University of Tehran Press Iranian Journal of Soil and Water Research 2008-479X 56 3 2025 05 22 Spatio-temporal analysis and future prediction of land use changes using multitemporal remotely sensed data and GIS techniques in Hirmand River Basin Spatio-temporal analysis and future prediction of land use changes using multitemporal remotely sensed data and GIS techniques in Hirmand River Basin 785 805 102207 10.22059/ijswr.2025.386623.669848 FA Mahboubeh Ebrahimian Department of Water Resources Management. Hamoun International Wetland Research Institute, Research Institute of Zabol. Roghayeh Karami Department of Natural Ecosystem Management, Hamoun International Wetland Research Institute, Research Institute of Zabol Journal Article 2024 12 07 This study aimed to analyze and quantify land use/land cover changes in the transboundary Hirmand River basin over the past 30 years and to predict probable changes for next 20 years. Land cover maps of 1992, 2002, and 2022 were generated using Landsat images of TM and OLI sensors. The Random Forest algorithm was employed for classification and identification of land use classes. The overall accuracy and Kappa index for all classified maps were over 80% and 0.78, respectively. CA-Markov model was used to predict the changes using the land use maps first simulated for 2022, after validation, the future maps of 2030 and 2040 projected. The Kappa index of 0.82 indicated the model's high ability to simulate land use and cover changes in the basin. Water bodies experienced a 97% reduction from 1992 to 2022, with a significant portion of the remaining water body related to the Hamoun Wetland. This trend is expected to reverse slightly, with the water body area increasing from 0.05% in 2022 to 0.36% and 0.37% in 2030 and 2040, respectively. Forests have lost 20% of area, and this decline is likely to continue. Dense rangelands have lost approximately 75% of their areas by 2022, and it is projected that they will decline to 34% by 2040, while poor rangelands have increased by around 2%. Meanwhile, agricultural land has expanded by approximately 115% by 2022, increasing from 2.72% to 5.88%. It is anticipated that agricultural land will experience a further increase of 20–30% by 2040. This study aimed to analyze and quantify land use/land cover changes in the transboundary Hirmand River basin over the past 30 years and to predict probable changes for next 20 years. Land cover maps of 1992, 2002, and 2022 were generated using Landsat images of TM and OLI sensors. The Random Forest algorithm was employed for classification and identification of land use classes. The overall accuracy and Kappa index for all classified maps were over 80% and 0.78, respectively. CA-Markov model was used to predict the changes using the land use maps first simulated for 2022, after validation, the future maps of 2030 and 2040 projected. The Kappa index of 0.82 indicated the model's high ability to simulate land use and cover changes in the basin. Water bodies experienced a 97% reduction from 1992 to 2022, with a significant portion of the remaining water body related to the Hamoun Wetland. This trend is expected to reverse slightly, with the water body area increasing from 0.05% in 2022 to 0.36% and 0.37% in 2030 and 2040, respectively. Forests have lost 20% of area, and this decline is likely to continue. Dense rangelands have lost approximately 75% of their areas by 2022, and it is projected that they will decline to 34% by 2040, while poor rangelands have increased by around 2%. Meanwhile, agricultural land has expanded by approximately 115% by 2022, increasing from 2.72% to 5.88%. It is anticipated that agricultural land will experience a further increase of 20–30% by 2040. https://ijswr.ut.ac.ir/article_102207_be0f5741007ac5a3297532062603ae5b.pdf