Title: Snow Cover Monitoring Techniques with GB-SAR
Authors: MARTÍNEZ-VÁZQUEZ Alberto
Editors: FORTUNY GUASCH Joaquim
Publisher: European Commission - Joint Research Centre
Publication Year: 2008
JRC N°: JRC47983
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC47983
Type: PhD Theses
Abstract: Ground-based synthetic aperture radars (GB-SAR) are instruments that, although relatively young, are operationally used to monitor landslides with sub-millimetre accuracy. There are however other application fields that deserve some attention. Monitoring of the snow cover and, in particular, of those processes associated with the snow avalanches are a clear example of this. To date, monitoring of the snow cover has been traditionally carried out at local scale either with invasive sensors or with continuous wave (CW) radars, while at wider scales air- or satellite-borne sensors have been employed. The work presented in this PhD thesis is a first attempt to study the potential use of GB-SAR sensors to monitor the snow cover. Three techniques for monitoring snow cover with GB-SAR are presented through Chapters 5, 6 and 7: snow height retrieval, snow avalanche volume retrieval and avalanche events detection and classification. Snow height is retrieved by using the differential interferometric phase of two consecutive SAR acquisitions under the assumption of single layer model and dry snow conditions. The volume displaced in a snow avalanche is computed by subtracting two digital terrain models (DTM) generated immediately before and after the avalanche event. DTMs are obtained with the topographic interferometric mode of the instrument: a spatial baseline separates two antennas that simultaneously receive the echoes of a third transmitting antenna. The third monitoring technique, avalanche detection and classification, is achieved identifying low-coherence anomalies in the coherence image between two successive SAR acquisitions. Snow avalanches present a low-coherence signature that can be identified by a morphological and statistical parameter model. A novel detection and classification scheme for snow avalanches is proposed. The Joint Research Centre¿s GB-SAR sensor, upgraded to allow continuous operation 24 hours a day 7 days a week, also as part of the work of this thesis (Chapter 3), was used to develop and assess the before mentioned techniques. Measurements were carried out during six winters, providing more than 120000 SAR images at a rate of one image every 12 minutes approximately. Two test sites were studied, each with different characteristics in order to assess under real conditions the operational use of the monitoring techniques. Results show that snow height retrieval is achievable but remains, for the moment, an on-going research topic due to strong constraints limiting its use. A feasibility study is presented showing the accuracy limitations of GB-SAR to compute the snow volume involved in an avalanche. Finally, the most promising technique is snow avalanche detection and classification, which is demonstrated to be feasible and robust from an operational point of view and practical from an end user perspective.
JRC Institute:Institute for the Protection and Security of the Citizen

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