A framework for assisted proximity analysis in feature data

Rolf Grütter ()
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Rolf Grütter: Swiss Federal Research Institute WSL

Journal of Geographical Systems, 2019, vol. 21, issue 3, No 3, 367-394

Abstract: Abstract 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.

Keywords: Feature data; Proximity analysis; Spatial relation; Spatial neighborhood; GIS; Decision support (search for similar items in EconPapers)
JEL-codes: C65 D83 I18 (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10109-019-00304-3

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