Bulletin de la Société Royale des Sciences de Liège, Vol. 85, 2016, p. 824 - 839 824 Prediction of Urban Growth through Cellular Automata-Markov Chain Ahmadreza EBRAHIMIPOUR 1,* , Mehdi SAADAT 2 , Amirreza FARSHCHIN 1 *Corresponding author Email Address : ar_ebrahimipoor@yahoo.com 1 Faculty member at Academic Centre for Education, Culture and Research (ACECR) 2 Researcher Abstract: Urban growth modelling can provide a useful tool to help decision-makers and urban planners evaluate different planning scenarios. Predicting the land uses and covers for sustainable utilization of lands cover is crucial due to rapid changes in the operations mainly arising from population growth and urbanization or perhaps because of changes in the stature of a city. The application of urban growth models such as CA-Markov could raise awareness about the future growth of the city aimed at consciously controlling and changing the land use planning in the future. The results of reviewing the urban growth process and land use changes around the city in the past mainly indicated the lands converted from agricultural use to urban areas across Bojnoord. Moreover, the hybrid model of CA-Markov was employed to predict the land use changes for the next 50 years with 10-year intervals between 2020 and 2070. The re- sults showed that if the process of urban growth and land use changes in areas around the city persist, the urban areas will double by 2070 compared to 2009, while the agricultural lands will shrink to half. This could provide the context for environmental issues in the future. Hence, it is recommended that the inner capacity of the city be used instead of ur- ban growth in the surrounding areas. Keywords: urban growth, cellular automata-Markov chain model, sustainable urban development. 1. Introduction The growing urbanization has been extremely accelerating due to migration to ur- ban areas over the past decade. It is expected that the global urban population will reach 5 billion people by 2030 [1]. Understanding the mechanism of urban growth is vital in urban planning and management so as to achieve sustainable urban form. In this process, model- ing tools can provide a helpful tool in planning and policy-making toward achievement of sustainable development [2]. Nowadays, remote sensing technologies and GIS as well as modeling and simulation provide an efficient tool in the service of urban management for detecting and predicting changes, measures and policies affecting the urban future growth planning. There are many strategies to model and predict changes in land cover and use,