Flood Monitoring and Damage Assessment of Gwadar City Using GIS and Remote Sensing

Abstract

Monitoring floods using Geographic Information System (GIS) and Remote Sensing (RS) is important for understanding the damages caused by flood and spatial patterns of inundation. For this study we use supervised image classification and freely available Sentinel-2 multispectral imagery and ASTER Digital Elevation Model (DEM) to map spatial extent of flood and assess damages to infrastructure caused by the February 2024 flash flood in Gwadar City. The process of Image classification was carried out using the Maximum Likelihood Supervised in ArcMap 10.8. In order to find the spatial pattern of flood we divided the land-use and land-cover (LULC) in Gwadar city into four classes. They were built-up areas, open/barren land, vegetation, and water bodies. The results of the analysis revealed extensive transformation of land-use and land-cover classed after the flood. The results showed that water bodies expanded from 0.54% to 15.26% and significant reductions in barren land (−18.35%), built-up areas (−7.89%), and vegetation (−38.26%). To assess the damages to infrastructure the whole land-use and land-cover was digitized from high-resolution mosaicked Google Earth images. Later the flood or water mask was overlaid on the land-use and land-cover layer. This approach provided us with a clear visualization of the extent of damages and inundation across different land-use and land-cover classes. The results indicated that residential areas were the most affected, with approximately 9.69% of all households impacted, followed by commercial areas where about 3.55% of the total commercial units experienced flood damage. The classification achieved an overall accuracy of 89% and a Kappa coefficient of 0.84, confirming the reliability of the analysis. This research shows that using multispectral satellite data offers a cost-effective approach for flood mapping and damage assessment, which is particularly valuable for climate resilient urban planning in coastal Pakistan.

Keywords: Gwadar City; Flood Mapping; Remote Sensing; GIS; Sentinel-2; ASTER DEM; Land Use/Land Cover; Damage Assessment; Spatial Analysis.