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Analysis and prediction of land cover changes by applying Cellular Automata-Markov model and geo-information: An arid and semi-arid river basin, Iran
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  • Sajad Khoshnood Motlagh,
  • Amir Sadoddin,
  • Amin Haghnegahdar,
  • Saman Razavi,
  • Khalil Ghorbani
Sajad Khoshnood Motlagh
Gorgan University of Agricultural Sciences and Natural Resources
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Amir Sadoddin
Gorgan University of Agricultural Sciences and Natural Resources
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Amin Haghnegahdar
University of Saskatchewan
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Saman Razavi
University of Saskatchewan
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Khalil Ghorbani
Gorgan University of Agricultural Sciences and Natural Resources
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Abstract

The prediction of future land cover changes is an important step in proper planning and management of watersheds. Various methods exist for this purpose. In this study, land cover changes were investigated in the Hable-Rud River basin in Iran, an arid and semi-arid region, using remote sensing and Geographic Information Systems (GIS). First, a supervised classification technique was applied to Landsat images acquired for 1986, 2000 and 2017 using the maximum likelihood method. Then, using pixel-by-pixel change detection, the land cover changes were predicted for 2017 and 2040 using a Cellular Automata (CA)-Markov model. The descriptive variables used included slope, aspect, elevation, and calculated distances from various land features such as rivers, roads, industrial areas, residential areas, saline land, and land in agricultural production. The predictions for 2017 were validated using the derived map from a Landsat image of 2017 with a resulting standard Kappa index of 0.74. According to the prediction results for 2040, the areas of rangeland and saline land will increase by approximately 6.5% and 2%, respectively, whereas the areas of bare land and agricultural land will decrease by approximately 6% and 2%, respectively. Moreover, the analysis of historical records since 1986 showed that the annual streamflow and precipitation have reduced by almost 44% and 29%, respectively. The reductions, particularly to streamflow, can be attributed largely to agriculture expansion, rapid population growth, and industrial developments. The analysis of the results indicates a need for more effective design, planning, and development of land cover policies for ecosystem protection.

Peer review status:IN REVISION

06 Mar 2020Submitted to Land Degradation & Development
11 Mar 2020Assigned to Editor
11 Mar 2020Submission Checks Completed
18 Mar 2020Reviewer(s) Assigned
26 Apr 2020Review(s) Completed, Editorial Evaluation Pending
30 Apr 2020Editorial Decision: Revise Minor