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

Abstract

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