Modelling Land-use and Land-cover Changes Using Markov-CA, and Multiple Decision Making in Kirkuk City

This paper tries to highlight on the analysis of the land-use and land-cover changes in Kirkuk city / Iraq that's due to repeated changes in structures of governments, wars and economic blockade over the past three decades that drove to chaos. The Markov-cellular automata model is an important and powerful tool in simulation. In this article a new Markov-CA model was developed based on built-in multi-regression model and multi-criteria evaluation approach to improve the representation of Markov-CA transition rules. Utilised data relate to the environmental and socio-economic are produce criteria layers and weights in order to output the suitability maps via a ranking method for periods 1984, 1990, 2000 and 2010, which have become conditional for the next step of Markov-CA generation. The suitability maps are compared in order to determine the best fit maps based on the values of the root equation (R 2 ). This comparison helpful to the stakeholders make better decisions and the best maps indicated best transition rules, which is represent the core of Markov-CA model. Thus, the resultant of best suitability maps derives a predefined transition rule for the end of Markov-CA model step. The approach used in the present study a mechanism for monitoring the land-use and land-cover changes in Kirkuk depend on Markov-CA is implemented and evaluated thru the different decision maker. The results assert that the model bears a high applicability and flexibility degree in land-use and land-cover changes.