Volume 20, Issue 56 (3-2020)
jgs 2020, 20(56): 141-158 |
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afifi M E. (2020). Modeling land use changes using Markov chain model and LCM model. jgs. 20(56), 141-158. doi:10.29252/jgs.20.56.141
URL: http://jgs.khu.ac.ir/article-1-3243-en.html
URL: http://jgs.khu.ac.ir/article-1-3243-en.html
Islamic Azad University of Lourestan, Islamic Azad University of Lourestan , afifi.ebrahim6353@gmail.com
Abstract: (6295 Views)
Land use maps are considered as the most important sources of information in natural resource management. The purpose of this research is to review, model, and predict landslide changes in the 30-year period by LCM model in Shiraz. In this research, TM Landsat 4, 5 and OLI Landsat 8 images were used for 1985, 2000 and 2015 respectively, as well as topographic maps and area coverage. Subsequent validation and detection of changes were made using the prediction model of variation The use of LCM markov and the model of user change approach. The images were classified into four classes of Bayer, garden, urban lands, and arable land for each of the three periods. According to the results, aquaculture is the most dynamic user in the area, which has led to an upward trend during 1985-2015, so that the amount (4337 ha, 12.7%) has been added to this area. The Bayer user change trend was also a downward trend during 1985 to 2015, reducing the 99.1995 hectares of this class. The results of the change in the 1985 changes with a kappa coefficient of 0.88, in the 2000 period with a CAAP of 0.77, and in the period 2015 with a Kappa coefficient of 0.92. The results of the change detection in 2030 are such that if the current trend continues in the region, 20.33% will be added to the crop category, so that in 2030, agricultural cropping will be 95.60% of the area of the area Gets In the Bayer and Garden uses 21.22% and 0.21% of the total area of each user has been reduced and has been added to the urban area. The prediction map derived from the Markov chain model is very important for providing a general view for better management of natural resources.
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This work is licensed under a Creative Commons — Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)