9,385 results returned
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Title: USA (Populated Places, 2003)
- 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: USA (Water Bodies, 2005)
- Polygon data
- 2005
- MIT authentication required
Summary: U.S. Water Bodies represents the major lakes, reservoirs, large rivers, lagoons, and estuaries in the United States.
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Title: Lidar-Derived Tiled DEM for Manitowoc County, WI 2023
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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.
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Title: LiDAR-Derived Intensity Images for Wood County, WI 2022
- Raster data
- 2022
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents a LiDAR-derived intensity images for Wood 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 Intensity Images for Oneida County, WI 2022
- Raster data
- 2022
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents LiDAR-derived intensity images for Oneida 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 Intensity Images for Iowa County, WI 2022
- Raster data
- 2022
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents LiDAR-derived intensity images for Iowa 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 Tile Index for Burnett County, WI 2022
- Polygon data
- 2022
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents the tile index used for LiDAR-derived datasets in Burnett County, Wisconsin in 2022. 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 Breaklines for Winnebago County, WI 2022
- Line data
- 2022
- Not owned by MIT (Owned by University of Wisconsin-Madison)
Summary: This data represents LiDAR-derived breaklines for Winnebago 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.