Prediction of spatial land use changes based on LCM in Metropolises (Case study:Arak Metropolis, Iran )

Document Type : Science - Research

Authors

1 Associate Professor, Department of Environmental Sciences and Engineering, Arak University, Arak, Iran.

2 Bachelor, Secretary of Social Sciences, Farhangian University, Arak, Iran.

Abstract

Arak Metropolis and its surrounding lands have undergone many changes in recent years. This study aims at monitoring and predicting land use changes using LCM module in the Arak Metropolis. Land sat images of year 1976, 1996 and 2024 were employed to produce digital land use maps. The images were classified into fure classes including city, agriculture, rangeland and forest areas. LCM module in Idrisi GIS software was used to analyze the land use changes and predict the land uses status in 2024, based on artificial neural network (ANN) and Markov Chain analysis. ANN was trained with various influencing factors include distance from road, distance from city human made areas, distance from Land changed edge, distance from stream, elevation and slope. The results indicated that 9343 hectares (50.38) of the rangeland cover have been degraded during the period 1976-2024. Furthermore, the agriculture and city human made areas have been increased 3194ha (147.72) and 4547ha (83.53) in comparison to initial situation. Also, the result shows that rangeland and agriculture and forest areas will decrease in the year 2040 compare to 2024 while, city human made areas increase.

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History

  • Receive Date: 10 June 2023
  • Revise Date: 29 November 2024
  • Accept Date: 10 January 2025

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