Urban growth pattern modeling using logistic regression

Abstract

Transformation of land use/ land cover change occurs due to the numbers and activities of people. Urban growth modeling has attracted substantial attention because it helps to comprehend the mechanisms of land use change and thus helps relevant policies made. This paper tends to apply logistic regression to model urban growth in the Jiayu county of Hubei province, China. It is applied in a GIS environment to calculate variables and, then, in SPSS to discover the relationships between urban growth and the driving forces. The relative operating characteristic (ROC) shows the modeling accuracy with the curve 0.891 with standard error 0.001. A probability map is generated finally to predict where urban growth will occur as a result of the computation. The result shows the model simulates urban growth well in the county scale. © 2011 Wuhan University and Springer-Verlag Berlin Heidelberg.