Abstract
This contribution describes the system developed and implemented for the detection of snow based on the fusion of optical and Synthetic Aperture Radar (SAR) remote sensing modalities. The work is focused on the performance comparison of different fusion operators for the implementation of the fusion stage. In case of the optical signal the so-called Normalized Difference Snow Index (NDSI) is used, whereas in SAR, the binary presence of wet and dry snow are used. We take into account soft data fusion, a framework where several operators are included. The comparison is undertaken on a set of satellite images by computing the standard Receiver Operating Curves (ROC) and the corresponding Area Under the Curves (AUC).
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Soria-Frisch, A., Repucci, A., Moreno, L., Caparrini, M. (2010). Performance Comparison of Fusion Operators in Bimodal Remote Sensing Snow Detection. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2010. Communications in Computer and Information Science, vol 81. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14058-7_22
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DOI: https://doi.org/10.1007/978-3-642-14058-7_22
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