Predict and Simulate Sustainable Urban Growth by Using GIS and MCE Based CA. Case of Famagusta in Northern Cyprus

The research study utilizes Multi Criteria Evaluation (MCE) method in geographic information systems (GIS) environment and uses MCE suitability maps with Cellular Automata (CA) for predicting simulating sustainable urban development scenarios Famagusta City. It represents first scenario-based simulations of the future growth as “do-nothing” “sustainable”. Under do-nothing scenario, Markov Chain probability analysis CA models is used temporal land-use/cover datasets based on images from 2002 2011. shows that, City moving away development. Future expansion both medium-density low-density zones are always located around existing built-up area along transportation lines. A similar model employed by applying policies policy driven scenario. As a main goal, includes three criteria, compactness, environmental protection, social equity. Additionally, brownfield development, distance center, soil characteristics, productivity, vegetation, protection areas (EPA), local services, open space criteria Analytical Hierarchy Process (AHP). Having such simulation combination MCE, GIS, has several advantages. Prediction presents possible alternative future; visualization decision making easier town planners supports spatial planning process; creates more realistic results our choices related to growth.