NDLI: Stochastic Approach in Wet Snow Detection Using Multitemporal SAR Data

Content Provider	IEEE Xplore Digital Library
Author	Besic, N. Vasile, G. Dedieu, J.-P. Chanussot, J. Stankovic, S.
Copyright Year	2004
Abstract	This letter introduces an alternative strategy for wet snow detection using multitemporal synthetic aperture radar (SAR) data. The proposed change detection method is primarily based on the comparison between two X-band SAR images acquired during the accumulation (winter) and melting (spring) seasons, in the French Alps. The new decision criterion relies on the local intensity statistics of the SAR images by considering the backscattering ratio as a stochastic process: the probability that “the intensity ratio fits into the predetermined range of values” is larger than a defined confidence level. Both the conducted snow backscattering simulations and the state-of-the-art measurements indicate more complex relation between the backscattering properties of the two snow types, with respect to the conventional assumption of the augmented electromagnetic absorption associated to the wet snow. Therefore, rather than adopting the standard hypothesis, we analyze the wet/dry snow backscattering ratio as a function of the local incidence angle (LIA). After employing the multilayer snow backscattering simulator, calibrated with scatterometer measurements in C-band, we modify, to some extent, the range of ratio values indicating the presence of the wet snow, by including positive ratio values for lower LIA. By simultaneously accounting for the speckle noise, the proposed stochastic approach derives the refined wet snow probability map. The performance analyses are carried out both through the comparison with the ground air temperature map and by comparing two copolarized channels processed separately.
Sponsorship	IEEE Geoscience and Remote Sensing Society
Starting Page	244
Ending Page	248
Page Count	5
File Size	786517
File Format	PDF
ISSN	1545598X
Volume Number	12
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Snow Backscatter Synthetic aperture radar Remote sensing Speckle Ice Land surface temperature wet snow Backscattering simulation change detection stochastic approach
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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