10,000+ results returned
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Title: United States Institutions, 2010-2014
Contributors:- Point data
- 2014
- Not owned by MIT (Owned by Stanford)
Summary: This shapefile represents point locations within the United States for common institution landmark types including hospitals, educational institutions, places of worship, government offices, cemeteries, museums, and libraries. This layer is part of the 2014 ESRI Data and Maps collection for ArcGIS 10.2. U.S. Institutions provides the locations for hundreds of thousands of hospitals, educational institutions, places of worship, government offices, cemeteries, museums, and libraries. Each institution is named and shows the state and county in which it resides. Tele Atlas and ESRI. (2014). United States Institutions, 2010-2014. ESRI. Available at: http://purl.stanford.edu/mn318kf6677
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Title: United States Census Block Groups, 2013
Contributors:- Polygon data
- 2014
- Not owned by MIT (Owned by Stanford)
Summary: U.S. Census Block Groups represents the U.S. Census block groups of the United States in the 50 states, the District of Columbia, and Puerto Rico. Data are represented at a scale of 1:100,000. This layer is part of the 2014 ESRI Data and Maps collection for ArcGIS 10.2. U.S. Census Block Groups provides boundaries and demographic information for the U.S. Census block groups within the United States. The boundaries are consistent with the tract, county, and state datasets. Tele Atlas and ESRI. (2014). United States Census Block Groups, 2013. ESRI. Available at: http://purl.stanford.edu/kr064yh0964
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Title: United States Large Area Landmarks, 2010-2014
Contributors:- Polygon data
- 2014
- Not owned by MIT (Owned by Stanford)
Summary: This polygon shapefile represents common landmark areas within the United States including military territories, hospitals, educational institutions, shopping centers, industrial areas, amusement parks, stadiums, golf courses, and cemeteries. This layer is part of the 2014 ESRI Data and Maps collection for ArcGIS 10.2. U.S. Large Area Landmarks provides thousands of common landmark areas within the United States. The areas can be used as a cultural layer at local and regional levels. Each landmark is named. Tele Atlas and ESRI. (2014). United States Large Area Landmarks, 2010-2014. ESRI. Available at: http://purl.stanford.edu/xk044yh3203
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Title: United States Recreation Areas, 2010-2014
Contributors:- Point data
- 2014
- Not owned by MIT (Owned by Stanford)
Summary: This shaoefile represents point locations within the United States for common recreational landmarks including golf courses, amusement parks, beaches, and park and recreation areas. This layer is part of the 2014 ESRI Data and Maps collection for ArcGIS 10.2. U.S. Recreation Areas provides the locations of common recreational landmarks including golf courses, amusement parks, beaches, and park and recreation areas. Each recreation area is named and shows the state and county in which it resides. Tele Atlas and ESRI. (2014). United States Recreation Areas, 2010-2014. ESRI. Available at: http://purl.stanford.edu/wz398ym3298
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Title: United States Parks, 2010-2014
Contributors:- Polygon data
- 2014
- Not owned by MIT (Owned by Stanford)
Summary: This polygon shapefile contains the boundaries of parks, gardens, and forests within the United States at national, state, county, regional, and local levels. Data are represented at a 1:500,000 scale. U.S. Parks provides thousands of parks, gardens, and forests at national, state, county, regional, and especially local levels. Tele Atlas and ESRI. (2014). United States Parks, 2010-2014. ESRI. Available at: http://purl.stanford.edu/wg587fd2376
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Title: Canada Postal Points, 2008
Contributors:- Point data
- 2008
- Not owned by MIT (Owned by Columbia)
Summary: Canada Postal Points is a point theme representing the centroids of the three-character Forward Sortation Areas (FSA) of Canada.
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Title: Canada Postal Areas, 2008
Contributors:- Polygon data
- 2008
- Not owned by MIT (Owned by Columbia)
Summary: Canada Postal Areas is a polygon theme representing the three-character Forward Sortation Areas (FSA) of Canada. This data set provides six levels of generalization for displaying the data at different scales. Everything about the levels is the same but the level of generalization and its name. The least generalized level is called <data set name>. The next more generalized level is called <data set name>_1, and so on. For best performance, use the most appropriate generalized level when displaying or printing.
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Title: Canada Railroads, 2008
Contributors:- Line data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Railroads is a line theme representing the railroads of Canada. This data set provides six levels of generalization for displaying the data at different scales. Everything about the levels is the same but the level of generalization and its name. The least generalized level is called <data set name>. The next more generalized level is called <data set name>_1, and so on. For best performance, use the most appropriate generalized level when displaying or printing.
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Title: Canada Interstate Highways, 2008
Contributors:- Line data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Interstate Highways is a line theme representing the interstate highways of Canada.
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Title: Canada Large Area Landmarks, 2008
Contributors:- Polygon data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Large Area Landmarks is a polygon theme representing common landmark areas within United States including military areas, prisons, educational institutions, amusement centers, government centers, sport centers, golf courses, and cemeteries. Attribute information includes the are, name and FCC code of the landmark. This dataset is a part of the 2008 ESRI Data & Maps collection.
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Title: Canada Airports, 2008
Contributors:- Polygon data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Airports is a polygon theme representing airport boundaries and runways within Canada. This data set provides six levels of generalization for displaying the data at different scales. Everything about the levels is the same but the level of generalization and its name. The least generalized level is called <data set name>. The next more generalized level is called <data set name>_1, and so on. For best performance, use the most appropriate generalized level when displaying or printing.
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Title: U.S. and Canada Highways, 2008
Contributors:- Line data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Highways is a line theme representing the major highways of Canada. These include inter-metropolitan area highways and major roads.
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Title: Canada Institutions, 2008
Contributors:- Point data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Institutions is a point theme representing locations within Canada for common institution landmark types including hospitals, educational institutions, religious institutions, government centers, and cemeteries.
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Title: Canada Recreation Areas, 2008
Contributors:- Point data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Recreation Areas is a point theme representing common recreation landmarks within Canada including golf courses, zoos, resorts, and other recreational facilities.
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Title: Canada Parks, 2008
Contributors:- Polygon data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Parks is a polygon theme representing parks and forests within Canada at national and local levels. This data set provides six levels of generalization for displaying the data at different scales. Everything about the levels is the same but the level of generalization and its name. The least generalized level is called <data set name>. The next more generalized level is called <data set name>_1, and so on. For best performance, use the most appropriate generalized level when displaying or printing.
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Title: Canada Lakes, 2008
Contributors:- Polygon data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Lakes is a polygon theme representing the major lakes within Canada. This data set provides five levels of generalization for displaying the data at different scales. Everything about the levels is the same but the level of generalization and its name. The least generalized level is called <data set name>. The next more generalized level is called <data set name>_1, and so on. For best performance, use the most appropriate generalized level when displaying or printing.
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Title: Canada Transportation Terminals, 2008
Contributors:- Point data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Transportation Terminals is a point theme representing transportation terminals in Canada such as bus terminals, train stations, marine terminals, and other significant transportation nodes.
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Title: Canada Cities, 2008
Contributors:- Point data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Cities is a point theme representing cities of Canada including national, state, and provincial capitals.
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Title: Canada Major Roads, 2008
Contributors:- Line data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada Major Roads is a line theme representing the major roads of Canada. These include interstates, inter-metropolitan area, and intra-state highways and major roads.
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Title: Canada City Areas, 2008
Contributors:- Polygon data
- 2007
- Not owned by MIT (Owned by Columbia)
Summary: Canada City Areas is a polygon theme representing the city limits of cities in Canada. This data set provides six levels of generalization for displaying the data at different scales. Everything about the levels is the same but the level of generalization and its name. The least generalized level is called <data set name>. The next more generalized level is called <data set name>_1, and so on. For best performance, use the most appropriate generalized level when displaying or printing.