Abstract
An important issue is to check and identify the inconsistency of multi-representation data, when building multiscale spatial database. The representations of the same geographic entity in real world are different in terms of location, shape, and spatial relationships. In order to efficiently integrate multi-scale spatial data, we present a seamless representation model of spatial data based on its innate characteristics. Meanwhile, we put forward a complete consistency evaluation model for multi-scale representation. Vertically, it is divided into three levels, including macro, medium, and micro consistencies. Horizontally, it involves location, spatial relationship, and semantics, etc. The quantitative similarity measurement methods of spatial relationship are presented, which are applicable to the case of collapse in generalization. As case study, three spatial scenes with different scales are used to prove the completeness and rationality of our assessment system.
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