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    Identifying Discontinuities in Trend Surfaces Using Bilateral Kernel Regression

    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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    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:
    Depositing User: Prof. Chris Brunsdon
    Date Deposited: 20 Feb 2015 10:32
    Journal or Publication Title: Transactions in GIS
    Publisher: Blackwell Publishing
    Refereed: Yes

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