Near Real-Time Flood Detection in Urban and Rural Areas Using High-Resolution Synthetic Aperture Radar Images

David C. Mason*, Ian J. Davenport, Jeffrey C. Neal, Guy J. -P. Schumann, Paul D. Bates

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

173 Citations (Scopus)


A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high-resolution synthetic aperture radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high-resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18%, respectively.

Original languageEnglish
Pages (from-to)3041-3052
Number of pages12
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number8
Publication statusPublished - Aug 2012


  • hydrology
  • image processing
  • Algorithms
  • simulation


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