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TitleWetland characterization using Polarimetric RADARSAT-2 capability
 
AuthorTouzi, R
SourceIEEE International Geoscience and Remote Sensing Symposium proceedings 4241570, 2006 p. 1639-1642, https://doi.org/10.1109/IGARSS.2006.423
Year2006
Alt SeriesNatural Resources Canada, Contribution Series 20181258
PublisherIEEE
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
Subjectsgeophysics; Nature and Environment; remote sensing
ProgramCanada Centre for Remote Sensing Divsion
AbstractWetlands play a key role in regional and global environments and are critically linked to many major issues such as climate change, water quality, the hydrological and carbon cycles, and wildlife habitat and biodiversity. Mapping wetlands and monitoring their change in a systematic and repeatable manner for the Canadian Wetland Inventory (CWI), led by the Canadian Wildlife Service of Environment Canada (EC), are important in order to manage and protect significant wetland areas in Canada. The use of RADARSAT-1 Synthetic Aperture Radar (SAR) data has been shown to be important for wetland water extent characterization. However, the limited capability of RADARSAT-1's single-polarization C-band SAR in vegetation type discrimination makes the use of clear-sky-dependent visible near-infrared (VNIR) satellite data necessary for wetland mapping. In this paper, the unique Polarimetric capability of RADARSAT-2 is investigated for wetland classification. The roll invariant incoherent target decomposition, the TSVM-ICTD [11], is used for optimum characterization of wetland target scattering. It is shown that like RADARSAT-1 HH polarization, the magnitude of the complex symmetric scattering is not effective for vegetation type discrimination. The phase of the symmetric scattering type has to be used for a more complete characterization of wetland vegetation species. This new phase scattering parameter introduced in [11] has been shown to be very promising for wetland classification using Convair-580 Polarimetric SAR data.
GEOSCAN ID311612

 
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