Alvarez-Vanhard Emilien- Phd
- PostDoc Position at Institut Français de Recherche pour l'Exploitation de la Mer
Alvarez-Vanhard Emilien
- Phd
- PostDoc Position at Institut Français de Recherche pour l'Exploitation de la Mer
About
12
Publications
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Introduction
I am postdoctoral researcher in the marine spatial ecology laboratory DYNECO-LEBCO Ifremer. My research focuses on environmental monitoring and mapping by optical remote sensing using convolutional neural networks. In my work I exploit the flexibility of UAVs as a bridge between satellite and in-situ observations via approaches ranging from multi-scale analysis to data fusion.
Current institution
Publications
Publications (12)
Recently, deep convolutional networks have made great progress on the task of super resolution, i.e. reconstructing images with finer spatial resolution. However, although the reconstructions are visually impressive, they may lack physical consistency. This aspect is sought in remote sensing, where the resolution of satellite imagery (e.g. Sentinel...
L’observation de la Terre par satellite est désormais un outil essentiel pour connaître les motifs de distribution spatio-temporelle des écosystèmes. Les observations satellitaires restent cependant limitées par un compromis entre les résolutions spatiales, temporelles et spectrales qui rend difficile le passage d’échelle entre observations in-situ...
La technologie drone est une nouvelle source de données de télédétection qui offre de nouvelles perspectives aux sciences de l'observation de la Terre. Elle permet un nouveau régime d'observation flexible et à très haute résolution spatiale qui apparaît comme complémentaire à celui des systèmes satellitaires et favorise l'application du changement...
Unmanned aerial vehicles (UAVs) and satellite constellations are both essential Earth Observation (EO) systems for monitoring land surface dynamics. The former is frequently used for its acquisition flexibility and its ability to supply imagery with very high spatial resolution (VHSR); the latter is interesting for supplying time-series data over l...
Remote-sensing time-series data are significant for global environmental change research and a better understanding of the Earth. However, remote-sensing acquisitions often provide sparse time series due to sensor resolution limitations and environmental factors, such as cloud noise for optical data. Image interpolation is the method that is often...
Unmanned aerial vehicles (UAV) and satellites are both essential Earth observation systems for monitoring land surface dynamics. UAVs are frequently used for their capability to acquire spontaneous images (even under clouds); conversely, satellites are interesting for the supply of times series data on wide areas. However, satellite spatial and tem...
Offering remarkable biodiversity, coastal salt marshes also provide a wide variety of ecosystem services: cultural services (leisure, tourist amenities), supply services (crop production, pastoralism) and regulation services including carbon sequestration and natural protection against coastal erosion and inundation. The consideration of this coast...
This research aims to assess the capabilities of Very High Spatial Resolution (VHSR) hyperspectral satellite data in order to discriminate urban tree diversity. Four dimension reduction methods and two classifiers are tested, using two learning methods and applied with four in situ sample datasets. An airborne HySpex image (408 bands/2 m) was acqui...
