Combining Incompatible Spatial Data
本文概述了整合不同尺度、分辨率和空间位置的空间数据时面临的统计问题，并介绍了来自地理学、生态学、农学、地质学和统计学的最新统计解决方案。
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.