Operational Surface Water Detection and Monitoring Using Radarsat 2

Remote Sensing

Brian Brisco¹  Alain Pietroniro²  Doug Stiff³  Sandra Bolanos⁴ 

[1] Canada Centre for Mapping and Earth Observation, Natural Resources Canada, 560 Rochester St, Ottawa, ON K1S 5K2, Canada;National Hydrological Services, Environment and Climate Change Canada, 11 Innovation Blvd., Saskatoon, SK S7N 3H5, Canada;National Hydrological Services, Environment and Climate Change Canada, 373 Sussex Dr., Ottawa, ON K1A 0H3, Canada;Science and Risk Assessment Directorate, Environment and Climate Change Canada, 351 Boulevard St-Joseph, Gatineau, QC K1A 0H3, Canada;

关键词: hydrological modeling;    water mapping;    wetlands;    flooding;    SAR;    Radarsat-2;    RCM;    potholes;   

DOI  :  10.3390/rs8040285

来源: DOAJ

【 摘 要 】

Traditional on-site methods for mapping and monitoring surface water extent are prohibitively expensive at a national scale within Canada. Despite successful cost-sharing programs between the provinces and the federal government, an extensive number of water features within the country remain unmonitored. Particularly difficult to monitor are the potholes in the Canadian Prairie region, most of which are ephemeral in nature and represent a discontinuous flow that influences water pathways, runoff response, flooding and local weather. Radarsat-2 and the Radarsat Constellation Mission (RCM) offer unique capabilities to map the extent of water bodies at a national scale, including unmonitored sites, and leverage the current infrastructure of the Meteorological Service of Canada to monitor water information in remote regions. An analysis of the technical requirements of the Radarsat-2 beam mode, polarization and resolution is presented. A threshold-based procedure to map locations of non-vegetated water bodies after the ice break-up is used and complemented with a texture-based indicator to capture the most homogeneous water areas and automatically delineate their extents. Some strategies to cope with the radiometric artifacts of noise inherent to Synthetic Aperture Radar (SAR) images are also discussed. Our results show that Radarsat-2 Fine mode can capture 88% of the total water area in a fully automated way. This will greatly improve current operational procedures for surface water monitoring information and impact a number of applications including weather forecasting, hydrological modeling, and drought/flood predictions.

【 授权许可】

Unknown