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Evaluating Full Polarimetric C- and L-Band Data for Mapping Wetland Conditions in a Semi-Arid Environment in Central Spain

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4 Author(s)
Koch, M. ; Center for Remote Sensing, Boston Univ., Boston, MA, USA ; Schmid, T. ; Reyes, M. ; Gumuzzio, J.

Semi-arid wetlands are very dynamic ecosystems as the different characteristics (areal extension, water depth and salinity, seasonal flooding, vegetation and fauna) that define them vary greatly in the short and long term. The objective of this work is to evaluate the contributions of Radarsat-2 (C-band) and ALOS PALSAR (L-band) full polarimetric data in characterizing and mapping wetland conditions in a semi-arid environment in Central Spain. The National Park of Las Tablas de Daimiel was selected as a test site because of on-going work in this wetland area which has produced ample information on the distribution of vegetation communities, soil types and wetland conditions obtained from spaceborne, airborne and ground based optical multispectral and hyperspectral sensors. The goal is to understand and evaluate the complementary information derived from multipolarized synthetic aperture radar (SAR) data not otherwise obtainable from optical sensors. Results suggest that the multipolarized SAR data enables a better separation of the vegetation structure and fragmentation than with the optical data. Optical sensors have the general advantage of improved spectral characterization of vegetation and soil types but are less effective in characterizing vegetation/soil morphology and detecting moisture conditions under dense canopies. Therefore, a combination of the radar and optical data can be very useful in assessing the wetland degradation status, so that appropriate measures can be designed for a sustainable management of the wetland. However, before such an integrated approach can be implemented, a thorough understanding of the type and nature of information derived from multi-frequency and multipolarized SAR data is needed.

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Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of  (Volume:5 ,  Issue: 3 )