A Morphological Approach to Predicting Urban Expansion

Abstract

Many methods for modeling urban expansion are available. Most of these computational models demand a variety of large-scale environmental and socio-economic data to investigate the relationship between urban expansion and its driving forces. These requirements are not always fulfilled, particularly in developing countries due to a lack of data availability. This necessitates methods not suffering from data limitations to ease their application. Consequently, this research presents a morphological approach for predicting urban expansion on the basis of spatiotemporal dynamics of urban margins by investigating the interior metropolitan area of Tehran, Iran as a case study. To assess the model's performance, urban expansion is monitored from 1976 to 2012. The proposed model is evaluated to ensure that the prediction performance for the year 2012 is acceptable. For the year 2024, the model predicts Tehran's urban expansion at an overall R2 of 88%. Accordingly, it is concluded that: (1) although this approach only inputs urban margins, it represents a suitable and easy-to-use urban expansion model; and (2) urban planners are faced with continuing urban expansion.