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Sökning: WFRF:(Vetra Carvalho Sanita)

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1.
  • Mason, David C., et al. (författare)
  • Improving Urban Flood Mapping by Merging Synthetic Aperture Radar-Derived Flood Footprints with Flood Hazard Maps
  • 2021
  • Ingår i: Water. - : MDPI. - 2073-4441. ; 13:11
  • Tidskriftsartikel (refereegranskat)abstract
    • Remotely sensed flood extents obtained in near real-time can be used for emergency flood incident management and as observations for assimilation into flood forecasting models. High-resolution synthetic aperture radar (SAR) sensors have the potential to detect flood extents in urban areas through clouds during both day- and night-time. This paper considers a method for detecting flooding in urban areas by merging near real-time SAR flood extents with model-derived flood hazard maps. This allows a two-way symbiosis, whereby currently available SAR urban flood extent improves future model flood predictions, while flood hazard maps obtained after the SAR overpasses improve the SAR estimate of urban flood extents. The method estimates urban flooding using SAR backscatter only in rural areas adjacent to urban ones. It was compared to an existing method using SAR returns in both rural and urban areas. The method using SAR solely in rural areas gave an average flood detection accuracy of 94% and a false positive rate of 9% in the urban areas and was more accurate than the existing method.
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2.
  • Mason, David C., et al. (författare)
  • Robust algorithm for detecting floodwater in urban areas using synthetic aperture radar images
  • 2018
  • Ingår i: Journal of Applied Remote Sensing. - : SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS. - 1931-3195. ; 12:4
  • Tidskriftsartikel (refereegranskat)abstract
    • Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. High-resolution synthetic aperture radar (SAR) sensors are able to detect flood extents in urban areas during both day- and night-time. If obtained in near real time, these flood extents can be used for emergency flood relief management or as observations for assimilation into flood forecasting models. A method for detecting flooding in urban areas using near real-time SAR data is developed and extensively tested under a variety of scenarios involving different flood events and different images. The method uses an SAR simulator in conjunction with LiDAR data of the urban area to predict areas of radar shadow and layover in the image caused by buildings and taller vegetation. Of the urban water pixels visible to the SAR, the flood detection accuracy averaged over the test examples is 83%, with a false alarm rate of 9%. The results indicate that flooding can be detected in the urban area to reasonable accuracy but that this accuracy is limited partly by the SAR's poor visibility of the urban ground surface due to shadow and layover. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.
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