efforts on developing and validating procedures and algorithms that would allow the retrieval of LAI from remotely sensed vegetation indices. This data set contains images of LAI and FPAR that were produced from the AVHRR Level-4c ten-day composite NDVI images produced at CCRS for the three summer IFCs in 1994. The algorithms were developed based on ground measurements and Landsat TM images (Chen and Cihlar, 1996; Chen, 1996b). The data are provided in binary image format files. Companion files include example thumbnail images that may be viewed and the image data files downloaded using a convenient viewer utility.
GHRSST L3C global sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-B) (GDS V2) produced by OSI SAF
A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) on the European Meteorological Operational-B (MetOp-B) platform (launched 17 Sep 2012). The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), Ocean and Sea Ice Satellite Application Facility (OSI SAF) is producing SST products in near real time from Metop/AVHRR. Global AVHRR level 1b data are acquired at Meteo-France/Centre de Meteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. SST is retrieved from the AVHRR infrared channels (3.7, 10.8 and 12.0 micrometer) using a multispectral algorithm. Atmospheric profiles of water vapor and temperature from a numerical weather prediction model, together with a radiatiave transfer model, are used to correct the multispectral algorithm for regional and seasonal biases due to changing atmospheric conditions. This global L3C product isderived from full resolution AVHRR l1b data that are re-mapped onto a 0.05 degree grid twice daily. The product format is compliant with the GHRSST Data Specification (GDS) version 2.
GHRSST Level 2P Global Sea Surface Temperature v2.0 from the AVHRR on the MetOp-B satellite produced by NAVO
A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P data set containing multi-channel Sea Surface Temperature (SST) retrievals derived in real-time from the Advanced Very High Resolution Radiometer (AVHRR) level-1B data from the Meteorological Operational-B (MetOp-B) satellite. The SST data in this data set are used operationally in oceanographic analyses and forecasts by the US Naval Oceanographic Office (NAVO). The MetOp satellite program is a European multi-satellite program to provide weather data services for monitoring climate and improving weather forecasts. MetOp-A, MetOp-B and Metop-C were respectively launched on 19 Oct 2006, 17 September 2012 and 7 November 2018. The program was jointly established by the European Space Agency (ESA) and the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) with the US National Oceanic and Atmospheric Administration (NOAA) contributing the AVHRR sensor. AVHRR instruments measure the radiance of the Earth in 5 (or 6) relatively wide spectral bands. The first two are centered around the red (0.6 micron) and near-infrared (0.9 micron) regions, the third one is located around 4 (3.6) micron, and the last two sample the emitted thermal radiation, around 11 and 12 micron, respectively. The legacy 5 band instrument is known as AVHRR/2 while the more recent version, the AVHRR/3 (first carried on the NOAA-15 platform), acquires data in a 6th channel located at 1.6 micron. Typically, the 11 and 12 micron channels are used to derive SST sometimes in combination with the 3.5 micron channel. The swath of the AVHRR sensor is a relatively large 2400 km. All MetOp platforms are sun synchronous and generally view the same earth location twice a day (latitude dependent). The ground native resolution of the AVHRR instruments is approximately 1.1 km at nadir and degrades off nadir. This particular data set is produced from legacy Global Area Coverage (GAC) data that are derived from a sample averaging of the full resolution global AVHRR data. Four out of every five samples along the scan line are used to compute on average value and the data from only every third scan line are processed, yielding an effective 4 km spatial resolution at nadir. The v2.0 is the updated version from current v1.0 with extensive algorithm improvements and upgrades. The major improvements include: 1) Significant changes in contaminant/cloud detection; 2) Increased the spatial resolution from 9 km to 4 km; 3) Updated compliance with GDS2, ACDD 1.3, and CF 1.6; and 4) Removed the dependency on the High-resolution Infrared Radiation Sounder (HIRS) sensor (only available to MetOp-A/B), thus allowing for the consistent inter-calibration and the processing of MetOp-A/B/C data
GHRSST NOAA/STAR Metop-C AVHRR FRAC ACSPO v2.80 1km L2P Dataset (GDS v2)
The MetOp First Generation (FG) is a European multi-satellite program jointly established by ESA and EUMETSAT, comprising three satellites, MetOp-A, -B and -C. The primary sensor onboard MetOp-FG, the Advanced Very High Resolution Radiometer/3 (AVHRR/3) contributed by NOAA, measures Earth emissions and reflectances in 5 out of 6 available bands (centered at 0.63, 0.83, 1.61, 3.7, 11 and 12 microns), in a swath of 2,600km from an 817km altitude. These data are collected in a Full Resolution Area Coverage (FRAC) mode, with pixel size of 1.1km at nadir. Metop-C launched on 7 November 2018 is the third and last in the MetOp-FG series. The NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) Level 2 Preprocessed (L2P) SST product is derived at the full AVHRR FRAC resolution and reported in 10 minute granules in NetCDF4 format, compliant with the GHRSST Data Specification version 2 (GDS2). Subskin SSTs are derived using the regression Nonlinear SST (NLSST) algorithm, which employs three bands (3.7, 11 and 12 microns) at night and two bands (11 and 12 microns) during the day. The ACSPO AVHRR FRAC L2P product is monitored and validated against quality controlled in situ data, provided by the NOAA in situ SST Quality Monitor system (iQuam; Xu and Ignatov, 2014, https://doi.org/10.1175/JTECH-D-13-00121.1 ), in another NOAA system, SST Quality Monitor (SQUAM; Dash et al, 2010, https://doi.org/10.1175/2010JTECHO756.1 ). SST imagery and clear-sky masking are continuously evaluated, and checked for consistency with other sensors and platforms, in the ACSPO Regional Monitor for SST (ARMS) system. MetOp-A orbital characteristics and AVHRR/3 sensor performance are tracked in the NOAA 3S system (He et al., 2016, https://doi.org/10.3390/rs8040346 ).The L2P Near Real Time (NRT) SST files are archived at PO.DAAC with 3-6 hours latency, and then replaced by the Re-ANalysis (RAN) SST after about 2 months later with identical file names. Two features can be used to identify them: different file name time stamps and netCDF global attribute metadata source=NOAA-NCEP-GFS for NRT and source=MERRA-2 for RAN. A reduced size (0.45GB/day), equal-angle gridded (0.02-deg resolution) ACSPO L3U product is available at https://doi.org/10.5067/GHMTC-3US28
BOREAS Level-4b AVHRR-LAC Ten-Day Composite Images: At-Sensor Radiance
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-4b data are gridded, 10-day composites of at-sensor radiance values 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. Companion files include example thumbnail images that may be viewed and the image data files downloaded using a convenient viewer utility.
ISLSCP II AVHRR Albedo and BRDF, 1995
This Albedo and BRDF (Bidirectional Reflectance Distribution Function) data set contains three files containing BRDF parameters, white- sky albedo and black-sky albedo at solar noon for three bands ((350-680nm, 680-3000nm, and 350-30000nm)derived from AVHRR (Advanced Very High Resolution Radiometer). These data are available at spatial resolutions of quarter, half, and one degree. Black-sky albedo (direct beam contribution) and white-sky (Completely diffuse contribution) can be linearly combined as a function of the fraction of diffuse skylight (itself a function of optical depth) to provide an actual or instantaneous albedo at local solar noon.
LBA Regional Land Cover from AVHRR, 1-km, 1992-1993 (Hansen et al.)
This data set is a subset of Hansen et al. (1999), "1 km Global Land Cover Data Set Derived from AVHRR," which was developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 N to 25 S, longitude 30 to 85 W). The data are in ASCII GRID file format.In recent years, researchers have increasingly turned to remotely sensed data to improve the accuracy of data sets that describe the geographic distribution of land cover at regional and global scales. To develop improved methodologies for global land cover classifications as well as to provide global land cover products for immediate use in global change research, LGRSS researchers have employed the NASA/NOAA Pathfinder AVHRR Land (PAL) data set with a spatial resolution of 1 km. The PAL data set has a record length of 14 years (1981-1994), providing the ability to test the stability of classification algorithms. The PAL data set includes red, infrared, and thermal bands in addition to the Normalized Difference Vegetation Index (NDVI). Inclusion of these additional bands improves discrimination between cover types. The LGRSS researchers' aim was to develop and validate global land cover data sets and to develop advanced methodologies for more realistically describing the vegetative land surface based on satellite data.The 1-km global land cover product was created from 1992-1993 local area coverage (LAC) AVHRR data. The global land cover product is available for download from the University of Maryland's Global Land Cover Facility (GLCF) Web site (http://glcf.umiacs.umd.edu/data/landcover/index.shtml). Forty-one metrics were developed to describe global vegetation phenology, and these data were used to make the 1-km land cover map. The final product contains 13 land cover classes.More information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/land_cover_data_1km/comp/glcf1km_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
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