Abstract

Many regional environmental problems are the consequence of anthropogenic activities involving land cover changes. Temporal land cover data with social aspects are critical in tracing relationships of cause and effect on variables of interest with the effects of context on behaviour, or with the process of human environment interaction and are also useful for governance of urbanising cities. Many cities are now rapidly urbanising and undergoing redevelopment for economic purposes with new roads, infrastructure improvements, etc. raising the necessity to understand the dynamics of urban growth process for planning of natural resources. Cellular automata (CA), an artificial intelligence technique based on pixels, states, neighbourhood and transition rules is useful in modelling the urban growth process due to its ability to fit such complex spatial nature using simple and effective rules. The present work develops calibration of a CA model by taking spatial and temporal dynamics of urban growth into account. The effectiveness of this technique is demonstrated by capturing the growth pattern of Bangalore city, India with historical remote sensing and population data.

Keywords: artificial intelligence; cellular automata; governance; land use model; urban growth