Special Section on Progress in Snow Remote Sensing

Snow cover area identification by using a change detection method applied to COSMO-SkyMed images

[+] Author Affiliations
Simone Pettinato

National Research Council, Institute of Applied Physics “Carrara,” Sesto Fiorentino (FI), Via Madonna del Piano 10, Sesto Fiorentino (FI), I-50019 Italy

Emanuele Santi

National Research Council, Institute of Applied Physics “Carrara,” Sesto Fiorentino (FI), Via Madonna del Piano 10, Sesto Fiorentino (FI), I-50019 Italy

Simonetta Paloscia

National Research Council, Institute of Applied Physics “Carrara,” Sesto Fiorentino (FI), Via Madonna del Piano 10, Sesto Fiorentino (FI), I-50019 Italy

Bruno Aiazzi

National Research Council, Institute of Applied Physics “Carrara,” Sesto Fiorentino (FI), Via Madonna del Piano 10, Sesto Fiorentino (FI), I-50019 Italy

Stefano Baronti

National Research Council, Institute of Applied Physics “Carrara,” Sesto Fiorentino (FI), Via Madonna del Piano 10, Sesto Fiorentino (FI), I-50019 Italy

Andrea Garzelli

University of Siena, Department of Information Engineering and Mathematical Sciences, Via Roma 56, Siena, I-53100 Italy

J. Appl. Remote Sens. 8(1), 084684 (Aug 07, 2014). doi:10.1117/1.JRS.8.084684
History: Received December 9, 2013; Revised July 9, 2014; Accepted July 11, 2014
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Abstract.  The information theoretic snow detection algorithm, a method that employs a change detection approach derived by Shannon’s information theory based on the conditional probability of the local means between two images taken at different times, is applied to multitemporal COSMO-SkyMed® data. The ultimate purpose of the method is the identification of snow cover areas in the case of extensive surface changes between summer and winter seasons. Both Himage and Ping Pong data in Stripmap acquisition mode from the COSMO-SkyMed constellation are processed. Results are compared to the available ground snow information gathered at the meteorological station present in the area. Quantitative assessments are obtained for Himage by considering a Landsat image as ground-truth. Receiver operating characteristic curves are used to deliver numerical comparisons between ground-truth and classified image, which is then compared to the well-known log-ratio approach. The proposed information theoretical approach to change detection provides very promising results in the case of large snow covering on multitemporal single-look synthetic aperture radar images at very high spatial resolution, due to its intrinsic low sensibility to speckle noise.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Simone Pettinato ; Emanuele Santi ; Simonetta Paloscia ; Bruno Aiazzi ; Stefano Baronti, et al.
"Snow cover area identification by using a change detection method applied to COSMO-SkyMed images", J. Appl. Remote Sens. 8(1), 084684 (Aug 07, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.084684


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