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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Vectorized version of the raster model with the PJ and Conifer interface areas merged across the west. A raster model was developed to identify sagebrush land cover which is in close proximity to conifer land cover, thus suggesting a risk for conifer encroachment. To achieve this end product the following general steps were taken: 1. Extract sagebrush land cover types from GAP/ReGAP data. 2. Extract conifer land cover types (excluding those corresponding to pinyon, juniper, and pinyon-juniper) from GAP/ReGAP data. 3. Reclassify and add these raster datasets. 4. Conduct a focal statistics operation. 5. Multiply the above product by the extracted, reclassified sagebrush raster to identify sagebrush cells adjacent...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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This dataset represents the cumulative result of multi-season classification of land cover in the GCPO LCC geography to NatureServe Ecological Systems based on 2011 seasonal Landsat Satellite Imagery. The approach used a Random Forest algorithm and several dozen input data layers to classify land cover at a 30 m pixel resolution. The description below is taken directly from the report titled “Update of the Eastern GCPO Land Cover Database to 2011 Using a LS2SRC Approach”, by Dr. Qingmin Meng, Department of Geosciences, Mississippi State University.Random Forest classifier is based on the general decision tree approach, which has been a popular approach to multilevel and multistage decision making. Its basic idea...
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A spatial dataset of public and private lands and waters secured by a conservation situation that includes an explicit level of security from future conversion and current incompatible uses.For more information on TNC's Secured Lands project visit: www.conservationgateway.org/ConservationByGeography/NorthAmerica/UnitedStates/edc/reportsdata/terrestrial/secured/Pages/default.aspx The list of sources for this dataset can be found in the attached word document. The full report on the status and condition of the northeastern natural landscapes, under all levels of protection: https://www.conservationgateway.org/ConservationByGeography/NorthAmerica/UnitedStates/edc/Documents/Conservation-Status-of-Fish-Wildlife-and-Natural-Habitats.pdf...
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This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the Northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the Southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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This dataset consists of polygon range maps for terrestrial vertebrate species in Alaska. The maps are shapefiles between 0 and 12 MB in size to be used in OpenGIS or ArcGIS on a PC. Individual species range maps were developed using the best available known range of the species (derived from a variety of available point data sources), overlaid with watershed-scale units (8-digit HUCs; standard map for U.S. GAP project) for the state of Alaska in the Alaska Albers NAD83 projection. These maps present the data in the form that they were created in, are subject to change, and are freely available from the the Alaska GAP project.
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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This dataset compiles land ownership and management data from state and federal agencies to create a map showing ownership, management, and conservation status of all land in Alaska. State, federal, and private lands, including Native corporations and Native allotments, are included. Conservation status describes the degree to which land, particularly public land, is legally designated and explicitly managed for biodiversity conservation. The most common classification, developed by the USGS GAP Program (www.gap.uidaho.edu), classifies land management types into four conservation status categories according to the degree to which the land is explicitly managed for conservation. In general, conservation status 1...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...
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Some of the SNK 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. - This dataset consists of raster distribution maps for terrestrial vertebrate species in Alaska. Individual species distribution maps were developed using the best available known occurrence points for each species and modeled using MaxEnt software and a series of environmental predictor variables. Output maps were clipped...


map background search result map search result map Secured Lands by GAP Status, 2012, Northeast Landcover Management and Conservation Stewardship of Alaska Lands, 2006, The Nature Conservancy Ecological Systems Classification 2011 Update for the Eastern GCPO LCC Geography BLM GRSG BER: Sagebrush, Pinyon-Juniper, and Conifer Interface (polygon) BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Alces americanus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Somateria fischeri BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Brachyramphus brevirostris BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Somateria mollissima BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Falco peregrinus BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Ovibos moschatus BLM REA SNK 2010 Alaska Gap Analysis Project: Seasonal range maps for Caribou BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Plectrophenax hyperboreus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Limosa lapponica BLM REA SNK 2010 Alaska Gap Analsysis Project: Year Round Distribution Map for Rangifer tarandus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Calidris canutus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Numenius tahitiensis BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Limosa haemastica BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Melanitta nigra BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Ursus americanus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Calidris canutus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Numenius tahitiensis Landcover BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Falco peregrinus BLM REA SNK 2010 Alaska Gap Analysis Project: Seasonal range maps for Caribou BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Plectrophenax hyperboreus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Limosa haemastica BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Ursus americanus BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Alces americanus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Somateria fischeri BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Brachyramphus brevirostris BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Somateria mollissima BLM REA SNK 2010 Alaska Gap Analysis Project: Year Round Distribution Map for Ovibos moschatus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Limosa lapponica BLM REA SNK 2010 Alaska Gap Analsysis Project: Year Round Distribution Map for Rangifer tarandus BLM REA SNK 2010 Alaska Gap Analysis Project: Breeding Season Distribution Map for Melanitta nigra Ecological Systems Classification 2011 Update for the Eastern GCPO LCC Geography Secured Lands by GAP Status, 2012, Northeast BLM GRSG BER: Sagebrush, Pinyon-Juniper, and Conifer Interface (polygon) Management and Conservation Stewardship of Alaska Lands, 2006, The Nature Conservancy