Simulating Future Land Use/Land Cover of Tigris River Basin Assuming the Continuation of the Conditions During 2018 and 2023.
(ندگان)پدیدآور
Ghanbari, AbolfazlKhaleel-Gharibawi, AyatAbdulkareem-Rubaiee, HalaJeihouni, Mehrdad
نوع مدرک
TextResearch Paper
زبان مدرک
Englishچکیده
Environmental planning and resource management necessitate an analysis of changes in land use and land cover (LULC). In recent years, climate change and human activities, notably the erection of the Ilisu dam, have adversely impacted the Tigris River Basin (TRB), one of the most vital natural resources in Western Asia, resulting in significant alterations in its LULC. Based on this, the present study developed multi-temporal (2003-2023) LULC maps for TRB through classifying Landsat images using the random forest (RF) and support vector machine (SVM) algorithms, and simulating future LULC states (2028) employing the cellular automata (CA)-Markov model. RF exhibited better performance than SVM in the classification of Landsat images, and its results were chosen for further investigation. The CA-Markov model simulated the landscape map of 2028 by considering LULC dynamics between 2018 and 2023. The model's performance was validated, confirming acceptable results with an accuracy rate of 0.798 and F1 score of 0.789. Notably, LULC changes in TRB were critical, including a reduction in water resources, wetlands and croplands. This could lead to several environmental challenges, highlighting the significance of quick LULC changes. The construction of the Ilisu Dam on the Tigris River in Turkey has worsened the situation by exacerbating water shortages, expanding bare ground, harming wetlands, reducing water quality, soil salinization, and damaging the aquatic ecosystems. The drying wetlands and expanding bare grounds will become potential dust sources in the future and affect surrounding countries. Accordingly, intergovernmental actions and special policies are needed to manage this environmental crisis.
کلید واژگان
remote sensingTigris River Basin
Random forest
Support vector machine
CA-Markov
LULC simulation
شماره نشریه
2تاریخ نشر
2024-12-011403-09-11
ناشر
University of Tehranسازمان پدید آورنده
Department of Remote Sensing and GIS, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, IranDepartment of Remote Sensing and GIS, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran
Department of Remote Sensing and GIS, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran
Department of Remote Sensing and GIS, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran
شاپا
2008-0875475-2345X



