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Surveys in Geophysics

, Volume 32, Issue 3, pp 255–269 | Cite as

Timely Low Resolution SAR Imagery To Support Floodplain Modelling: a Case Study Review

  • Giuliano Di Baldassarre
  • Guy Schumann
  • Luigia Brandimarte
  • Paul Bates
Article

Abstract

It is widely recognised that remote sensing can support flood monitoring, modelling and management. In particular, satellites carrying Synthetic Aperture Radar (SAR) sensors are valuable as radar wavelengths can penetrate cloud cover and are insensitive to daylight. However, given the strong inverse relationship between spatial resolution and revisit time, monitoring floods from space in near real time is currently only possible through low resolution (about 100 m pixel size) SAR imagery. For instance, ENVISAT-ASAR (Advanced Synthetic Aperture Radar) in WSM (wide swath mode) revisit times are of the order of 3 days and the data can be obtained within 24 h at no (or low) cost. Hence, this type of space-borne data can be used for monitoring major floods on medium-to-large rivers. This paper aims to discuss the potential for, and uncertainties of, coarse resolution SAR imagery to monitor floods and support hydraulic modelling. The paper first describes the potential of globally and freely available space-borne data to support flood inundation modelling in near real time. Then, the uncertainty of SAR-derived flood extent maps is discussed and the need to move from deterministic binary maps (wet/dry) of flood extent to uncertain flood inundation maps is highlighted.

Keywords

Hydrology Remote sensing Flood monitoring Inundation modelling Floodplain mapping 

Notes

Acknowledgments

The authors are extremely grateful to the European Space Agency (ESA) for allowing access to the flood images used in this study (Category 1 Project ID: 5739), the Environment Agency of England and Wales for the LiDAR data and the River Po Authority. Guy Schumann is funded by a Great Western Research fellowship.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Giuliano Di Baldassarre
    • 1
  • Guy Schumann
    • 2
  • Luigia Brandimarte
    • 3
  • Paul Bates
    • 2
  1. 1.Department of Hydroinformatics and Knowledge ManagementUNESCO-IHEDelftThe Netherlands
  2. 2.School of Geographical SciencesUniversity of BristolBristolUK
  3. 3.Department of Water EngineeringUNESCO-IHEDelftThe Netherlands

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