A Review of Driving Factors, Scenarios, and Topics in Urban Land Change Models

Abstract

Due to the increase in future uncertainty caused by rapid environmental, societal, and technological change, exploring multiple scenarios has become increasingly important in urban planning. Land Change Modeling (LCM) enables planners to have the ability to mold uncertain future land changes into more determined conditions via scenarios. This paper reviews the literature on urban LCM and identifies driving factors, scenario themes/types, and topics. The results show that: (1) in total, 113 driving factors have been used in previous LCM studies including natural, built environment, and socio-economic factors, and this number ranges from three to twenty-one variables per model; (2) typical scenario themes include “environmental protection” and “compact development”; and (3) LCM topics are primarily growth prediction and prediction tools, and the rest are growth-related impact studies. The nature and number of driving factors vary across models and sites, and drivers are heavily determined by both urban context and theoretical framework.