Spatial Modeling of Land Degradation Index (LDI) Using Geographic Artificial Intelligence in Al-Anbar Governorate – Iraq
DOI:
https://doi.org/10.59992/IJESA.2026.v5n8p5Keywords:
Spatial Modeling, Environmental Degradation, Geographic Artificial Intelligence, Remote Sensing, Environmental IndicesAbstract
This study aims to monitor, assess, and analyze Land Degradation (LDI) in the study area for the year 2025 using remote sensing techniques. The study was based on extracting a set of environmental indicators, namely NDBSI, NDMI, NDVI, and LST, for the years 2015 and 2025. These indicators were integrated to produce the 2025 land degradation map. In addition, a predictive modeling approach was conducted to forecast land degradation for the year 2030 using Geographic Artificial Intelligence (GeoAI) in order to understand the temporal trends of environmental change and identify the future trajectory of land degradation within the study area. The prediction results generated by the Random Forest model indicated an increase in the area classified as moderate land degradation from 60.79% in 2025 to 66.90% in 2030, while the area experiencing high land degradation is projected to increase from 0.07% to 1.30%. These findings suggest a future trend toward intensified land degradation if the current environmental conditions persist.
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