Enhancing Flood Detection in Surabaya: A Comparative Study of VV and VH Polarizations with Sentinel-1 Data - Hafizhah Ashilah; Umboro Lasminto (Institut Teknologi Sepuluh Nopember (ITS), 2025)
Flood mapping is critical to strengthen urban resilience, particularly in Surabaya,where flooding is a major and recurring threat. Sentinel-1 satellite data offerssignificant advantages for flood model calibration due to its high-resolution imageryand frequent revisits. This study utilizes Google Earth Engine to process and analyseSentinel-1 data for mapping flood extents using two different polarizations: VV andVH. The research compares the capabilities of these polarizations in detecting floodareas. The results show that VV polarization consistently identifies a larger flood areacompared to VH polarization under similar processing conditions. However, theKappa coefficient was used to assess classification accuracy, with VV achieving aKappa of 0.8 and VH reaching a higher Kappa of 0.92, reflecting better classificationperformance. These findings suggest that while VV provides a broader flooddetection, VH offers more reliable flood mapping, highlighting the trade-offs betweensensitivity and accuracy in flood monitoring using Sentinel-1 satellite.