A comparison of global flood models using Sentinel-1 and a change detection approach

Axel Risling, Sara Lindersson and Luigia Brandimarte ()
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Axel Risling: KTH Royal Institute of Technology
Sara Lindersson: Uppsala University
Luigia Brandimarte: KTH Royal Institute of Technology

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 12, No 28, 11133-11152

Abstract: Abstract Advances in numerical algorithms, improvement of computational power and progress in remote sensing have led to the development of global flood models (GFMs), which promise to be a useful tool for large-scale flood risk management. However, performance and reliability of GFMs, especially in data-scarce regions, is still uncertain, as they are difficult to validate. Here we aim at contributing to develop alternative, more flexible, and consistent methods for GFM validation by applying a change detection analysis on synthetic aperture radar (CD-SAR) imagery obtained from the Sentinel-1 imagery, on a cloud-based geospatial analysis platform. The study addresses two main objectives. First, to validate four widely adopted GFMs with flood maps generated through the proposed CD-SAR approach. This exercise was conducted for eight different large river basins on four continents, to account for a diverse range of hydro-climatic environments. Second, to compare CD-SAR-derived flood maps with those obtained from alternative remote sensing sources. These comparative results offer valuable insights into the reliability of CD-SAR data as a validation tool, more specifically how it stacks up against flood maps generated by other remote sensing techniques.

Keywords: Change detection; SAR; Sentinel 1; Global flood models; Global flood databases (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11069-024-06629-7

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