Laurence Hubert-Moy

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Independent Component Analysis (ICA) is a multivariate data analysis process largely sudied these last years in the signal processing community for blind source separation. This paper proposes to show the interest of ICA as a tool for unsupervised analysis of hyperspectral images. The commonly used Principal Component Analysis (PCA) is the mean square(More)
The spatial prediction of land cover at the field scale in winter appears useful for the issue of bare soils reduction in agricultural intensive regions. High variability of the factors that motivate the land cover changes between each winter involves integration of uncertainty in the modelling process. Fusion process with Dempster-Shafer Theory (DST)(More)
The study adresses the problem of spectral unmixing hyperspectral images, technique allowing the spectra and abundance of each pure material present in each pixel of a scene to be extracted. We first remark that the linear model commonly used in spectral unmixing is exactly the same as the model used in the Independant Component Analysis (ICA), a blind(More)
Denitrification is the main process removing nitrate in river drainage basins and buffer input from agricultural land and limits aquatic ecosystem pollution. However, the identification of denitrification hotspots (for example, riparian zones), their role in a landscape context and the evolution of their overall removal capacity at the drainage basin scale(More)
Change detection of landscape features is an important stake to understand relationships between human and natural phenomena. In the remote sensing community, most of change detection methods have been developed to detect abrupt changes from low or medium resolution imagery [1;2]. Such techniques, based on a pixel approach, are not well adapted to Very High(More)
Monitoring changes in the vegetation cover during the intercrop season is of special interest in intensive agricultural region, such as the Brittany region in France, to locate bare soils and control their influence to the environment. The presence of bare soils leads to detrimental environmental effects such as soil erosion or water quality degradation.(More)
A vectorial extension of the scalar anisotropic diffusion nonlinear filtering process applied on hyperspectral images is presented. In a first step, data are projected in a transformed space with a Maximum Noise Fraction transform, allowing the new components to be sorted in order of signal to noise ratio. The filtering is adapted to the signal to noise(More)
Support Vector Machines, recently introduced in hyperspectral imagery, are applied to classify land cover on images from the airborne CASI sensor with a small training set. A smoothing preprocessing step is achieved, based on a vectorial extension of the anisotropic diffusion nonlinear filtering process. It allows the separability of the classes to be(More)
The main objective of this work is to elaborate a generic methodological approach to build prospective scenarios spatially explicit at a local scale. This approach is based on the scenario 2 Revue Internationale de Géomatique. Volume X – n° X/200X method used in prospective studies, and uses methodological techniques developed for the modelling of complex(More)