License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GISCIENCE.2018.12
URN: urn:nbn:de:0030-drops-93400
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/9340/
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Murray, Alan T. ; Feng, Xin ; Shokoufandeh, Ali

Heterogeneous Skeleton for Summarizing Continuously Distributed Demand in a Region

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LIPIcs-GISCIENCE-2018-12.pdf (0.4 MB)

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.

BibTeX - Entry

@InProceedings{murray_et_al:LIPIcs:2018:9340,
  author =	{Alan T. Murray and Xin Feng and Ali Shokoufandeh},
  title =	{{Heterogeneous Skeleton for Summarizing Continuously Distributed Demand in a Region}},
  booktitle =	{10th International Conference on Geographic Information  Science (GIScience 2018)},
  pages =	{12:1--12:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Stephan Winter and Amy Griffin and Monika Sester},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/9340},
  URN =		{urn:nbn:de:0030-drops-93400},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.12},
  annote =	{Keywords: Medial axis, Object center, Geographical summary, Spatial analytics}
}

Keywords: Medial axis, Object center, Geographical summary, Spatial analytics
Collection: 10th International Conference on Geographic Information Science (GIScience 2018)
Issue Date: 2018
Date of publication: 02.08.2018

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