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چکیده
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Land degradation is a major environmental issue that puts ecosystem services, agricultural productivity and people's well-being at risk, especially in semi-arid areas, where urban growth rates are high. Reliable assessments of spatial information are needed for land use and sustainable development planning. This study created and evaluated an integrated Remote Sensing (RS) and Geographic Information System (GIS) based framework to quantify the amount of land degradation and study the relationship between the amount of land degradation and urban growth in the Erbil Governorate, Iraq, between 2014-2024. Multi-temporal Landsat 8 and 9 data were fused with the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) precipitation data and morphometric variables from Shuttle Radar Topography Mission (SRTM) and were analyzed using a Fuzzy Analytical Hierarchy Process (FAHP) to get composite Land Degradation Index (LDI). Six key indicators were normalized, weighted and integrated presenting vegetation condition, thermal stress, climatic gradients and hydro-geomorphological controls on degradations, such as Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Land Use/Land Cover (LULC), rainfall, slope and Stream density. Urban expansion was mapped with the help of LULC classification using Random Forest (RF) response classifiers of 2014 and 2024, the results of which indicate the net increment in built-up areas and the main radial expansion around Erbil City and its peri-urban corridors. When spatially cross-tabulated to the classes of the LDI, the results showed a significant change and an increase in the proportion of severely degraded land lie within urban areas through 2024 and a significant change and improvement in the statistical association of urban extent and extent of degradation intensity through time. Model reliability was also determined using 80 field soil samples and laboratory analyses to arrive at an independent Sample Degradation Index (SDI). The FAHP-based LDI had an overall accuracy of 80% and a Kappa coefficient of 0.72, which showed an improvement over two recently published LDI approaches that were replicated and applied to the same case study. These results demonstrate the robustness and transferability of the FAHPs-based regional land degradation assessment framework and its potential as a decision support tool for the management of the coupled bilateral built and wetland relations of urban growth and land degradation in dryland environments.
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