A Voronoi-like model of spatial autocorrelation for characterizing spatial patterns in vector data

Xiang Zhang, Tinghua Ai, Jantien E. Stoter

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

3 Citations (Scopus)

Abstract

The paper presents a computational model of spatialautocorrelation based on a Voronoi-like auxiliary structure. It shows that the Voronoi-like partition of map objects can be used to discern spatial patterns (e.g. clustered or dispersed) of geographic phenomena. In this paper, we transform the problem of characterizing the patterns for different geometry types (i.e. points, curves, and polygons) into a process of calculating spatial autocorrelation based on the auxiliary partition units. The method is shown to be successful for the designated tasks.
Original languageEnglish
Title of host publication2009 Sixth International Symposium on Voronoi Diagrams
Subtitle of host publication23-26 June 2009, Copenhagen, Denmark
EditorsF. Anton
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages118-126
ISBN (Electronic)978-0-7695-3781-8
ISBN (Print)978-0-7695-3781-8
DOIs
Publication statusPublished - 2009
Event6th International Symposium on Voronoi Diagrams 2009 - Copenhagen, Denmark
Duration: 23 Jun 200926 Jun 2009
Conference number: 6

Conference

Conference6th International Symposium on Voronoi Diagrams 2009
CountryDenmark
CityCopenhagen
Period23/06/0926/06/09

Keywords

  • ADLIB-ART-370
  • GIP

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