Laurence Hubert-Moy

Learn 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)
– 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 identification and monitoring of wooded hedgerows at field boundaries present a great interest in intensive agricultural landscapes because they protect crops against wind and water, and are recognized for their ecological values [1]. These linear features can reduce pollutant loads in runoff and mitigate the effects of discharge runoff directly into(More)
— Leaving fields with a vegetation cover during the winter is one of the main ways to reduce water pollution, in restricting pollutant fluxes towards rivers. The bare soils/vegetation ratio monitoring can be carried out daily at a coarse spatial resolution with SPOT VEGETATION (1 km), and also at a higher spatial resolution with SPOT HRVIR (20 m), but with(More)
Keywords: Radiative transfer theory BRDF Vegetation Adding method SAIL model Kuusk' model The SAIL model (proposed by Verhoef) is largely used in the remote sensing community to calculate the canopy Bidirectional Reflectance Distribution Function. The simulation results appear acceptable compared to observations especially for not very dense planophile(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)
—The goal of this paper is to propose a methodology based on vegetation index fusion to provide an accurate estimation of the fraction of vegetation cover (fCover). Because of the partial and imprecise nature of remote-sensing data, we opt for the evi-dential framework that allows us to handle such kind of information. The defined fCover belief functions(More)