Abstract
Processing of data recorded by the MODIS sensors on board the Terra and Aqua satellites has provided AOT maps that in some cases show low correlations with ground-based data recorded by the AERONET. Application of SVR techniques to MODIS data is a promising, though yet poorly explored, method of enhancing the correlations between satellite data and ground measurements. The article explains how satellite data recorded over three years on central Europe are correlated in space and time with ground based data and then shows results of the application of the SVR technique which somewhat improves previously computed correlations. Hints about future work in testing different SVR variants and methodologies are inferred from the analysis of the results thus far obtained.
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AERONET - AErosol Robotic Network, http://aeronet.gsfc.nasa.gov/
LIBSVM: A Library for Support Vector Machines, http://www.csie.ntu.edu.tw/~cjlin/libsvm/
MEEO: Meteorological Environmental Earth Observation, http://www.meeo.it/
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Nguyen, T.N.T., Mantovani, S., Campalani, P., Cavicchi, M., Bottoni, M. (2010). Aerosol Optical Thickness Retrieval from Satellite Observation Using Support Vector Regression. In: Bloch, I., Cesar, R.M. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2010. Lecture Notes in Computer Science, vol 6419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16687-7_65
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DOI: https://doi.org/10.1007/978-3-642-16687-7_65
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