Author: Mennis, Jeremy

Source: Cartographic Journal, The, Volume 43, Number 2, July 2006 , pp. 171-179(9)

Publisher: Maney Publishing

Abstract:

Geographically weighted regression (GWR) is a local spatial statistical technique for exploring spatial nonstationarity. Previous approaches to mapping the results of GWR have primarily employed an equal step classification and sequential no-hue colour scheme for choropleth mapping of parameter estimates. This cartographic approach may hinder the exploration of spatial nonstationarity by inadequately illustrating the spatial distribution of the sign, magnitude, and significance of the influence of each explanatory variable on the dependent variable. Approaches for improving mapping of the results of GWR are illustrated using a case study analysis of population density–median home value relationships in Philadelphia, Pennsylvania, USA. These approaches employ data classification schemes informed by the (nonspatial) data distribution, diverging colour schemes, and bivariate choropleth mapping.

Document Type: Research Article

DOI: http://dx.doi.org/10.1179/000870406X114658

Publication date: 2006-07-01

More about this publication?

• Editorial Board
• Information for Authors
• Submit a Paper
• Subscribe to this Title
• Membership Information
• Information for Advertisers
• Terms & Conditions
• Top articles
• MORE Open Choice
• ingentaconnect is not responsible for the content or availability of external websites

Related content

• In this: publication
• By this: publisher
• In this Subject: Geography
• By this author: Mennis, Jeremy

Website © Publishing Technology. Article copyright remains with the publisher, society or author(s) as specified within the article.

• Terms and conditions
• Privacy policy
• Information for advertisers