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Snow cover monitoring using multitemporal ENVISAT/ASAR data


Valenti, L; Small, D; Meier, E (2008). Snow cover monitoring using multitemporal ENVISAT/ASAR data. In: 5th EARSeL Workshop: Remote Sensing of Land Ice and Snow, Berne, 11 February 2008 - 13 February 2008, 8pp.

Abstract

A method has been developed to apply multi-temporal Advanced Synthetic Aperture Radar (ENVISAT/ASAR, C-Band) images to snow cover monitoring and mapping in mountainous areas. A multi-temporal dataset that includes sequences of ascending and descending ASAR wide swath and beam mode IS2 scenes acquired over Switzerland was investigated. The images were geometrically corrected to remove relief distortions, producing geocoded terrain corrected (GTC) image products. Backscattering coefficients (Beta, Sigma and Gamma nought) are typically calculated using a nominal local incidence angle value using a simplified ellipsoid geometry. We apply a more rigorous approach that models the backscattering coefficients normalised for local illuminated area (projected into the look direction for γ° retrieval), producing radiometric terrain corrected (RTC) image products.
The snow cover was monitored by calculating the difference between the backscattering coefficients (γ°) of each ASAR image and the reference backscattering coefficient of a syn-thetic dry snow or snow free image. Similar to conventional fixed thresholding (e.g. 3 dB), a reference winter dry snow image was compared to each new ASAR image. Analysis of the resulting time series shows strong seasonal trends in backscatter behaviour, likely caused by variations of liquid water content in the snow cover. Meteorological data (MeteoSchweiz), NOAA images and snow cover maps from the Swiss Federal Institute for Snow and Avalanche Research supported interpretation and validation of the results.

Abstract

A method has been developed to apply multi-temporal Advanced Synthetic Aperture Radar (ENVISAT/ASAR, C-Band) images to snow cover monitoring and mapping in mountainous areas. A multi-temporal dataset that includes sequences of ascending and descending ASAR wide swath and beam mode IS2 scenes acquired over Switzerland was investigated. The images were geometrically corrected to remove relief distortions, producing geocoded terrain corrected (GTC) image products. Backscattering coefficients (Beta, Sigma and Gamma nought) are typically calculated using a nominal local incidence angle value using a simplified ellipsoid geometry. We apply a more rigorous approach that models the backscattering coefficients normalised for local illuminated area (projected into the look direction for γ° retrieval), producing radiometric terrain corrected (RTC) image products.
The snow cover was monitored by calculating the difference between the backscattering coefficients (γ°) of each ASAR image and the reference backscattering coefficient of a syn-thetic dry snow or snow free image. Similar to conventional fixed thresholding (e.g. 3 dB), a reference winter dry snow image was compared to each new ASAR image. Analysis of the resulting time series shows strong seasonal trends in backscatter behaviour, likely caused by variations of liquid water content in the snow cover. Meteorological data (MeteoSchweiz), NOAA images and snow cover maps from the Swiss Federal Institute for Snow and Avalanche Research supported interpretation and validation of the results.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Event End Date:13 February 2008
Deposited On:02 Dec 2008 14:13
Last Modified:03 Apr 2017 23:36
Publisher:European Association of Remote Sensing Laboratories
Additional Information:
Official URL:http://saturn.unibe.ch/rsbern/people/earsel/papers/Valenti_Paper.pdf
Related URLs:http://www.geography.unibe.ch/lenya/giub/live/research/remotesensing/Forschung/earselworkshop_en.html
http://saturn.unibe.ch/rsbern/people/earsel/presentations/Valenti_Presentation.pdf

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