Spectral and spatial methods for the classification of urban remote sensing data

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

Note that this scheme can be applied for both classification and unmixing, i.e., the input of the fusion function can be either the class of a pixel in the case of classification,

Advanced Multi-Sensor Optical Remote Sensing for Urban Land Use and Land Cover Classification: Outcome of the 2018 IEEE GRSS Data Fusion Contest... Outcome

Six classes appear in both study areas (Transportation areas, Tile roof, Metallic roof, Other roof, Vegetation and Shadow), while Water class was only

Taking advantage of the availability of other data sets of relevance to the parameter under concern, though different, a method is proposed for the synthesis of the initial

The ARSIS method was designed to synthetize in a set of images with different spatial and spectral resolutions, multispectral images with the best resolution

For these missions to come, the ratio of spatial resolution between the multispectral set of images and the panchromatic image is 2 or 4, like in the case of SPOT P and XS

We remind that an MST is a tree (a connected graph without cycle, i.e., there exists a unique path between any pair of nodes) of minimum weight. It is unique if all weights