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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.
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.
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.
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.
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.
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.
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.
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.
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.
Geospatial data that is a derivative land cover product depicting woodland on topographic maps.
Geospatial data that is a derivative land cover product depicting woodland on topographic maps.
Geospatial data that is a derivative land cover product depicting woodland on topographic maps.
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.
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.
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.
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...
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...
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...
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...
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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