Urban land use and land cover change analysis and modeling a case study area Malatya, Turkey

Abstract

This research was conducted to analyze the land use and land cover changes and to model the changes for the case study area Malatya, Turkey. The first step of the study was acquisition of multi temporal data in order to detect the changes over the time. For this purpose satellite images (Landsat 1990-2000-2010) have been used. In order to acquire data from satellite images object oriented image classification method have been used. To observe the success of the classification accuracy assessment has been done by comparing the control points with the classification results and measured with kappa. According to results of accuracy assessment the overall kappa value found around 75%. The second step was to perform the suitability analysis for the urban category to use in modeling process and it has been done using the Multi Criteria Evaluation method. The third step was to observe the changes between the defined years in the study area. In order to observe the changes land use/cover maps belongs to different years compared with cross tabulation and overlay methods, according to the results it has been observed that the main changes in the study area were the transformation of agricultural lands and orchards to urban areas. Every ten years around 1000ha area of agricultural land and orchards were transformed to urban. After detecting the changes in the study area simulation for the future has been performed. For the simulation two different methods have been used which are; the combination of Cellular Automata and Markov Chain methods and the combination of Multilayer Perceptron and Markov Chain methods with the support of the suitability analysis. In order to validate the models; both of them has been used to simulate the year 2010 land categories using the 1990 and 2000 data. Simulation results compared with the existing 2010 map for the accuracy assessment (validation). For accuracy assessment the quantity and allocation based disagreements and location and quantity based kappa agreements has been calculated. According to the results it has been observed that the combination of Multilayer Perceptron and Markov Chain methods had a higher accuracy in overall, so that this combination used for predicting the year 2020 land categories in the study area. According to the result of simulation it has been found that; the urban area would increase 1575ha in total and ~936ha of agricultural lands and orchards would be transformed to the urban area if the existing trend continued.