The data set consists of a subset for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 deg to 30 deg W, latitude 25 deg S to 10 deg N) of the 5-min resolution Global Potential Vegetation data set developed by Navin Ramankutty and Jon Foley at the University of Wisconsin. Data are available in both ASCII GRID and binary image file formats.The original map was derived at a 5-min resolution and contains natural vegetation classified into 15 types.

An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Vegetation

This data set is a subset of an 8-km global land cover product (DeFries et al. 1998). 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.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 at the University of Maryland employed the NASA/NOAA Pathfinder AVHRR Land (PAL) data set with a spatial resolution of 8 km. The PAL data set has a length of record of 14 years (1981-1994), providing the ability to test the stability of classification algorithms. Furthermore, the 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's 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 global land cover product (Defries et al. 1998) 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 University of Maryland's Global Land Cover Facility (GLCF) Web site (http://glcf.umiacs.umd.edu/data/landcover/index.shtml). Additional information and references on this data set can be found at the GLCF Web site, as well as at the LGRSS Web site (http://www.geog.umd.edu/LGRSS/intro.html). More information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/comp/land_cover_data_8km/glcf8km_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.

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.

This data set is a subset of a global vegetation and soils data set by Wilson and Henderson-Sellers (1985a). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The data are in ASCII GRID format.The original global data set (Wilson and Henderson-Sellers 1985a) is an archive of soil type and land cover data derived for use in general circulation models (GCMs). The data were collated from maps depicting natural vegetation, forestry, agriculture, land use, and soil, and they were archived at a resolution of 1 latitude by 1 longitude. The data set indicates soil type, soil data reliability, primary vegetation, secondary vegetation, and land cover data reliability. Approximately 50 land cover classifications are used, including categories for agricultural and urban uses. The inclusion of secondary vegetation type is particularly useful in areas with cover types that may have a fragmented distribution, such as in areas of urban development. The soil type data are classified according to climatically important properties for GCMs, and they indicate color (light, medium, or dark), texture, and drainage quality of the soil. The land cover data are compatible with the soils data, forming a coherent and consistent data set. The reliability of the land cover data is ranked on a scale of 1 to 5 (high to low). The reliability of the soil data is ranked as high, good, moderate, fair, or poor.Recommendations for the use of these data, as well as more detailed information can be found in Wilson and Henderson-Sellers (1985b).Further data set information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/wilhend/comp/wilhend_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.

This data set is a subset of a global croplands data set (Ramankutty and Foley 1999a). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The data are in ASCII GRID format at 5-min resolution.Navin Ramankutty and Jonathan Foley, of the Center for Sustainability and the Global Environment (SAGE) at the University of Wisconsin, developed a global, spatially explicit data set of reconstructed historical croplands from 1700 to 1992. The method for historical reconstruction used a simple algorithm that linked contemporary satellite data and historical cropland inventory data. A spatially explicit croplands data set for 1992 was first derived by calibrating a satellite-derived land cover classification data set against cropland inventory data for 1992. This derived data set was then used within a simple land cover change model, along with historical cropland inventory data, to derive spatially explicit maps of historical croplands. The global data set was restricted to a representation of permanent croplands (i.e., excluding shifting cultivation), which follows the Food and Agriculture Organization (FAO) definition of arable lands and permanent crops. Data values represent fraction of grid cell in croplands.Data for the LBA study area are available for the years 1900, 1910, 1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, and 1992. Although the global croplands data set contains data representing croplands since 1700, essentially no croplands were in the LBA study area until 1900. Data from previous years were excluded at the suggestion of the data originator.More information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/historical_croplands/comp/uwcrop_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.

This data set contains proportional estimates for the vegetative cover types of woody vegetation, herbaceous vegetation, and bare ground over the Amazon Basin for the period 2000-2001. These products were derived from all seven bands of the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellite. A set of MODIS 32-day composites were used to create the vegetation cover types using the Vegetation Continuous Fields (VCF) (Hansen et al., 2002) approach which shows how much of a land cover such as "forest" or "grassland" exists anywhere on the land surface. The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated.The original MODIS products are 500-m spatial resolution and are derived from 2000-2001 data products. The data were resampled to 1-km resolution for the regional study under this project, and provided as 3 separate cover type files in ENVI and GeoTIFF file formats that are provided in six zipped files. These products are registered to the rest of the regional data sets over the Amazon basin. These data are also available for download from the Global Land Cover Facility Website (http://modis.umiacs.umd.edu/).

This data set is a subset of the IGBP DISCover data set, which was derived from the Global Land Cover Characteristics database. The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 deg N to 25 deg S, longitude 30 to 85 W). The data are at 1-km resolution in ASCII GRID format.

This data set is a subset of Olson et al. (1985, 2000) "Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation." 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 format."Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation" is a computerized database used to generate a global vegetation map of 44 different land ecosystem complexes (mosaics of vegetation or landscapes) comprising seven broad groups. The map is derived from patterns of preagricultural vegetation, modern areal surveys, and intensive biomass data from research sites. Work on the database was begun in 1960 and completed in 1980.Ecosystem complexes are defined for each 0.5-degree grid cell, reflecting the major climatic, topographic, and land-use patterns. Numeric codes are assigned to each vegetation type. Classifications include natural as well as human managed/modified complexes such as mainly cropped, residential, commercial, and park. The complexes are ranked by estimated organic carbon in the mass of live plants given in units of kilograms of carbon per square meter. Counting the cells of each type and adding their areas give total area estimates for the ecosystem complexes. Multiplying by carbon estimates gives corresponding estimates of carbon by ecosystem complex with in the LBA study area. The results help define the role of the terrestrial biosphere in the global carbon cycle.Information about the ecosystem classifications, as well as the procedure used to create the LBA subset can be found at ftp://daac.ornl.gov/data/lba/carbon_dynamics/olson/comp/olson_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.Carbon in Live Vegetation is a computerized database, used to generate a global vegetation map of 44 different land ecosystem complexes (mosaics of vegetation or landscapes) comprising seven broad groups.

This data set consists of a southern African subset of the 5-min resolution Global Potential Vegetation data set developed by Navin Ramankutty and Jon Foley at the University of Wisconsin. Data are available in both ASCII GRID and binary image file formats.