Long Term Shoreline Change Analysis and Forecasting in Kuwait Bay via NDWI and DSAS (Global Journal of Human-Social Science, 2025)
Integrating remote sensing and geographic information systems (GIS) can be applied through shoreline monitoring. Coastal environments undergo both natural and anthropogenic processes that drive shoreline changes, making them highly dynamic systems. Kuwait Bay is characterized by its shallow waters and broad intertidal flats, where the tidal activities, wave action, and sediment transportation influence their morphological changes and contribute to critical socio-economic and environmental impacts. This study aims to quantify, calculate, and analyze the metrics of morphological shoreline changes along Kuwait Bay during and to predict the future shoreline position during 2034 and 2044. Four Landsat sensors (5, 7, 8, and 9) derived from the Google Earth Engine (GEE) platform were used for data acquisition. Shoreline changes were analyzed using the DSAS 5.0 extension in ArcMap 10.4, employing metrics such as SCE, NSM, EPR, and LRR, ArcGIS Pro, and Python (ArcPy library) for shoreline extraction and calculating (NDWI). The highest SCE value was 2889.63 m. As for the NSM, the maximum erosion exceeded that of accretion (2432.94 m and 1482.08 m, respectively). The EPR was 78.64 m/y -1 for erosion and 48.09 m/y -1 for accretion.