摘要
粗集是一种处理地理信息不确定性和不精确性的新型数学工具,在揭示和表达多层次(或粒度)的空间知识方面具有较大优势。为此,从空间信息观测或表达的粒度角度来探讨空间数据所蕴含的不确定性。在此基础上,运用粗集理论中的一些基本概念和方法来系统地描述和表达空间目标位置数据、属性数据以及空间关系数据的不确定性,旨在建立一种多粒度的不确定性分析和表达方法。
Rough set is a novel mathematical tool for dealing with uncertainties and imprecision of geographic information, which can he used to represent uncertainties in multi-levels spatial knowledge. Based upon the fundamental concepts in rough set theory, this paper proposes rough set models to represent the uncertainties in position, attribute and topological relation of spatial objects. The changes of these uncertainties with the observation granularity are also investigated and represented by the rough set approach. It suggests that rough set is a very promising tool to integrate the representation of the uncertainties in measurement, classification and spatial relationships, and their changes with the observation granularity.
出处
《测绘学报》
EI
CSCD
北大核心
2006年第1期64-70,共7页
Acta Geodaetica et Cartographica Sinica
基金
香港理工大学基金项目(G-T873)
测绘遥感信息工程国家重点实验室开放基金项目(WKL040304)
关键词
空间目标
粒度
不确定性
粗集
空间关系
spatial object
granularity
uncertainty
rough set
spatial relations
