Filters: Tags: forest inventory and analysis (X)
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Some of the CYR rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - An aboveground live forest biomass map for the conterminous U.S., Alaska and Puerto Rico is derived from modeling field biomass estimates, collected nationwide by the USDA Forest Service Forest Inventory and Analysis (FIA) program, as functions of 250-m resolution satellite image products and other digital geographic layers....
Abstract: This dataset portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center. Â Purpose: The purpose of this dataset is to portray broad distribution patterns of forest cover in the United States and provide input to national scale modeling projects. The data should not be displayed at scales smaller...
A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, models were developed relating field-measured response variables to plot attributes serving as the predictor variables. The plot attributes came from intersecting plot coordinates with geospatial datasets. Consequently, these models serve as mapping models. The geospatial predictor variables included Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; land cover proportions and other data...
This dataset portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center.
This dataset portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center.
This dataset portrays 61 forest group types across the southeastern United States. These data were derived from a product created by the USFS Forest Inventory and Analysis (FIA) program and the Remote Sensing Applications Center (RSAC). Â The original dataset (accessible from the US Forest Service Website) consists of 141 forest types across the contiguous United States. The original dataset was downloaded on 12/13/2013, clipped to the southeastern states, Â and used in a generalization procedure which involved the application of a majority filter (8 neighbors, half replacement threshold) followed by a sieving process which removed pixels in groups of four or less by reassigning them to their nearest neighbor value....
This dataset portrays 141 forest types across Alaska. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, and ecoregions. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center.
Abstract: This dataset portrays 141 forest types across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center. Purpose: The purpose of this dataset is to portray broad distribution patterns of forest cover in the United States and provide input to national scale modeling projects. The data should not be displayed at scales smaller than...
The Interagency Vegetation Mapping Project (IVMP) provides maps of existing vegetation, canopy cover, size, and cover type for the entire range of the Northern Spotted Owl using satellite imagery from the Landsat Thematic Mapper (TM). This area is commonly called the FEMAT area, in reference to the area's analysis by the Forest Ecosystem Management Assessment Team. A regression modeling approach was used to predict vegetation characteristics from this Landsat data. This process involved the use of numerous sources of ancillary data, the most crucial being USFS, BLM, and Forest Inventory and Analysis (FIA) plot field data and plot photo interpreted information. This data served as training data in the regression...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: BLM,
Bureau of Land Management,
FEMAT,
FIA,
Forest inventory and analysis,
This dataset portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center.
This dataset portrays 11 forest group types across the southeastern United States. These data were derived from a product created by the USFS Forest Inventory and Analysis (FIA) program and the Remote Sensing Applications Center (RSAC). Â The original dataset (accessible from the US Forest Service Website) consists of 28 forest type groups across the contiguous United States. The original dataset was downloaded on 12/13/2013, clipped to the southeastern states, Â and used in a generalization procedure which involved the application of a majority filter (8 neighbors, half replacement threshold) followed by a sieving process which removed pixels in groups of four or less by reassigning them to their nearest neighbor...
This dataset portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center.
A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, models were developed relating field-measured response variables to plot attributes serving as the predictor variables. The plot attributes came from intersecting plot coordinates with geospatial datasets. Consequently, these models serve as mapping models. The geospatial predictor variables included Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; land cover proportions and other data...
This dataset consists of the average residual errors for the rulesets developed to predict biomass: http://app.databasin.org/app/pages/datasetPage.jsp?id=b0817400a441487baf1409580acc6620 The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis Program and the USFS Remote Sensing Applications Center.
This dataset consists of the average residual errors for the rulesets developed to predict biomass: http://app.databasin.org/app/pages/datasetPage.jsp?id=e44f9d6470de4df7a24cbc52ff665b47 The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis Program and the USFS Remote Sensing Applications Center.
Some of the YKL rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - An aboveground live forest biomass map for the conterminous U.S., Alaska and Puerto Rico is derived from modeling field biomass estimates, collected nationwide by the USDA Forest Service Forest Inventory and Analysis (FIA) program, as functions of 250-m resolution satellite image products and other digital geographic layers....
This dataset consists of the average residual errors for the rulesets developed to predict biomass: http://app.databasin.org/app/pages/datasetPage.jsp?id=503ca5e998f64443bc04c330d3a9fcc0 The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis Program and the USFS Remote Sensing Applications Center.
A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, models were developed relating field-measured response variables to plot attributes serving as the predictor variables. The plot attributes came from intersecting plot coordinates with geospatial datasets. Consequently, these models serve as mapping models. The geospatial predictor variables included Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; land cover proportions and other data...
A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, models were developed relating field-measured response variables to plot attributes serving as the predictor variables. The plot attributes came from intersecting plot coordinates with geospatial datasets. Consequently, these models serve as mapping models. The geospatial predictor variables included Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; land cover proportions and other data...
This dataset portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center.
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