Analysis and prediction of land cover/use changes in Mosul city using a combined approach of object-oriented processing and CA-Markov model

Document Type : Science - Research

Authors

1 Faculty member, Department of Geography and Urban Planning, Maragheh University, Maragheh, Iran

2 عضو هیات علمی گروه جغرافیا و برنامه ریزی شهری دانشگاه مراغه

3 گروه جغرافیا و برنامه ریزی شهری دانشگاه مراغه

Abstract

The present study investigated the analysis and prediction of land cover/use changes in Mosul city . In this study,, Landsat and Sentinel satellite images were prepared for different time periods from 2000 to 2024 with an interval of 8 years and the necessary pre-processing was performed. Then, land cover/use classes were extracted. The processing results were exported in the eCognition Developer software as a shape file to be used in the GIS environment for cartography and calculating land use changes. Next, using the CA-Markov model in Terrst software, land cover/use changes over time were simulated and predicted. The transition probability matrix between land cover/use types in different time periods was calculated and showed the probability with which each type of cover will be converted to another type. The results show that the area of built-up areas has increased from 132,380 km2 in 2000 to 234,143 km2 in 2024. This unbalanced growth has been influenced by economic, social and post-crisis reconstruction programs. Also, agricultural land has decreased from 33,657 km2 to 25,709 km2, representing a more than 5% decrease in agricultural land. Barren land has also experienced a decrease of approximately 17.69%. In the field of water resources, the area of irrigated land has decreased from 8,951 km2 to 5,316 km2 and green space from 8,767 km2 to 6,147 km2. The vulnerability analysis of the changes shows that 24.29% of the city area is in the “very high vulnerability” category, which seriously threatens the food security of the region.

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History

  • Receive Date: 12 August 2025
  • Revise Date: 04 February 2026
  • Accept Date: 22 February 2026

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