*SPATIAL DATA ACQUISITION AND INTEGRATION*
John Jensen, Department of Geography, University of South Carolina,
Science, Ohio State University, Columbus, OH.
Fred Broome, Bureau of the Census, Washington, DC.
Dave Cowen, Department of Geography, University of South Carolina,
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
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
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