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A framework for assisted proximity analysis in feature data
Journal of Geographical Systems ( IF 2.417 ) Pub Date : 2019-08-03 , DOI: 10.1007/s10109-019-00304-3
Rolf Grütter

This framework for assisted proximity analysis in feature data consists of a hierarchy of proximity classes that use spatial neighborhoods as fundamental building blocks. The instances are spatial relations between isolated objects, or objects in a cluster, sharing the relational properties of reflexivity/irreflexivity and symmetry/asymmetry. The framework proposes ways of generating spatial neighborhoods and includes a discussion of how to deal with the vagueness inherent in nearness relations. It is applied to a realistic use case of epizootic disease outbreak. The framework updates the current state of knowledge in the field by considering: (1) spatial objects in a cluster, (2) spatially coextensive regions, and (3) regions in a partition chain. It relates ways of generating spatial neighborhoods to the proximity classes and introduces a number of yes–no questions to be implemented as a sequence of functions in a GIS system. The objective of the latter is to assist non-expert users, such as decision-makers, in carrying out proximity analyses. This is the first time that such a comprehensive framework has been proposed.

中文翻译:

用于特征数据的辅助邻近分析的框架

这种用于要素数据中辅助接近度分析的框架由将空间邻域用作基本构建块的接近度类层次结构组成。实例是孤立的对象之间或群集中的对象之间的空间关系,它们具有反射性/非反射性和对称性/非对称性的关系属性。该框架提出了生成空间邻域的方法,并讨论了如何处理邻近关系中固有的模糊性。它适用于流行病暴发的实际使用案例。该框架通过考虑以下因素来更新该领域的当前知识状态:(1)集群中的空间对象,(2)空间上共同扩展的区域,以及(3)分区链中的区域。它将生成空间邻里的方式与邻近度类别相关联,并引入了一些是非题,以GIS系统中的一系列功能来实现。后者的目的是帮助非专家用户(例如决策者)进行邻近度分析。这是第一次提出这样一个全面的框架。
更新日期:2019-08-03
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