Predicting locational trend of land use changes using CA-Markov model (Case study: Safarod Ramsar watershed)

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Article Type:
Case Study (دارای رتبه معتبر)
Abstract:
Predicting land use changes using satellite imagery is now a useful tool for helping planners in complex situations. The purpose of this study was to detect and predict land use changes during the 28-year period (1986-2014) by CA- Markov model in the Safarood-Ramsar watershed of Mazandaran province. In this research, land use and NDVI maps were prepared using Landsat TM (1986), ETM+ (2000) and OLI (2014) satellite images. The accuracy of the CA-Markov model was estimated using the Kappa index of 87%. In order to calibrate the CA-Markov model, the land use map was prepared in 2014, and the Kappa coefficient of the mapping from modeling and user base map (2014) was 82%. The results showed that during the period between 1986 and 2014, the area of forest lands decreased by 10.26% and the total area of residential areas increased by 3.27%. The land use map for the years 2021 and 2028 was predicted by the CA-Markov model. The results showed that during the period 2014-2028, forested lands and rangelands decreased by 4.92% and 1.7%, respectively. Residential areas will increase by 8.04% and the agricultural land will change slightly, indicating the changes in land use to residential land.
Language:
Persian
Published:
Journal of Rs and Gis for natural Resources, Volume:10 Issue: 1, 2019
Pages:
106 to 120
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