Local Cost Surface Models of Distance Decay for the Analysis of Gridded Population Data

Abstract

The paper evaluates some proposed improvements to the analysis of gridded population data, using as a case-study the religious segregation that is observed in gridded population data from Northern Ireland: first, the use of cost surfaces rather than simple Euclidean (straight line) distances to represent the interactions between gridded geographic areas; second, a method for creating gridded cost surfaces that takes account of vector features (such as roads and physical obstructions); third, the limitation of cost surfaces to a tightly defined 'local' set of areas, with a view to reduce computational overheads significantly without adversely impacting the accuracy of subsequent results. The results suggest that all three improvements have merit. The paper further explores the effect of using log-ratios rather than percentages (minimal) and of local rather than global measures of segregation (which allows for considerably greater insight into population characteristics). Although the case-study and results apply specifically to gridded population data, the results of the paper have wider implications for the analysis of any type of zonal data.

Neighbourhood change and spatial inequalities in Cape Town

“…Other possibilities are distance decay functions whereby the likelihood of interactions between people in areas are assumed to reduce as distance between areas increases. More sophisticated ways of measuring potential interactions (and thus exposure to people with different socio-economic characteristics) include the use of cost surface analysis, as applied by Lloyd (2015) in an analysis of residential segregation by religion in Belfast. Future work will assess some such schemas in the context of South Africa.…”