Author: Myles Burt
Burt, Myles, 2024 Skimming the Surface: Mapping Flood Extent in the Burdekin Basin with RADAR and GIS, Flinders University, College of Science and Engineering
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This study explores the effective utilization of Synthetic Aperture Radar (SAR) data, specifically from Sentinel-1, for flood identification. The research focuses on how the SAR data collection, processing, and analysis can be performed to provide valuable insights on flood scenarios where optical imagery may fall short, and aid in improved preparedness for future floods in a changing climate. Whilst using SAR for flood identification has a proven and demonstrated method found in academic literature, there is limited academic literature focusing on the validation of SAR methods compared to optical methods for flood identification in the field of remote sensing. SAR technology was applied to identify surface water and classify flood areas within the Lower Burdekin Basin during the severe weather event 'Tropical Low 13U' in 2019. This process involved employing the Sentinel Application Platform (SNAP), an open-source toolbox from the European Space Agency, in conjunction with ESRI's ArcGIS Pro. Flood identification using SAR was established through a binary classification method and validated with the Normalised Difference Water Index (NDWI) processed optical imagery. As a result, SAR successfully identified 5.9% of the land as flooded, in comparison to NDWI's 6.5%, resulting in a minimal 0.6% variation in flood results between SAR binary classification and optical NDWI methods. These findings demonstrate SAR's efficacy in flood identification. While optical imagery, especially when processed with the NDWI method, excels in pinpointing flooded areas, SAR showcases remarkable consistency in capturing and analysing flood events. A distinctive advantage of SAR is its ability to penetrate cloud cover, ensuring uninterrupted data capture in adverse weather conditions. With open-access resources like Sentinel-1 and SNAP from the European Space Agency (ESA), SAR data emerges as a crucial component in the development of cost-effective and efficient flood mapping solutions.
Keywords: Geospatial, GIS, Remote Sensing, Radar, SAR, Flood, Burdekin Basin, detection, identify, Queensland,
Subject: Engineering thesis
Thesis type: Masters
Completed: 2024
School: College of Science and Engineering
Supervisor: David Bruce