Prediction of Land Use Changes Using CA-Markov: A Case Study of Yasuj City
2020
Asghari Sereskanrood, Sayyad | Ardeshirpey, Aliasghar
Land use mapping and land use maps related to the prediction of spatial-temporal changes provide a major portion of the information required by urban planners and administrators to adopt correct measures and make principled decisions to achieve sustainable urban development. The purpose of this investigation was to examine land use and land cover changes in Yasuj city in the past and, consequently, to predict the spatial pattern of the land structure in the near future. In this study, the satellite object-based image analysis of the images taken by Landsat satellite in 1990, 2000, and 2018 was used to make a dynamic modeling of Yasuj lands use changes. Moreover, a combination of the Markov chain and automated cells were employed to predict land use changes. The results showed that during the period between 1991 and 2018, the area of pasturelands decreased by 7.18%, while the total area of residential areas increased by 2.02%. That is to say, the spread of Yasuj city has led to the increase in the residential and irrigated cultivation lands, while it has decreased pastures, forests, dryland cultivation areas, barren lands, and gardens. Furthermore, the development process of Yasuj city shows its tendency to physical-spatial expansion in all dimensions. Moreover, the land use map for the years 2030 and 2040 was predicted by the CA-Markov model. The results showed that during the period 2018-2040, pasturelands, dryland farming areas, and forests will decrease 1.08%, 1.03%, and 1.47%, respectively, residential areas will increase by 4.17%, and the waterbody will change a little. The results of the study show the high efficiency of the CA-Marcov model for monitoring the trend of changes, especially urban growth, for the coming years based on the pattern of changes in the past years.
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Эту запись предоставил University of Tehran
