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Level 1A Raw Image Data from SPOT 5 and SPOT 4 satellite. These images were used to create the orthoimages for the product GeoBase Orthoimage 2005-2010. Images of Raw Imagery GeoBase 2005-2010 product are raster digital date coming from SPOT 4 and SPOT 5 satellites that contain a panchromatic band with 10 meter pixels and four multispectral bands with 20 meter pixels. These images were used to produce the orthoimages of the GeoBase Orthoimage 2005-2010 product. These images are not georeferenced. The main objective of the project is to produce a complete set of raw images covering Canada's landmass over a five-year period, from May 2005 to October 2010. The goal is also to promote the use of geomatics and education...
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The LANDFIRE existing vegetation layers describe the following elements of existing vegetation for each LANDFIRE mapping zone: existing vegetation type, existing vegetation canopy cover, and existing vegetation height. Vegetation is mapped using predictive landscape models based on extensive field reference data, satellite imagery, biophysical gradient layers, and classification and regression trees.DATA SUMMARY: The existing vegetation type (EVT) data layer represents the current distribution of the terrestrial ecological systems classification developed by NatureServe for the western Hemisphere (http://www.natureserve.org/publications/usEcologicalsystems.jsp). A terrestrial ecological system is defined as a group...
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The dataset represents the work of multiple states and Federal agencies as part of the US Gap Analysis and LandFire programs. Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. The minimum mapping unit for this dataset is approximately 1 acre. Landcover classes are drawn from NatureServe's Ecological System concept. Five-hundred and fourty-four land cover classes composed of 12 cultural and 532 Natural/Semi-natural types are described. Land cover classes were mapped with a variety of techniques including decision tree classifiers, terrian modeling, inductive...
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LANDFIRE disturbance data are developed to provide temporal and spatial information related to landscape change for determining vegetation transitions over time and for making subsequent updates to LANDFIRE vegetation, fuel and other data. Disturbance data include attributes associated with disturbance year, type, and severity. These data are developed through use of Landsat satellite imagery, local agency derived disturbance polygons, and other ancillary data. DATA SUMMARY: The disturbance data are developed through a multistep process. Inputs to this process include; Landsat imagery and derived NBR (normalized burn ratio) data; polygon data developed by local agencies for the LANDFIRE Refresh effort; fire data...
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The LANDFIRE vegetation layers describe the following elements of existing and potential vegetation for each LANDFIRE mapping zone: environmental site potentials, biophysical settings, existing vegetation types, canopy cover, and vegetation height. Vegetation is mapped using predictive landscape models based on extensive field reference data, satellite imagery, biophysical gradient layers, and classification and regression trees.DATA SUMMARYThe biophysical settings (BpS) data layer represents the vegetation that may have been dominant on the landscape prior to Euro-American settlement and is based on both the current biophysical environment and an approximation of the historical disturbance regime. It is a refinement...
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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. - The National Land Cover Database 2011 land cover layer for Alaska was produced 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...
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The dataset represents the work of multiple states and Federal agencies as part of the US Gap Analysis and LandFire programs. Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. The minimum mapping unit for this dataset is approximately 1 acre. Landcover classes are drawn from NatureServe's Ecological System concept. Five-hundred and fourty-four land cover classes composed of 12 cultural and 532 Natural/Semi-natural types are described. Land cover classes were mapped with a variety of techniques including decision tree classifiers, terrian modeling, inductive...
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Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National...
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Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National...
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These data are orthorectified radar intensity images (ORI) derived from interferometric synthetic aperture radar (ifsar) data. An ORI is a high-resolution image derived from ifsar which has geometric distortions removed. Unlike optical imagery, ifsar can be collected in cloudy conditions. The USGS performs minimal quality assurance and no reprocessing of the ORI data. USGS distributes the ORI data as received from the contractors, partners or contributing entities.
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These data are orthorectified radar intensity images (ORI) derived from interferometric synthetic aperture radar (ifsar) data. An ORI is a high-resolution image derived from ifsar which has geometric distortions removed. Unlike optical imagery, ifsar can be collected in cloudy conditions. The USGS performs minimal quality assurance and no reprocessing of the ORI data. USGS distributes the ORI data as received from the contractors, partners or contributing entities.
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These data are orthorectified radar intensity images (ORI) derived from interferometric synthetic aperture radar (ifsar) data. An ORI is a high-resolution image derived from ifsar which has geometric distortions removed. Unlike optical imagery, ifsar can be collected in cloudy conditions. The USGS performs minimal quality assurance and no reprocessing of the ORI data. USGS distributes the ORI data as received from the contractors, partners or contributing entities.
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These data are orthorectified radar intensity images (ORI) derived from interferometric synthetic aperture radar (ifsar) data. An ORI is a high-resolution image derived from ifsar which has geometric distortions removed. Unlike optical imagery, ifsar can be collected in cloudy conditions. The USGS performs minimal quality assurance and no reprocessing of the ORI data. USGS distributes the ORI data as received from the contractors, partners or contributing entities.
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These data are orthorectified radar intensity images (ORI) derived from interferometric synthetic aperture radar (ifsar) data. An ORI is a high-resolution image derived from ifsar which has geometric distortions removed. Unlike optical imagery, ifsar can be collected in cloudy conditions. The USGS performs minimal quality assurance and no reprocessing of the ORI data. USGS distributes the ORI data as received from the contractors, partners or contributing entities.
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These data are orthorectified radar intensity images (ORI) derived from interferometric synthetic aperture radar (ifsar) data. An ORI is a high-resolution image derived from ifsar which has geometric distortions removed. Unlike optical imagery, ifsar can be collected in cloudy conditions. The USGS performs minimal quality assurance and no reprocessing of the ORI data. USGS distributes the ORI data as received from the contractors, partners or contributing entities.
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These data are orthorectified radar intensity images (ORI) derived from interferometric synthetic aperture radar (ifsar) data. An ORI is a high-resolution image derived from ifsar which has geometric distortions removed. Unlike optical imagery, ifsar can be collected in cloudy conditions. The USGS performs minimal quality assurance and no reprocessing of the ORI data. USGS distributes the ORI data as received from the contractors, partners or contributing entities.
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These data are orthorectified radar intensity images (ORI) derived from interferometric synthetic aperture radar (ifsar) data. An ORI is a high-resolution image derived from ifsar which has geometric distortions removed. Unlike optical imagery, ifsar can be collected in cloudy conditions. The USGS performs minimal quality assurance and no reprocessing of the ORI data. USGS distributes the ORI data as received from the contractors, partners or contributing entities.
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These data are orthorectified radar intensity images (ORI) derived from interferometric synthetic aperture radar (ifsar) data. An ORI is a high-resolution image derived from ifsar which has geometric distortions removed. Unlike optical imagery, ifsar can be collected in cloudy conditions. The USGS performs minimal quality assurance and no reprocessing of the ORI data. USGS distributes the ORI data as received from the contractors, partners or contributing entities.
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These data are orthorectified radar intensity images (ORI) derived from interferometric synthetic aperture radar (ifsar) data. An ORI is a high-resolution image derived from ifsar which has geometric distortions removed. Unlike optical imagery, ifsar can be collected in cloudy conditions. The USGS performs minimal quality assurance and no reprocessing of the ORI data. USGS distributes the ORI data as received from the contractors, partners or contributing entities.


map background search result map search result map USGS NED Orthorectified Radar Intensity Image AK IFSAR-D6-L4-C37 2013 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-D6-L4-C64 2013 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-D6-L4-C89 2013 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-NRCS-L2-C258 2012 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK Mid-Accuracy CarryOver-C92 TIFF 2016 USGS NED Orthorectified Radar Intensity Image AK Mid-Accuracy CarryOver-C118 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK Mid-Accuracy CarryOver-C119 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-D5-L2-C132 2012 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-D5-L6-C29 2012 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-D6-L1B-C83 2012 TIFF 2015 BLM REA COP 2010 NatureServe National Landcover (v27) ColoradoPlateauMixedBedrockCanyonTableland_NatureServe_DIST_30m BLM REA COP 2010 NatureServe National Landcover (v27) InterMountainBasinsBigSagebrushShrubland_NatureServe_DIST_30m BLM REA COP 2010 LANDFIRE - Existing Vegetation Type (version 1.1.0) BLM REA COP 2010 LANDFIRE - Disturbance (2003) BLM REA SOD 2010 LANDFIRE - Percent Mixed Severity Fire for the Sonoran Desert ecoregion, USA (version 1.0) BLM REA SOD 2010 LANDFIRE - Percent Replacement Severity Fire (version 1.0) BLM REA SOD 2010 LANDFIRE - Biophysical Settings (version 1.0) USGS NED Orthorectified Radar Intensity Image AK IFSAR-D6-L4-C37 2013 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-D6-L4-C89 2013 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-D6-L4-C64 2013 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-D6-L1B-C83 2012 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK Mid-Accuracy CarryOver-C118 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK Mid-Accuracy CarryOver-C92 TIFF 2016 USGS NED Orthorectified Radar Intensity Image AK Mid-Accuracy CarryOver-C119 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-D5-L6-C29 2012 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-D5-L2-C132 2012 TIFF 2015 USGS NED Orthorectified Radar Intensity Image AK IFSAR-NRCS-L2-C258 2012 TIFF 2015 BLM REA SOD 2010 LANDFIRE - Percent Mixed Severity Fire for the Sonoran Desert ecoregion, USA (version 1.0) BLM REA SOD 2010 LANDFIRE - Percent Replacement Severity Fire (version 1.0) BLM REA SOD 2010 LANDFIRE - Biophysical Settings (version 1.0) BLM REA COP 2010 LANDFIRE - Disturbance (2003) BLM REA COP 2010 NatureServe National Landcover (v27) ColoradoPlateauMixedBedrockCanyonTableland_NatureServe_DIST_30m BLM REA COP 2010 NatureServe National Landcover (v27) InterMountainBasinsBigSagebrushShrubland_NatureServe_DIST_30m BLM REA COP 2010 LANDFIRE - Existing Vegetation Type (version 1.1.0)