GeoInformatica

, Volume 20, Issue 1, pp 95–116 | Cite as

Kernel density estimation based on Ripley’s correction

Article

Abstract

In this paper, we investigate a technique inspired by Ripley’s circumference method to correct bias of density estimation of edges (or frontiers) of regions. The idea of the method was theoretical and difficult to implement. We provide a simple technique – based of properties of Gaussian kernels – to efficiently compute weights to correct border bias on frontiers of the region of interest, with an automatic selection of an optimal radius for the method. We illustrate the use of that technique to visualize hot spots of car accidents and campsite locations, as well as location of bike thefts.

Keywords

Border bias Edge correction Frontier GIS Kernel density estimation Polygons Ripley’s circumference method Spatial process Visualization 

Notes

Acknowledgments

The authors would like to thank Olivier Scaillet and John Wilson for stimulating comments, and helping us to improve the paper, as well as three anonymous reviewers.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.UQAMMontréal (Québec)Canada
  2. 2.CREM UMR CNRS 6211, Université de Rennes 1Rennes CedexFrance

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