Estimation of snow-pack characteristics by means of polarimetric SAR data

A. Reppucci; X. Banque; Yu Zhan; Alberto Alonso; C. López-Martinez

doi:10.1117/12.974598

19 October 2012 Estimation of snow pack characteristics by means of polarimetric SAR data

A. Reppucci, X. Banque, Yu Zhan, Alberto Alonso, C. López-Martinez

Proceedings Volume 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV; 85310Z (2012) https://doi.org/10.1117/12.974598
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

Abstract

Characterization of the snow-pack is fundamental for several applications in hydrology, such as modelling and forecasting of snow melt runoff, water resource management and risk analysis. Thanks to its night/day capabilities and weather conditions independence, Synthetic Aperture Radar (SAR) represents a valuable tool for snow monitoring, especially in mountain areas often covered by clouds. The goal of the research project presented in this communication is to investigate the sensitivity of fully polarimetric Cband satellite SAR data to different conditions of the snow-pack. The work is based on the use of RADARSAT-2 C-band SAR data and collocated in-situ measurements acquired during two ground campaigns over an area located in the Catalan Pyrenees, that took place between February to October 2011. The main outcome of this study is the definition of two new polarimetric parameters sensitive to the snow presence, able to distinguish between dry-snow and non snow cover, allowing a qualitative remote sensing with C-band polarimetric space-borne SAR data. The importance of developing an application based on remote sensed data will be discussed. Results of the activity scheduled during the first year of the project will be highlighted. Observed deviations between SAR measurements and in situ measurement shall be analyzed and discussed.

Citation Download Citation

A. Reppucci, X. Banque, Yu Zhan, Alberto Alonso, and C. López-Martinez "Estimation of snow pack characteristics by means of polarimetric SAR data", Proc. SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 85310Z (19 October 2012); https://doi.org/10.1117/12.974598

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