Abstract
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.
Highlights
The National Hydrological Service (NHS) of Environment and Climate Change Canada is the national agency responsible for the collection, interpretation and dissemination of standardized data on water resources and information in Canada
Statistical information is combined with digital elevation models [8,14,16], where pixels likely to contain water are first determined based on topographic data and the probability of water is based on histograms of water vs. land pixels in the image, but this requires a coarse water mask to determine the statistics of water pixels
Radarsat-2 derived polygons were evaluated against water polygons derived from cloud-free, temporally coincident high-resolution optical imagery over three areas of interest (AOIs) in Alberta, temporally coincident high-resolution optical imagery over three areas of interest (AOIs) in Alberta, selected based on the availability of the imagery and landscape characteristics
Summary
The National Hydrological Service (NHS) of Environment and Climate Change Canada is the national agency responsible for the collection, interpretation and dissemination of standardized data on water resources and information in Canada. Statistical information is combined with digital elevation models [8,14,16], where pixels likely to contain water are first determined based on topographic data and the probability of water is based on histograms of water vs land pixels in the image, but this requires a coarse water mask to determine the statistics of water pixels This dependence on a pre-determined water mask and high-resolution digital elevation models makes these methods unusable for mapping small ephemeral water bodies. Active contour algorithms, called snakes [23], have been applied with some success for water mapping from radar images [17,22] These algorithms, rely on ancillary data to determine candidate pixels for water as well as on morphological operators, which results in longer processing times. The fragmentation of SAR-derived water polygons (in blue)(in make them smaller band Blue ==green band).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
