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Heterogeneous Skeleton for Summarizing Continuously Distributed Demand in a Region

Authors Alan T. Murray , Xin Feng , Ali Shokoufandeh



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Author Details

Alan T. Murray
  • Department of Geography, University of Santa Barbara, CA, USA
Xin Feng
  • Department of Geography, University of Santa Barbara, CA, USA
Ali Shokoufandeh
  • Department of Computer Science, Drexel University, Philadelphia, PA, USA

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Alan T. Murray, Xin Feng, and Ali Shokoufandeh. Heterogeneous Skeleton for Summarizing Continuously Distributed Demand in a Region. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 12:1-12:11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.GISCIENCE.2018.12

Abstract

There has long been interest in the skeleton of a spatial object in GIScience. The reasons for this are many, as it has proven to be an extremely useful summary and explanatory representation of complex objects. While much research has focused on issues of computational complexity and efficiency in extracting the skeletal and medial axis representations as well as interpreting the final product, little attention has been paid to fundamental assumptions about the underlying object. This paper discusses the implied assumption of homogeneity associated with methods for deriving a skeleton. Further, it is demonstrated that addressing heterogeneity complicates both the interpretation and identification of a meaningful skeleton. The heterogeneous skeleton is introduced and formalized, along with a method for its identification. Application results are presented to illustrate the heterogeneous skeleton and provides comparative contrast to homogeneity assumptions.

Subject Classification

ACM Subject Classification
  • Applied computing → Operations research
  • Information systems → Geographic information systems
  • Theory of computation → Computational geometry
Keywords
  • Medial axis
  • Object center
  • Geographical summary
  • Spatial analytics

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