Fully polarimetric airborne SAR and ERS SAR observations of snow: implications for selection of ENVISAT ASAR modes

Abstract

Snow cover has a substantial impact on processes involved in the interaction between atmosphere and surface, and the knowledge of snow parameters is important in both climatology and weather forecasting. With the upcoming launch of Advanced Synthetic Aperture Radar (ASAR) instruments on Envisat, enhanced snow-mapping capabilities are foreseen. In this paper fully polarimetric C-and L-band airborne SAR data, ERS SAR and auxiliary data from various snow conditions in mountainous areas are analysed in order to determine the optimum ASAR modes for snow monitoring. The data used in this study are from the Norwegian part of the snow and ice experiment within the European Multi-sensor Airborne Campaign (EMAC'95) acquired in the Kongsfjellet area, located in Norway, 66 ‡ N, 14 ‡ E. Fully polarimetric C-and L-band SAR data from ElectroMagnetic Institute SAR (EMISAR), an airborne instrument operated by the Danish Center for Remote Sensing (DCR), were acquired in March, May, and July 1995. In addition, several ERS SAR, airborne photos, field and auxiliary data were acquired.A larger separation between wet snow and bare ground in EMISAR C-VV polarisation data was found at high incidence angle (55 ‡) compared to lower incidence angle (45 ‡). Cross-polarized observations from bare ground, dry and wet snow in the incidence angle range 35 ‡ to 65 ‡ are below the specified Envisat ASAR noise floor of -20-22 dB. The backscattering angular dependency for wet snow and bare ground derived from EMISAR C-VV and ERS SAR data corresponds well, and agrees to some extent with volume and surface scattering model results. The C-band is more sensitive to variation in snow properties than the L-band.

Towards automated ‘Ground truth’ snow measurements—a review of operational and new measurement methods for Sweden, Norway, and Finland

“…He concluded that SCA mapping had to be improved, particularly in forests, and that melting had to be included in a more sophisticated way in the model. Satelliteborne (SAR) measurements within the project Snowtools have been used to discriminate between wet and dry snow (Guneriussen, 1997;Guneriussen and Johnsen, 2003) but the measurements did not seem to have been implemented into the operational HBV model. According to Engeset et al (2003), the satellite-observed SCA was used qualitatively to detect when the models did not simulate the snow reservoir correctly but was not used directly in the HBV model.…”

Automatic mapping of snow cover depletion curves using optical remote sensing data under conditions of frequent cloud cover and temporary snow

“…The coarse spatial resolution restricts their use in snow cover mapping (Rango, 1996). Active microwave data with higher spatial resolution, such as Envisat Advanced Synthetic Aperture Radar (ASAR) and Radarsat and European Remote Sensing Satellite (ERS) can detect snow cover under cloud easily (Nagler and Rott, 1998;Koskinen et al, 1999;Guneriussen et al, 2001;Guneriussen and Johnsen, 2003;Storvold and Malnes, 2004). However, these SAR generally cannot detect dry snow and their temporal resolutions, ranging from 24 to 35 days, are too low, and thus cannot be used for the purpose of mapping detailed snow cover depletion curves.…”