10,000+ results returned
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Title: USA (Populated Places, 2003)
Contributors:- Point data
- 2008
Summary: This data set includes cities in the United States, Puerto Rico and the U.S. Virgin Islands. These cities were collected from the 1970 National Atlas of the United States. Where applicable, U.S. Census Bureau codes for named populated places were associated with each name to allow additional information to be attached. The Geographic Names Information System (GNIS) was also used as a source for additional information. This is a revised version of the December, 2003, data set.
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Title: Coal deposits, Shiawassee County, Mich., 1976
Contributors:- Not specified
- 1976
- Not owned by MIT (Owned by Michigan State University)
- Welch, Edwin J.
- Kalliokoski, J.
- Michigan Technological University
- Michigan
- Geological Survey Division
Summary: Extent: 1 map Notes: From: Kalliokoski, J. Magnitude and quality of Michigan's coal reserves. Lansing, Mich. : Geological Survey Division, 1977. Cartographic material.
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Title: Indiana, index base map
Contributors:- Index maps ; Aerial photographs
- 1979
- Not owned by MIT (Owned by Indiana University)
Summary: Blue line print. "March 1978." Hand annotated in red ink to show High altitude photography (HAP) sectors for photography in 1977 and 1979 with notation "flight height 40,000'." Imprint: [Reston, Va.] : The Center, [1979?] Dimensions: 47 x 31 cm; Scale: 1:1,000,000 Coordinates: W0880700 W0844500 N0414500 N0375200
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Title: MassGIS 2003 Massachusetts Major Drainage Basins (Arcs) (March 2003)
Contributors:- Line data
- 2003
- Not owned by MIT (Owned by Harvard)
- MassGIS (Office : Mass.)
- Geological Survey (U.S.). Water Resources Division.
- Massachusetts Water Resources Authority.
- Massachusetts. Dept. of Environmental Protection.
Summary: This datalayer, produced by MassGIS, contains polylines representing boundaries of the 28 major drainage basins of Massachusetts as defined by the USGS Water Resources Division and the MA Water Resources Commission. (See also the Major Drainage Basins (Polygons) datalayer).
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Title: MassGIS 2003 Massachusetts Major Watersheds (Polygons) (June 2000)
Contributors:- Polygon data
- 2003
- Not owned by MIT (Owned by Harvard)
- MassGIS (Office : Mass.)
- Geological Survey (U.S.). Water Resources Division.
- Massachusetts Water Resources Authority.
Summary: This datalayer contains polygons representing Massachusetts watersheds (see also the Watersheds (Arcs) datalayer). MassGIS has produced a statewide digital datalayer of the 32 major watersheds covering Massachusetts as defined by the USGS Water Resources Division and the MA Water Resources Commission. The datalayer is called Watersheds. Unlike the Major Drainage Basins layer, the watersheds in this layer extend beyond the state boundary to include the full extent of either the full watershed or a full USGS sub-basin.
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Title: MassGIS 2003 Massachusetts Major Drainage Basins (Polygons) (March 2003)
Contributors:- Polygon data
- 2003
- Not owned by MIT (Owned by Harvard)
- MassGIS (Office : Mass.)
- Geological Survey (U.S.). Water Resources Division.
- Massachusetts Water Resources Authority.
- Massachusetts. Dept. of Environmental Protection.
Summary: This datalayer, produced by MassGIS, contains polygons representing the 28 major drainage basins of Massachusetts as defined by the USGS Water Resources Division and the MA Water Resources Commission. (See also the Major Drainage Basins (Arcs) datalayer).
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Title: MassGIS 2003 Massachusetts Major Watersheds (Arcs) (June 2000)
Contributors:- Line data
- 2003
- Not owned by MIT (Owned by Harvard)
- MassGIS (Office : Mass.)
- Geological Survey (U.S.). Water Resources Division.
- Massachusetts Water Resources Authority.
Summary: This datalayer contains lines representing Massachusetts watershed boundaries (see also the Watersheds (Polygons) datalayer). MassGIS has produced a statewide digital datalayer of the 32 major watersheds covering Massachusetts as defined by the USGS Water Resources Division and the MA Water Resources Commission. The datalayer is called Watersheds. Unlike the Major Drainage Basins layer, the watersheds in this layer extend beyond the state boundary to include the full extent of either the full watershed or a full USGS sub-basin.
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Title: Lidar-Derived Tiled DEM for Manitowoc County, WI 2023
Contributors:- Raster data
- 2023
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents a Lidar-derived tiled Digital Elevation Model (DEM) for Manitowoc County, Wisconsin in 2023. A DEM represents the bare-Earth surface, removing all natural and built features. This dataset contains individual files available for download consisting of smaller tiled geographic areas over the extent of an entire county.
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Title: Lidar-Derived Breaklines for Buffalo County, WI 2023
Contributors:- Line data
- 2023
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents Lidar-derived breaklines in Buffalo County, Wisconsin in 2023. Hydro breaklines maintain the definition of water-related features in an elevation model. They are used to capture linear discontinuities in the surface, lake shorelines, single-line drains for small rivers, and double-line drains for large rivers.
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Title: Lidar-Derived Tiled DEM for Buffalo County, WI 2016
Contributors:- Raster data
- 2023
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents a Lidar-derived tiled Digital Elevation Model (DEM) for Buffalo County, Wisconsin in 2023. A DEM represents the bare-Earth surface, removing all natural and built features. This dataset contains individual files available for download consisting of smaller tiled geographic areas over the extent of an entire county.
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Title: Lidar-Derived Classified LAS for Manitowoc County, WI 2023
Contributors:- Point data
- 2023
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents Lidar-derived classified LAS points for Manitowoc County, Wisconsin in 2023. Point classification uses semi-automated techniques on the point cloud to assign the feature type associated with each point. Lidar points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files.
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Title: Lidar-Derived Classified LAS for Buffalo County, WI 2023
Contributors:- Point data
- 2023
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents Lidar-derived classified LAS points for Buffalo County, Wisconsin in 2023. Point classification uses semi-automated techniques on the point cloud to assign the feature type associated with each point. Lidar points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files.
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Title: Lidar-Derived Breaklines for Manitowoc County, WI 2023
Contributors:- Line data
- 2023
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents Lidar-derived breaklines for Manitowoc County, Wisconsin in 2023. Hydro breaklines maintain the definition of water-related features in an elevation model. They are used to capture linear discontinuities in the surface, lake shorelines, single-line drains for small rivers, and double-line drains for large rivers.
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Title: Lidar-Derived Intensity Images Buffalo County, WI 2023
Contributors:- Raster data
- 2023
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents Lidar-derived tiled intensity images for Buffalo County, Wisconsin in 2023. Lidar intensity is recorded as the return strength of a laser beam. It is a bi-product, provided as an integer number between 1-256. This number varies with the composition of the surface object reflecting the laser beam. A low number indicates low reflectivity while a high number indicates high reflectivity. The intensity of the laser beam return can also be affected by the angle of arrival (scan angle), range, surface composition, roughness, and moisture content.
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Title: Lidar-Derived Intensity Images for Manitowoc County, WI 2023
Contributors:- Raster data
- 2023
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents Lidar-derived tiled intensity images for Manitowoc County, Wisconsin in 2023. Lidar intensity is recorded as the return strength of a laser beam. It is a bi-product, provided as an integer number between 1-256. This number varies with the composition of the surface object reflecting the laser beam. A low number indicates low reflectivity while a high number indicates high reflectivity. The intensity of the laser beam return can also be affected by the angle of arrival (scan angle), range, surface composition, roughness, and moisture content.
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Title: Lidar Tile Index Buffalo County, WI 2023
Contributors:- Polygon data
- 2023
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents the tile index used for Lidar-derived datasets in Buffalo County, Wisconsin in 2023. The tile index is a shapefile that shows how tiled Lidar datasets are labeled and where they are located geographically.
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Title: Lidar Tile Index for Manitowoc County, WI 2023
Contributors:- Polygon data
- 2023
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents the tile index used for Lidar-derived datasets in Manitowoc County, Wisconsin in 2023. The tile index is a shapefile that shows how tiled Lidar datasets are labeled and where they are located geographically.
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Title: LiDAR-Derived Tiled Digital Elevation Model (DEM) for Trempealeau County, WI 2022
Contributors:- Raster data
- 2022
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents a LiDAR-derived tiled Digital Elevation Model (DEM) for Trempealeau County, Wisconsin in 2022. A DEM represents the bare-Earth surface, removing all natural and built features.
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Title: LiDAR-Derived Intensity Images for Vilas County, WI 2022
Contributors:- Raster data
- 2022
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents a LiDAR-derived intensity images for Vilas County, Wisconsin in 2022. LiDAR intensity is recorded as the return strength of a laser beam. It is a bi-product, provided as an integer number between 1-256. This number varies with the composition of the surface object reflecting the laser beam. A low number indicates low reflectivity while a high number indicates high reflectivity. The intensity of the laser beam return can also be affected by the angle of arrival (scan angle), range, surface composition, roughness, and moisture content.
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Title: LiDAR-Derived Breaklines for Oneida County, WI 2022
Contributors:- Line data
- 2022
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents LiDAR-derived breaklines for Oneida County, Wisconsin in 2022. Hydro breaklines maintain the definition of water-related features in an elevation model. They are used to capture linear discontinuities in the surface, lake shorelines, single-line drains for small rivers, and double-line drains for large rivers.