Abstract

Dasymetric mapping using high resolution address point datasets
Track: Education
Authors: Paul Zandbergen

Mismatching sets of boundaries present a persistent problem in spatial analysis for many different applications. Dasymetric mapping techniques provide one possible solution for this. The current research examines the use of address points as ancillary data for dasymetric mapping of population. Datasets from 16 counties in Ohio were used in the analysis. Results indicate that address points perform significantly better compared to other types of ancillary data. The overall error in population estimates using address points is 4.9% compared to 10.8% for imperviousness, 11.6% for land cover, 13.3% for road density, 18.6% for nighttime lights and 21.2% for areal weighting. Current developments in the growing availability of address point datasets and the implications for spatial demographic analysis are discussed.