Operational Surface Water Detection and Monitoring Using Radarsat 2

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.

[1]  Robert Woodruff,et al.  Detecting seasonal flooding cycles in marshes of the Yucatan Peninsula with SIR-C polarimetric radar imagery , 1997 .

[2]  H. Winsemius,et al.  Automated global water mapping based on wide-swath orbital synthetic-aperture radar , 2012 .

[3]  David Gillieson,et al.  Relationship of local incidence angle with satellite radar backscatter for different surface conditions , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[4]  E. Nezry,et al.  Adaptive speckle filters and scene heterogeneity , 1990 .

[5]  Brian Brisco,et al.  Water resource applications with RADARSAT-2 – a preview , 2008, Int. J. Digit. Earth.

[6]  T. Guneriussen,et al.  Mapping surface-water with Radarsat at arbitrary incidence angles , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[7]  T. J. Pultz,et al.  Case studies demonstrating the hydrological applications of C-band multipolarized and polarimetric SAR , 2004 .

[8]  Rob J. Dekker,et al.  Texture analysis and classification of ERS SAR images for map updating of urban areas in The Netherlands , 2003, IEEE Trans. Geosci. Remote. Sens..

[9]  David Gillieson,et al.  Use of ENVISAT ASAR Global Monitoring Mode to complement optical data in the mapping of rapid broad-scale flooding in Pakistan , 2011 .

[10]  Thomas Blaschke,et al.  Image Segmentation Methods for Object-based Analysis and Classification , 2004 .

[11]  Masanobu Shimada,et al.  Mapping Regional Inundation with Spaceborne L-Band SAR , 2015, Remote. Sens..

[12]  Brian Brisco,et al.  RADARSAT-2 Beam Mode Selection for Surface Water and Flooded Vegetation Mapping , 2014 .

[13]  M. Buchroithner,et al.  Strategies for the Automatic Extraction of Water Bodies from TerraSAR-X / TanDEM-X data , 2010 .

[14]  Yeong-Sun Song,et al.  Efficient water area classification using radarsat-1 SAR imagery in a high relief mountainous environment , 2007 .

[15]  Alberta.,et al.  A review of indicators of wetland health and function in Alberta's prairie, aspen parkland and boreal dry mixedwood regions / , 2006 .

[16]  Ridha Touzi,et al.  Wetland Characterization using Polarimetric RADARSAT-2 Capability , 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

[17]  Brian Brisco,et al.  A semi-automated tool for surface water mapping with RADARSAT-1 , 2009 .

[18]  S. Quegan,et al.  Understanding Synthetic Aperture Radar Images , 1998 .

[19]  Ali El-Zaart,et al.  Automatic Thresholding Techniques for SAR Images , 2013, CSE 2013.

[20]  E. Pottier,et al.  Polarimetric Radar Imaging: From Basics to Applications , 2009 .

[21]  Aline Pieterse,et al.  Using Remote Sensing to Map and Monitor Water Resources in Arid and Semiarid Regions , 2015 .

[22]  Thomas Blaschke,et al.  Object based image analysis for remote sensing , 2010 .

[23]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[24]  P. Manjusree,et al.  Optimization of threshold ranges for rapid flood inundation mapping by evaluating backscatter profiles of high incidence angle SAR images , 2012, International Journal of Disaster Risk Science.

[25]  Birgit Wessel,et al.  Surface Water Body Detection in High-Resolution TerraSAR-X Data using Active Contour Models , 2010 .

[26]  T. Toutin,et al.  A New Hybrid Modeling for Geometric Processing of Radarsat-2 data without User's GCP , 2011 .

[27]  Shusen Wang,et al.  An automatic method for mapping inland surface waterbodies with Radarsat-2 imagery , 2015 .

[28]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[29]  K. Moffett,et al.  Remote Sens , 2015 .

[30]  Sandro Martinis,et al.  Towards operational near real-time flood detection using a split-based automatic thresholding procedure on high resolution TerraSAR-X data , 2009 .

[31]  Marco L. Carrera,et al.  The Canadian Land Data Assimilation System (CaLDAS): Description and Synthetic Evaluation Study , 2015 .

[32]  Alain Pietroniro,et al.  Towards operational monitoring of a northern wetland using geomatics-based techniques , 2005 .

[33]  John W. Pomeroy,et al.  Storage dynamics simulations in prairie wetland hydrology models: evaluation and parameterization , 2013 .

[34]  R. Heremans,et al.  Automatic detection of flooded areas on ENVISAT/ASAR images using an object-oriented classification technique and an active contour algorithm , 2003, International Conference on Recent Advances in Space Technologies, 2003. RAST '03. Proceedings of.