Abstract
Timely and accurate information about the extent of floodwater is critical for emergency planning and disaster management efforts. Despite the advances in computational resources and in the field of remote sensing, there is a clear gap that restricts the disaster community from leveraging the technological resources in real time, which impedes on-ground response efforts. To bridge this gap, this paper makes two contributions. First, the paper presents a new web application, the Global Flood Mapper (GFM) that allows the user to generate flood maps quickly and without getting into technical intricacies. To derive the flood extent from Sentinel-1 satellite data, the pre-flood collection is considered as base and anomaly cells in the during-flood image(s) are identified using Z-Score values. Second, it advances an existing flood mapping method to (a) Map the peak of the floods by combining ascending and descending scenes when necessary, and (b) Check for false positives in hilly terrains by adding slope and elevation mask parameters. By comparing our results with Sentinel-2 MSI derived flood maps and field photographs, we show that the GFM can generate flood maps with precision. The GFM can be used to map and download the extent of multiple flood events of an area as vector data (.kml format), which can be a critical input for flood modeling and risk and impact assessments. The GFM shall enable first responders and practitioners across the globe to overcome technical barriers and lack of computational resources to map the extent of inundation during and after floods.
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Data availability
The link to the Global Flood Mapper can be found at https://github.com/PratyushTripathy/global_flood_mapper.
Code availability
The source code of the Global Flood Mapper can be found at https://github.com/PratyushTripathy/global_flood_mapper.
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Acknowledgments
The authors express gratitude to the European Space Agency for making the Sentinel data freely available. The authors would also like to thank Google for providing access to the Google Earth Engine (GEE).
Funding
This work was completed with support from the PEAK Urban program, funded by UK Research and Innovation’s Global Challenge Research Fund, Grant Ref: ES/P011055/1.
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Conceptualization, formal analysis, investigation, resources, data curation, writing—original draft preparation, writing—review and editing, visualization and project administration were contributed by PT and TM; methodology and application development were contributed by PT.; supervision was contributed by TM.
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Appendix 1
Appendix 1
See Figures 10, 11, 12, 13 and 14.
Global coverage of Sentinel-1 SAR ascending and descending directions for a SW mode during 01 Jan 2015 to 01 August 2020 and b IW mode during 01 July 2020 to 01 August 2020 as seen on Google Earth Engine code editor
Flood map of Thua Thien—Hue, Viet Nam generated using the GFM. Parameter used: pre-flood date: 01 Aug 2020 + 60 days, during-flood date: 13 Oct 2020 + 1 day
Flood map of Assam, India generated using the GFM. Parameter used: pre-flood date: 01 May 2019 + 45 days, during-flood date: 04 July 2019 + 10 days
Flood map of Bahamas generated using the GFM. Parameter used: pre-flood date: 01 Jun 2019 + 60 days, during-flood date: 03 Sep 2019 + 5 days
Flood map of Sofala, Mozambique generated using the GFM. Parameter used: pre-flood date: 01 Jan 2019 + 60 days, during-flood date: 19 Mar 2019 + 1 day
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Tripathy, P., Malladi, T. Global Flood Mapper: a novel Google Earth Engine application for rapid flood mapping using Sentinel-1 SAR. Nat Hazards 114, 1341–1363 (2022). https://doi.org/10.1007/s11069-022-05428-2
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DOI: https://doi.org/10.1007/s11069-022-05428-2