Predicting of Land Use Changes for 2030 Using Remote Sensing and Landsat Multi-Temporal Images (Case study: Mashhad)
2018
Rayegani, Behzad | Jahani, Ali | Satari Rad, Amir | Shoghi, Narges
By predicting land use changes, the extent of the expansion and destruction of resources can be determined, and future policies can be pushed in the right direction. The aim of this study is modeling the land use changes process in Mashhad by using Landsat satellite images related to 1989, 2008, and 2014. Initially, based on the hybrid method (unsupervised and supervised classification combination), land uses were classified into six classes. Then, by using the Markov chain, the transmission matrix between 1989 and 2008 was calculated and by applying it in the Markov-CA model, the land use map for 2014 was predicted. In the following, the predicted land use map for 2014 with the actual 2014 land use map was compared with the Crosstab table, and the total Kappa coefficient was 0.91. Accordingly, the accuracy of the predicted Markov-CA model was confirmed. Finally, this model was used to predict land use in 2030. Therefore, by entering the 2014 reference map as the base map, the 2030 land use map prediction map was extracted. The results showed that from 1998 to 2030 there will be an increasing trend in urban and arid lands and a decreasing trend in agricultural lands and gardens. The results indicate that the Markov-CA model can contribute to the design of a sustainable urban system.
Afficher plus [+] Moins [-]Informations bibliographiques
Cette notice bibliographique a été fournie par University of Tehran
Découvrez la collection de ce fournisseur de données dans AGRIS
