Abstract:

The prediction of the expansion of urban built-up areas is an important management basis for preventing the spread of cities.At present,the CA-Markov model has become an important method for the expansion of urban built-up areas.The model is more sensitive to the method of index weight assignment.In the past,the single index assignment method affected the accuracy and credibility of the extended prediction of urban built-up areas.To this end,this paper proposes to improve the CA-Markov model by integrating AHP and logistic regression models based on the traditional weighted assignment method.The paper selects Dali city,Yunnan province as a case study to simulate and forecast the expansion of urban built-up areas in 2020 and 2030,and finally verifies the accuracy.The results show that:①Kappa index can reach 96.8%,the prediction results have a good consistency.②The expansion of urban built-up areas in Dali City continues to expand outward,with the southeast and northwest directions as the main expansion direction between the two built-up areas.Research provides a combination of weight assignment method to improve the CA-Markov model,which will provide planners with strong support in the future planning.

Key words: urban expansion simulation, CA-Markov model, analytical hierarchy process, logistic regression model, integrated analytic hierarchy process and logistic regression model