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This dataset provides an estimate of water-based recreation travel corridors, based on a combination of wild and scenic rivers, and major rivers selected from NHD that were listed on the BLM rivers website. All reaches of these rivers were selected, as insufficient information exists to determine what segments may or may not be open to recreation. Other areas may be open to water-based recreation travel than are represented in this dataset.
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This dataset provides an estimate of water-based recreation travel corridors, based on a combination of wild and scenic rivers, and major rivers selected from NHD that were listed on the BLM rivers website. All reaches of these rivers were selected, as insufficient information exists to determine what segments may or may not be open to recreation. Other areas may be open to water-based recreation travel than are represented in this dataset.
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This dataset provides a measure of near-term high development, as an integration of several factors representing landscape development. This measure was calculated using a fuzzy logic model, which is represented in graphical format in \Vector\Change_Agents\Development\Documentation\COP_DV_logic_models.pptx This dataset represents the combination of energy, agriculture, urban, and recreation development. Original source data were summarized to 4KM reporting unit, and converted to fuzzy values (rescaled on a -1 to 1 value range) for input to the fuzzy logic model. These data include: utility lines, pipelines (from BLM), oil/gas wells (from BLM), oil/gas well anticipated development (from Holly Copeland 2009), mines...
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Each community in the study area is served by an isolated grid, with its own generation and distribution infrastructure. All energy infrastructure in each community is within the community’s footprint. Barrow and Prudhoe Bay, the two largest population centers, rely completely on natural gas for generation of electricity. Nuiqsut relies both on natural gas and diesel. Other than Barrow and Prudhoe Bay, all other communities have small demand loads, and thus only generate less than a megawatt.
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This raster dataset is the result of a subtraction of the classification of raster datasets bhd2030us and bhd2000us. Both are produced using the SERGoM v3 model, they depict housing density for the coterminous US in 2030 and 2000, resp., and are based on 2000 US Census Bureau block (SF1) datasets. (The classication of the subtraction is shown below.) A raster layer that portrays not-developed (and assumed to be undevelopable) called CUS_UPP_100 depicts protected/unprotected lands and Census water polygons. First, Land was removed from blocks (reducing the area of a block, but not its number of housing units -- assuming that private housing units must be on private land) that was public and/or protected in the UNPROTPRIV100...
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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. - As a final measure of potential human impacts to the ecoregions, the impacts of current anthropogenic development are summarized in a 60 x 60 m grid by the landscape condition model (LCM). The LCM weighs the relative influence of different types of human footprints based on factors like permanence, nature of the activity,...
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Landscape condition should not be assessed at a particular location without some explicit consideration of the surrounding environment. Landscape intactness provides a quantifiable and readily assessable measure of naturalness: it is a measure of how contiguous a landscape is. The purpose of this dataset is to provide an assessment of the relative landscape condition across a region to identify if the areas with degraded conditions are isolated or connected, which corresponds to how resilient an area might be to future changes. Some elements of human modification, specifically subsistence harvest, are not captured well in current models of intactness. Therefore, we modeled landscape intactness by extracting areas...
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This raster is used to answer management questions (MQs) about where conservation elements (CEs) overlap with areas of high wind energy potential in the Mojave Basin and Range Ecoregion. The value indicated in the raster represents a normalized score between 0-1, the lower the value the few species and poorer modeled landscape condition (ecological integrity) expected. The higher the score, the more species and higher condition are expected. This layer seeks to address an article in the BLM Statement of Work 1.1.1 stated, Areas with High Potential for Renewable Energy Development (Required) (The Contractor shall a) locate areas identified (e.g., by DOE, USGS) as suitable for wind, solar, geothermal, and biomass...
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Some of the NOS 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. - As a final measure of potential human impacts to the ecoregions, the impacts of current anthropogenic development are summarized in a 60 x 60 m grid by the landscape condition model (LCM). The LCM weights the relative influence of different types of human footprints based on factors like permanence, nature of the activity,...
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This simple assessment raster is used to answer management questions (MQs) about where change agents (CAs) overlap with BLM Herd Management Areas (HMAs) in the Central Great Basin and Range Ecoregion. This is a basic footprint assessment of anthropogenic features (urban development, roads, etc) intersect with areas managed for wild horses and burros in the western US. It does not model actual response or condition of the HMAs to the CAs. The data intersects two primary classes of information: The CAs consist of 19 classes which represent different types of human infrastructure on the landscape. Some types are easily defined, precise footprints (pipelines, roads, energy development areas) while others are broader...
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This simple assessment raster is used to answer management questions (MQs) about which grazing allotments (GAs) will experience significant climate change in the near future scenario in the Mojave Basin and Range Ecoregion. This is a basic intersect of areas that will likely experience significant climate change effects with the areas of public land that are leased to private entities for grazing by livestock. It does not model actual response or condition of the GAs to climate change. Nearly all GAs in the ecoregion will experience significant effects according to the criteria that were selected. The climate space trends data layer was used to ascertain areas of significant climate changes. Cells that represent...
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This simple assessment raster is used to answer management questions (MQs) about which herd management areas (HMAs) will experience significant climate change in the near future scenario in the Mojave Basin and Range Ecoregion. This is a basic intersect of areas that will likely experience significant climate change effects with the areas of public land that managed for wild herds of horses and/or burros. It does not model actual response or condition of the HMAs to climate change. Nearly all HMAs in the ecoregion will experience significant effects according to the criteria that were selected. The climate space trends data layer was used to ascertain areas of significant climate changes. Cells that represent Near...
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This dataset is a 100-meter cell resolution raster of estimated use of public supply water for the southwestern United States. The dataset was generated from 1:100,000-scale county boundary data, 2005 LandScan population data, and USGS estimated use of water in the United States in 2000.
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This data depicts pipeline locations in Alaska as digitized primarily from 1:24,000, 1:63,360, and 1:250,000 USGS quadrangles. The source document that represented the newest information and best geographic location was used to capture the data. All infrastructure from the primary source document was digitized and then supplemented with the information from other source documents for additional or updated infrastructure or attributes.
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This simple assessment raster is used to answer management questions (MQs) about where change agents (CAs) overlap with BLM high biodiversity sites (HBS) in the Central Great Basin and Range Ecoregion. This is a basic footprint assessment of anthropogenic features (urban development, roads, etc) intersect with the areas of HBS. The HBS were derived from source data characterizing locations with concentrated at-risk biodiversity or existing source data of a prioritization exercise that identified areas of high conservation significance. It does not model actual response or condition of the HBS to the CAs. The data intersects two primary classes of information: The CAs consist of 19 classes which represent different...
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This report presents updated information about subsistence uses of fish, wildlife, and plant resources in 5 communities of southcentral Alaska - Igiugig, Kokhanok, Koliganek, Levelock, and New Stuyahok. The Division of Subsistence of the Alaska Department of Fish and Game conducted the study in collaboration with Stephen R. Braund & Associates. Phase I of this study took place in the communities of Iliamna, Newhalen, Nondalton, Pedro Bay, and Port Alsworth in 2005, to document subsistence uses and harvests and demographic and other economic data for the study year of 2004 (Fall et al. 2006). This report documents findings from phase II which expanded the study to 5 additional communities within the watersheds that...
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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. - As a final measure of potential human impacts to the ecoregions, the impacts of current and long term potential anthropogenic development are summarized in a 60 x 60 m grid by the landscape condition model (LCM). The LCM weights the relative influence of different types of human footprints based on factors like permanence,...
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Locations of landfills and waste transfer stations in the Central Great Basin Ecoregion taken from a larger data set of 11 western states. USGS/SAGEMAP obtained this data from state and federal agencies in GIS, tabular, and map format. The primary contact for this the source data set is Steve Hanser, USGS-FRESC, Snake River Field Station, Boise, ID Not intended for use at scales greater than 1:250000


map background search result map search result map BLM REA COP 2010 Water Based RecreationTravel Corridors BLM REA COP 2010 Near-Term High Landscape Development BLM REA COP 2010 Water-Based Recreation Travel Corridors BLM REA CYR 2013 Material Sales Sites BLM REA SOD 2010 Development Risk, Contiguous US (2030) BLM REA NOS 2012 Existing Energy Sources in Communities in the North Slope - Oil BLM REA CYR 2013 Current Landscape Integrity Minimum Reserve in the Central Yukon Study Area BLM REA CYR 2013 Long-Term Future (2060) Landscape Condition per 5th Level Hydrologic Unit BLM REA YKL 2011 Alaska Pipelines 1:63,360 BLM REA YKL 2011 Long term future (2060) landscape condition model in the Yukon River Lowlands - Kuskokwim Mountains - Lime Hills BLM REA YKL 2011 Distribution of Potential Hydroelectric Energy in the Yukon River Lowlands - Kuskokwim Mountains - Lime Hills BLM REA YKL 2011 kll Moose polys dis BLM REA NOS 2012 High Development Scenario (2040) Landscape Condition BLM REA MBR 2010 CBR Footprint Assessment Change Agent/High Biodiversity Sites Intersect BLM REA MBR 2010 Estimated Public Supply Water Use of the Southwest Principal Aquifer (SWPA) study in 2005 BLM REA MBR 2010 Footprint Assessment Change Agent/Herd Management Areas Intersect BLM REA MBR 2010 Grazing Allotments Potentially Affected by Significant Climate Change BLM REA MBR 2010 Herd Management Areas Potentially Affected by Significant Climate Change BLM REA MBR 2010 Assessment Landscape Species and Wind Renewable Energy Potential Suitability BLM REA CBR 2010 Landfills in the Central Great Basin BLM REA YKL 2011 kll Moose polys dis BLM REA MBR 2010 Footprint Assessment Change Agent/Herd Management Areas Intersect BLM REA MBR 2010 Herd Management Areas Potentially Affected by Significant Climate Change BLM REA MBR 2010 Grazing Allotments Potentially Affected by Significant Climate Change BLM REA COP 2010 Water Based RecreationTravel Corridors BLM REA COP 2010 Water-Based Recreation Travel Corridors BLM REA COP 2010 Near-Term High Landscape Development BLM REA MBR 2010 Assessment Landscape Species and Wind Renewable Energy Potential Suitability BLM REA MBR 2010 CBR Footprint Assessment Change Agent/High Biodiversity Sites Intersect BLM REA SOD 2010 Development Risk, Contiguous US (2030) BLM REA CBR 2010 Landfills in the Central Great Basin BLM REA YKL 2011 Distribution of Potential Hydroelectric Energy in the Yukon River Lowlands - Kuskokwim Mountains - Lime Hills BLM REA NOS 2012 Existing Energy Sources in Communities in the North Slope - Oil BLM REA YKL 2011 Long term future (2060) landscape condition model in the Yukon River Lowlands - Kuskokwim Mountains - Lime Hills BLM REA MBR 2010 Estimated Public Supply Water Use of the Southwest Principal Aquifer (SWPA) study in 2005 BLM REA CYR 2013 Material Sales Sites BLM REA NOS 2012 High Development Scenario (2040) Landscape Condition BLM REA CYR 2013 Current Landscape Integrity Minimum Reserve in the Central Yukon Study Area BLM REA CYR 2013 Long-Term Future (2060) Landscape Condition per 5th Level Hydrologic Unit BLM REA YKL 2011 Alaska Pipelines 1:63,360