期刊名称:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN:2194-9042
电子版ISSN:2194-9050
出版年度:2001
卷号:XXXIV-4/W5
页码:1-5
出版社:Copernicus Publications
摘要:Modern geospatial databases are becoming increasingly complex, with multiple types of information (e.g. imagery, maps, vector data, video, and text), huge volumes of data (e.g. numerous satellite images continuously captured in the span of a mission), and distributed storage (e.g. various servers storing different types of information). Furthermore, spatiotemporal analysis is also becoming more complicated, with analysts making use of diverse datasets to make complex decisions. These trends make geospatial queries increasingly complex and challenging. In this paper we introduce non-linear correlations within geospatial databases to better handle user queries in distributed environments. In order to support queries, datasets are typically indexed according to their metadata information. For example, an image may be indexed according to its metadata parameters (e.g. area, scale, time, sensor). This results in defining a multidimensional (MD) space and indexing individual datasets in this space. Each dimension of this space corresponds to an individual parameter in the metadata description