Journal
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
Volume 97, Issue 458, Pages 632-648Publisher
TAYLOR & FRANCIS INC
DOI: 10.1198/016214502760047140
Keywords
change of support; data assimilation; ecological inference; modifiable areal unit problem; multiscale processes; spatially-misaligned data
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Global positioning systems (GPSs) and geographical information systems (GISs) have been widely used to collect and synthesize spatial data from a variety of sources, New advances in satellite imagery and remote sensing now permit scientists to access spatial data at several different resolutions. The Internet facilitates fast and easy data acquisition. In any one study, several different types of data may be collected at differing scales and resolutions, at different spatial locations, and in different dimensions. Many statistical issues are associated with combining such data for modeling and inference, This article gives an overview of these issues and the approaches for integrating such disparate data, drawing on work from geography, ecology, agriculture, geology, and statistics. Emphasis is on state-of-the-art statistical solutions to this complex and important problem.
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