نوع مقاله : پژوهشی
نویسندگان
1 استاد ژئومورفولوژی، گروه ژئومورفولوژی، دانشکده برنامه ریزی و علوم محیطی، دانشگاه تبریز، ایران
2 گروه ژئومورفولوژی ، دانشکده برنامه ریزی و علوم محیطی، دانشگاه تبریز
3 ، گروه ژئومورفولوژی، دانشکده برنامه ریزی و علوم محیطی، دانشگاه تبریز
4 گروه ژئومورفولوژی، دانشکده برنامه ریزی و علوم محیطی، دانشگاه تبریز
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
The data used included informational layers effective in land subsidence, such as: groundwater level decline (based on ten-year piezometric data), aquifer thickness and environment (based on drilling logs), recharge rate (using the Piscopo method integrating precipitation, slope, and permeability), pumping rate (based on discharge from exploitation wells), distance from faults, elevation and slope (from ALOS-PALSAR DEM), soil moisture (NDMI index from Sentinel-2 imagery), and land use. After preparing and rasterizing the layers in the GIS environment, the fuzzification process was performed using linear increasing membership functions (for factors like water level decline and aquifer thickness) and decreasing functions (for factors like recharge and elevation). Finally, the fuzzy layers were combined using the fuzzy gamma operator (with γ values between 0.7 and 0.9) to produce the final land subsidence potential map in five hazard classes (very low, low, moderate, high, and very high). Model validation was performed using subsidence data measured by three-frequency GPS.
کلیدواژهها [English]
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