Brunsdon, Chris (2011) Identifying Discontinuities in Trend Surfaces Using Bilateral Kernel Regression. Transactions in GIS, 15 (3). pp. 385-400. ISSN 1467-9671

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Abstract

Following a brief review of the kernel regression approach to estimating surface models of the form z = f(x,y) + e, this article will consider the situation where f is not a continuous surface function, and in particular where the discontinuities take the form of one-dimensional breaks in the surface, and are not specified a priori. This form of model is particularly useful when visualizing some social and economic data where very rapid changes in geographical characteristics may occur – such as crime rates or house prices. The article briefly reviews approaches to this problem and proposes a novel approach (Bilateral Kernel Regression) adapting an algorithm from the field field of image processing (Bilateral Filtering), giving example analyses of synthetic and real-world data. Techniques for enhancing the basic algorithm are also considered.

Item Type:	Article
Keywords:	Trend Surfaces; Bilateral Kernel Regression;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
Item ID:	5887
Identification Number:	https://doi.org/10.1111/j.1467-9671.2011.01241.x
Depositing User:	Prof. Chris Brunsdon
Date Deposited:	20 Feb 2015 10:32
Journal or Publication Title:	Transactions in GIS
Publisher:	Blackwell Publishing
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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