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Earth observation satellites will provide in the next years time series with enough revisit time allowing a better surface monitoring. In this work, we propose a cloud screening and a cloud shadow detection method based on detecting abrupt changes in the temporal domain. It is considered that the time series follows smooth variations and abrupt changes in certain spectral features will be mainly due...
Nowadays, the increasing quantity of applications using images from Earth Observation satellites makes demanding better spatial, spectral and temporal resolutions. Nevertheless, due to the technical constraint of a trade off between spatial and spectral resolutions, and between spatial resolution and coverage, high spatial resolution is related with low spectral and temporal resolutions and vice versa...
This letter presents advanced classification methods for very high resolution images. Efficient multisource information, both spectral and spatial, is exploited through the use of composite kernels in support vector machines. Weighted summations of kernels accounting for separate sources of spectral and spatial information are analyzed and compared to classical approaches such as pure spectral classification...
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