<![CDATA[Flooding in urban and semi-urban areas of Indonesia, particularly in Surabaya and Gresik, has become an ongoing challenge, exacerbated by rapid urbanization and climate change. This study explores the application of Sentinel-1 Dual-Polarization Water Index (SDWI) and Normalized Difference Water Index (NDWI) derived from Sentinel-2 and Landsat 9 imagery to map flood extents during three major flood events in 2022, 2023 and 2024. The analysis is conducted on a cloud-based Google Earth Engine (GEE) platform to enable near real-time flood monitoring with significantly faster processing time. The results indicate that NDWI is useful in detecting large-scale water bodies and coastal flooding, whereas SDWI performs better in urban and vegetated environments, capturing inundation in built-up areas that NDWI may overlook. The comparison of satellite-derived flood maps with ground-truth data from news reports confirms that both indices can provide indicative flood assessments where SDWI performs slightly better than NDWI. However, discrepancies between remote sensing data and ground observations suggest the need for a hybrid approach combining satellite data with ground-based observations to enhance flood mapping accuracy. The integration of these indices on cloud-based platforms like Google Earth Engine (GEE) offers a scalable solution for rapid flood mapping, supporting emergency response and disaster risk reduction efforts in Indonesia, particularly in flood-prone regions.]]>
