Improving Urban Flood Mapping by Merging Synthetic Aperture Radar-Derived Flood Footprints with Flood Hazard Maps
| Autor: | Sarah L. Dance, John Bevington, Beatriz Revilla-Romero, Sanita Vetra-Carvalho, Richard Smith, Hannah Cloke, David C. Mason |
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| Rok vydání: | 2021 |
| Předmět: |
Synthetic aperture radar
010504 meteorology & atmospheric sciences Backscatter Geography Planning and Development Flood forecasting 0211 other engineering and technologies hydrology Oceanografi hydrologi och vattenresurser 02 engineering and technology Aquatic Science 01 natural sciences Biochemistry Remote Sensing Oceanography Hydrology and Water Resources Hydrology (agriculture) parasitic diseases Incident management (ITSM) Fjärranalysteknik TD201-500 021101 geological & geomatics engineering 0105 earth and related environmental sciences Water Science and Technology Remote sensing Water supply for domestic and industrial purposes Flood myth fungi Flooding (psychology) food and beverages Hydraulic engineering humanities image processing population characteristics Environmental science Rural area TC1-978 synthetic aperture radar |
| Zdroj: | Water Volume 13 Issue 11 Water, Vol 13, Iss 1577, p 1577 (2021) |
| ISSN: | 2073-4441 |
| DOI: | 10.3390/w13111577 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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