Land use change modeling using integration of GIS-based cellular automata and weights-of-evidence techniques

Document Type: Original Article


Faculty of Architecture and Urban Planning, Islamic Azad University, Qazvin Branch, Qazvin, Iran


In recent decades, attaining urban sustainability is the primary goal for urban planners and decision makers. Among various aspects of urban sustainability, environmental protection such as agricultural and forest conservations is very important in tropical countries like Malaysia. In this regard, prediction of future land use changes is very useful for Malaysian government. This paper attempts to propose an integrated modeling approach to predict the future land use changes using integration of GIS-based cellular automata and weights-of-evidence techniques. The cellular automata (CA) were applied for calculating land use conversion. In addition, weights-of-evidence (WoE) which is based on Bayes theory using several urban-related parameters was utilized to calibrate CA model and to support the transitional rule assessment. The results showed that the modeling approach supports the essential logic of probabilistic methods and indicates that spatial autocorrelation of various land use types and accessibility is the main drivers of urban land use changes.