Interpretation of a RADARSAT-2 fully polarimetric time-series for snow cover studies in an Alpine context - first results

• Published in: Canadian journal of remote sensing Vol. 38; no. 3; pp. 336 - 351
• Main Authors: Dedieu, J.P., De Farias, G. Beninca, Castaings, T., Allain-Bailhache, S., Pottier, E., Durand, Y., Bernier, M.
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 01.06.2012; Canadian Aeronautics and Space Institute; Canadian Aeronautics
• Subjects: Earth Sciences; Geomorphology; Remote sensing; Sciences of the Universe; Snow; Studies; Time series; Topography; Alps
• ISSN: 0703-8992; 1712-7971
• DOI: 10.5589/m12-027

The aim of the SOAR #1341 project is to perform temporal analyses of changes in RADARSAT-2 full-polarimetry parameters on snow cover in a mountainous area. The objective of the present study was to determine whether there is a correlation between changes in radar statistics and changes in physical snow parameters during winter and spring. This paper focuses on the preprocessing of the images and presents the methodological steps and first results obtained in full polarimetry mode. Six RADARSAT-2 quad-pol images were acquired between January 2009 and January 2010, five in different snow conditions and one snow-free image in summer used as a reference. The fine acquisition mode was selected with a medium incidence angle (39°). A combination of LANDSAT-7 and SPOT optical images and field measurements was used for the validation step. First, RADARSAT-2 images had to be pre-processed due to the influence of high mountain topography on the polarimetric signal: the planned incidence angle was computed using a fine digital elevation model (DEM). Next, the DEM and optical dataset were reprojected onto the slant range mode of RADARSAT-2, the configuration required to preserve the phase signal and polarimetric statistics. Polarimetric analysis was performed using the PolSARpro software from ESA/IETR. The coherency matrices were calculated for each RADARSAT-2 image. Polarimetric descriptors based on the eigenvector-eigenvalue decomposition theorem of this coherency matrix were obtained. The behavior of the Single Eigenvalue Relative Difference, a polarimetric parameter that depends on scattering mechanisms, was analyzed. The polarimetric analysis showed an increase in the multiple scattering mechanism with a dry snow cover compared with the snow-free image. With a wet snow cover, there was an increase in contribution of the single scattering compared with the snow-free image. Our results showed that it was possible to identify temporal changes in dry, wet, or no snow characteristics throughout the winter season by analyzing primary polarimetric decomposition parameters and by comparing them with measurements made at 10 field sites.