文章基本信息

标题：Spatial statistics in geographical information science: from interpolation to probabilistic robotics
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作者：Alfred Stein
期刊名称：Annals of GIS
印刷版ISSN：1947-5683
出版年度：2010
卷号：16
期号：4
页码：211-221
DOI：10.1080/19475683.2010.539986
语种：English
出版社：Taylor & Francis Ltd.
摘要：This review article presents an overview of spatial statistical procedures that are of use and value in geographical information science. Spatial statistics considers the handling of spatial data, with an emphasis on modeling and on dealing with uncertainty. Spatial statistics includes issues of interpolation, point statistics, and sampling. Within a robotics context we distinguish localization, mapping, and decision control and support. Localization is based on advanced image analysis in which the idea of image mining plays an important role. Image mining considers the chain from object identification on natural or man-made processes from remote sensing images through modeling, tracking on a series of images and prediction, toward communication to stakeholders. Geographical information science serves as a scientific field, for example, to generate a platform for storing observed and collected data, analyzing them, and displaying the results. This article shows how within the domain of robotics there are novel and intriguing possibilities to use spatial statistics and image mining. The article gives a concise overview of these procedures and several ways ahead that are of value within a robotics context. It is illustrated with a field study on robotics in agriculture.
关键词：spatial statistics;image mining;interpolation;robotics;spatial data quality