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A supervised classification is a system of classification in which the user builds a series of randomly generated training datasets or spectral signatures representing different land-use and land-cover (LULC) classes and applies these datasets in machine learning models to predict and spatially classify LULC patterns and evaluate classification accuracies.
The geographic information available includes orthoimagery (aerial photographs), elevation, geographic names, hydrography, boundaries, transportation, structures and land cover. The National Map is accessible via the Web, as products and services, and as downloadable data. Its uses range from recreation to scientific analysis to emergency ...
USGS Land Cover Institute: Set of links from the USGS for numerous land cover datasets. Although primarily US data, further down the list there is data for other continents. Atlas of the Biosphere: Mapping the Biosphere: Raster maps of environmental variables including soil pH, potential evapotranspiration, average snow depth, and more. Global 200
Generic Mapping Tools [16] Map generation and analysis Lamont–Doherty and University of Hawaii: GPL: Cross-platform: C: Implemented in OpendTect GPlates [17] Interactive visualization of plate tectonics University of Sydney, Caltech, NGU: GPL: Cross-platform: C++, Python: Implements GPML: OpenStereo [18] [19] Geoscience plotting tool
The GAP program began in the 1980s, based on analysis of Hawaiian bird species by J. Michael Scott. GAP has produced national land cover and protected areas datasets, which it uses to assess the conservation status of mammal, bird, reptile, and amphibian species in the U.S. A GAP program normally has three principal components: 1. Landcover ...
In 1995 the USGS was in need of a Windows viewer for their data products, so they developed the dlgv32 application for viewing their DLG (Digital Line Graph) vector data products. Between 1995 and 1998 the dlgv32 application was expanded to include support for viewing other USGS data products, including DRG (topographic maps) and DEM (digital ...
The National Elevation Dataset (NED) consists of high precision topography or ground surface elevation data (digital elevation model) for the United States. It was maintained by the USGS and all the data is in the public domain. Since the 3D Elevation Program came online, the NED was subsumed [1] into The National Map as one of its layers of ...
Aerial photography, land cover data, and digital elevation models all provide coverage data. Generally, a coverage can be multi-dimensional, such as 1-D sensor timeseries, 2-D satellite images, 3-D x/y/t image time series or x/y/z geo tomograms , or 4-D x/y/z/t climate and ocean data.