Rapid Assessment of Economic Impacts from Inundation in Karawang, Indonesia: A Multi-Platform Geospatial Approach

Inundation poses significant challenges to the economic stability of Karawang, Indonesia, a key rice production region located near the coastline and at low elevations. These areas are highly vulnerable to flooding from high rainfall and sea level rise events. Remote sensing data plays a critical role in monitoring these events. This study combines several geospatial tools—SatGPT, Google Earth Engine (GEE), QGIS, and WebGIS—to conduct a rapid assessment of inundation impacts and associated economic losses over the past 13 years (2007-2020). The analysis found that approximately 30,790 hectares were inundated, with croplands experiencing the most severe damage. The estimated total economic losses amounted to USD 177,215,000, affecting croplands, forests, wetlands, built-up areas, and mangroves. The results were validated against data from Indonesia's National Disaster Management Authority (BNPB), ensuring high accuracy. This study introduces two key novelties: the first use of SatGPT in an Indonesian context and the innovative integration of SatGPT, GEE, QGIS, and WebGIS for a rapid assessment of inundation impacts and economic losses. These findings highlight the potential of geospatial platforms for quick disaster impact assessment and provide valuable insights for improving disaster risk management strategies in Indonesia.