Change detection and prediction of urban land use changes by CA–Markov model (case study: Talesh County)

Abstract

Earth’s surface has continued to change due to human activities and natural reasons. Land use and land cover (LULC) change is one of the significant issues which has considerable impacts on environment and its processes. Access to precise and up-to-date data of LULC through satellite images provides a great opportunity to detect, monitor and model a prediction of the future changes. The purpose of this research is to monitor and study land use changes, especially in urban land, during the past years and the possibility of predicting future changes by CA–Markov in Talesh County. In this research, satellite imagery of ETM 2000, LISS III 2007 and OLI-TIRS 2014 have been used. Supervised classification of images is done using the maximum likelihood method. Then the accuracy of the generated land use maps was evaluated using the overall accuracy and kappa coefficients. The results of the evaluation showed that land use maps from 2000, 2007 and 2014 had kappa coefficients equal to 0.86, 0.85 and 0.89, respectively, and an overall accuracy of 91%, 90%, and 93%. The land use map for 2028 has been predicted by the CA–Markov model. The results of the model forecast indicate a significant increase in the size of finished and urban areas by 29/83% and a reduction of the area of agricultural land, forests, and wastelands, respectively, to the 3/12, 0.59, and 0.48% over the next 14 years in the area under study. The model also showed that the future development of the city would occur linearly and mainly around the city of Hashtpar, especially on the western and eastern borders of the city.