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Sheet1 Page 1 *SPATIAL DATA ACQUISITION AND INTEGRATION* John Jensen, Department of Geography, University of South Carolina, Columbia, SC. Science, Ohio State University, Columbus, OH. Fred Broome, Bureau of the Census, Washington, DC. Dave Cowen, Department of Geography, University of South Carolina, Columbia, SC. Kevin Price, Department of Geography, University of Kansas, Lawrence, KS. Doug Ramsey, Department of Geography and Earth Resources, Utah State University, Logan, UT. Lewis Lapine, Chief South Carolina Geodetic Survey, Columbia, SC *1. Objective* To improve the logic and technology for /capturing/ and /integrating/ spatial data resources, including: /in situ/ sample measurements, complete census enumeration, maps, and remotely sensed imagery. The priority also desires to identify where research should take place concerning: data collection standards, geoids and datums (reference frames, in general), positional accuracy, measurement sampling theory, classification systems (schemes), metadata, address matching, and privacy issues. The goal is to obtain accurate socioeconomic and biophysical spatial data that may be analyzed and modeled to solve problems. *2. Background* Geographic information provides the basis for many types of decisions ranging from simple wayfinding to management of complex networks of facilities, predicting complex socioeconomic and demographic characteristics (e.g. population estimation), and the sustainable management of natural resources. Improved geographic data should lead to better conclusions and better decisions. According to several standards' and 'user' groups, better data would include greater positional accuracy and logical consistency and completeness. But each new data set, each new data item that is collected can be fully utilized only if it can be placed correctly into the context of other available data and information. To this end, the National Research Council Mapping Science Committee (1995) made a strong case that the United States' National Spatial Data Infrastructure (NSDI) consist of the following three */foundation/* spatial databases *(Figure 1 <#Figure 1>)*: 1) geodetic control, 2) digital terrain (including elevation and bathymetry), and 3) digital orthorectified imagery. Foundation spatial data are /the minimal directly observable or recordable data from which other spatial data are referenced and sometimes compiled./ They used a metaphor from the construction industry wherein a building must have a solid foundation of
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Sheet1 Page 2 concrete or other material. Then a framework of wood or steel beams is connected to the foundation to create a structure to support the remainder of the building. Examples of important */thematic/* */framework /*data might include hydrography and transportation. In fact, the National Spatial Data Infrastructure (NSDI) framework incorporates the following three foundation and four framework data
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This note was uploaded on 10/05/2010 for the course GEO 591 taught by Professor Davidm.mark during the Fall '10 term at SUNY Buffalo.

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