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This dataset is the third (circa 2013) in a series of three 1-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation...
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This dataset was produced by the US Geological Survey as a supporting dataset to be used for the purpose of calculating stream gage basin characteristics in preparation for the South Carolina StreamStats application. This integer raster dataset represents runoff curve numbers for the combinations of hydrological soils groupings and land cover types within the South Carolina StreamStats study area. Soils data are from the USDA, NRCS SSURGO soils database and land cover data are USGS 2019 NLCD data. The dataset will be used in peak flow regression equations that are used to predict flow in South Carolina streams. The StreamStats application provides access to spatial analytical tools that are useful for water-resources...
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Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Acadia National Park, ArcGIS Pro, Arcpy, Autoclassification, Automation, All tags...
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Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Acadia National Park, ArcGIS Pro, Arcpy, Autoclassification, Automation, All tags...
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The U.S. Virgin Islands 2007 land cover, created as part of the USVIGAP analysis project supported by the USGS, is a forty-nine class land cover classification. The USVIGAP land cover is based primarily on the unsupervised classification of five Earth Observing 1 (EO-1) Advanced Land Imager (ALI) scenes acquired in 2007. The ALI scenes were processed, segmented into geoclimatic zones and classified individually. ASTER and Landsat 7 ETM+ imagery from 2008 and 2009 were used to complete areas of no data resulting from cloud and cloud shadow in the initial ALI classification. The land cover was created through the use of the spectral information derived from the satellite imagery and ancillary data such as geology,...
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Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Acadia National Park, ArcGIS Pro, Arcpy, Autoclassification, Automation, All tags...
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These data represent land cover and land use for the Crown of the Continent Ecosystem. The data are a compilation from multiple sources [Multi-Resolution Land Characteristics (MRLC) Consortium, Agriculture and Agri-Food Canada (AAFC), and the Canadian Forest Service (CFS)], Canadian data are circa 2000, US are circa 2001. VALUE: 0 = NoData; 20 = Water; 30 = Barren; 31 = Ice/Snow; 34 = Developed; 50 = Scrub/Shrub; 80 = Wetland; 110 = Grassland; 120 = Agriculture; 210 = Coniferous; 220 = Deciduous; 230 = Mixed. This dataset was published in November 2010. The dataset was updated in 2014 to fix several no-data pixels along the US-Canada border. This dataset was developed by the Crown Managers Partnership, as part of...
The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). The success of NLCD over nearly two decades is credited to the continuing collaborative...
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This dataset is the second (2013) of two 500-meter land use land cover (LULC) time-periods datasets (2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation using Esri’s ArcGIS Desktop...
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The Great Plains Landscape Conservation Cooperative (GPLCC, https://www.fws.gov/science/catalog) is a partnership that provides applied science and decision support tools to assist natural resource managers conserve plants, fish and wildlife in the mid- and short-grass prairie of the southern Great Plains. It is part of a national network of public-private partnerships — known as Landscape Conservation Cooperatives (LCCs, http://www.fws.gov/science/shc/lcc.html) — that work collaboratively across jurisdictions and political boundaries to leverage resources and share science capacity. The Great Plains LCC identifies science priorities for the region and helps foster science that addresses these priorities to support...
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This dataset is the second (circa 2000) in a series of three 1-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation...
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This dataset is the second (circa 2000) in a series of three 2-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources (exception is Tchad at 4 kilometers). To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to...
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This raster stack contains 15 probability layers representing the pixel-level predicted probability of membership in each species-specific vegetation class from 0 to 1. These probability layers can be used to generate class membership uncertainty maps or probabilistic class cover maps from the model outputs. They provide additional information beyond the discrete categorial land cover assignments.
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This dataset is the first (circa 1975) in a series of three 1-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation...
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The Great Plains Landscape Conservation Cooperative (GPLCC, https://www.fws.gov/science/catalog) is a partnership that provides applied science and decision support tools to assist natural resource managers conserve plants, fish and wildlife in the mid- and short-grass prairie of the southern Great Plains. It is part of a national network of public-private partnerships — known as Landscape Conservation Cooperatives (LCCs, http://www.fws.gov/science/shc/lcc.html) — that work collaboratively across jurisdictions and political boundaries to leverage resources and share science capacity. The Great Plains LCC identifies science priorities for the region and helps foster science that addresses these priorities to support...
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The Puerto Rico 2000 land cover, created as part of the Puerto Rico GAP Analysis project supported by the USGS, is a seventy-class land cover classification. The PRGAP land cover is based primarily on the unsupervised classification of eighteen Landsat 7 Enhanced Thematic Mapper + (ETM+) scenes acquired from 1999 - 2003. The Landsat 7 scenes were separated into wet and dry season imagery, mosaiced, and segmented based on geo-climatic zones. The land cover was created through the use of the spectral information derived from the satellite imagery and ancillary data such as geology, topography, hydrology and land use history. The Puerto Rico GAP 2000 land cover product represents the first time a 15 meter spatial resolution...
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Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Acadia National Park, ArcGIS Pro, Arcpy, Autoclassification, Automation, All tags...
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This dataset is the first (circa 1975) in a series of three 2-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources (exception is Tchad at 4 kilometers). To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to...
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This dataset is the third (2013) in a series of three 2-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources (exception is Tchad at 4 kilometers). To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate...
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This dataset is the first (circa 2000) of two 500-meter land use land cover (LULC) time-periods datasets (2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation using Esri’s ArcGIS Desktop...


map background search result map search result map 2010 Cropland Data Layer for the Great Plains Landscape Conservation Cooperative Land Cover Gap Analysis Project for the Great Plains Landscape Conservation Cooperative Puerto Rico 2000 GAP Land Cover U.S. Virgin Islands 2007 GAP Land Cover Land Use & Land Cover in the Crown of Continent Ecosystem c2000 Gambia Land Use Land Cover 1975 Gambia Land Use Land Cover 2000 Gambia Land Use Land Cover 2013 Capo Verde, Land Use Land Cover 2000 Capo Verde, Land Use Land Cover 2013 West Africa Land Use Land Cover 1975 West Africa Land Use Land Cover 2000 West Africa Land Use Land Cover 2013 Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Perpetual Hazards Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Event Hazards Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Maximum Change Likelihood Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Hazard Impact Type Gridded South Carolina StreamStats Runoff Curve Numbers by NLCD Landcover and SSURGO Soils Class High-Resolution Land Cover Maps of Lāna‘i, Hawai‘i, 2020 - Class Probability Stack High-Resolution Land Cover Maps of Lāna‘i, Hawai‘i, 2020 - Class Probability Stack U.S. Virgin Islands 2007 GAP Land Cover Puerto Rico 2000 GAP Land Cover Gambia Land Use Land Cover 1975 Gambia Land Use Land Cover 2000 Gambia Land Use Land Cover 2013 Capo Verde, Land Use Land Cover 2000 Capo Verde, Land Use Land Cover 2013 Land Use & Land Cover in the Crown of Continent Ecosystem c2000 Gridded South Carolina StreamStats Runoff Curve Numbers by NLCD Landcover and SSURGO Soils Class Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Maximum Change Likelihood Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Hazard Impact Type Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Perpetual Hazards Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Event Hazards Land Cover Gap Analysis Project for the Great Plains Landscape Conservation Cooperative 2010 Cropland Data Layer for the Great Plains Landscape Conservation Cooperative West Africa Land Use Land Cover 2000 West Africa Land Use Land Cover 2013 West Africa Land Use Land Cover 1975