Land cover mapping with higher order graph-based co-occurrence model

Deep learning has become a standard processing procedure in land cover mapping for remote sensing images. Instead of relying on hand-crafted features, deep learning algorithms, such as Convolutional Neural Networks (CNN) can automatically generate effective feature representations, in order to recognize objects with complex image patterns. However, the rich spatial information still remains unexploited, since most of the deep learning algorithms only focus on small image patches that overlook the contextual information at larger scales.

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Recommended citation: Wenzhi Zhao, et al. (2019). “Land cover mapping with higher order graph-based co-occurrence model” remote sensing. 11(10).