Aurélien Arnaubec

Les techniques polarimétriques et interférométriques SAR (PolInSAR) en bande P (250Mhz - 500Mhz), offrent une solution à échelle mondiale pour l'étude des paramètres de la biomasse végétale. L'objectif de ce travail de doctorat est de proposer une analyse de la précision d'estimation que l'on peut espérer obtenir à l'aide de ces techniques pour certains paramètres tels que la hauteur de la végétation et du sol, en s'appuyant sur une des modélisation de la végétation les plus utilisées (modèle RVoG). Nous avons tout d'abord déterminé la Borne de Cramér-Rao (BCR) qui permet de fournir une borne inférieure à la variance d'estimation lorsque cette dernière est sans biais. Cette étude montre qu'il peut exister une grande diversité de situations, avec dans les cas favorables un écart type d'estimation de l'ordre du mètre pour une taille d'échantillon de 100 pixels. Il a pu ainsi être montré que la technique d'estimation la plus utilisée conduit à des variances proches de la BCR dans un grand nombre de situations. Cette étude a également permis d'analyser les performances quand on réduit l'information polarimétrique (Polarimétrie Compacte). Nous avons ensuite analysé l'influence de quelques écarts au modèle RvoG (fluctuations de la hauteur du sol et de la végétation, et décorrélation temporelle). La décorrélation temporelle semble être la perturbation la plus critique car elle peut fortement biaiser l'estimation. Finalement nous avons illustré, sur des forêts tropicales et tempérées, certains de ces résultats théoriques à l'aide de données acquises par les systèmes radar RAMSES et SETHI de l'ONERA en bande P.

Underwater images are altered by the physical characteristics of the medium through which light rays pass before reaching the optical sensor. Scattering and wavelength-dependent absorption significantly modify the captured colors depending on the distance of observed elements to the image plane. In this paper, we aim to recover an image of the scene as if the water had no effect on light propagation. We introduce SUCRe, a novel method that exploits the scene’s 3D structure for underwater color restoration. By following points in multiple images and tracking their intensities at different distances to the sensor, we constrain the optimization of the parameters in an underwater image formation model and retrieve unattenuated pixel intensities. We conduct extensive quantitative and qualitative analyses of our approach in a variety of scenarios ranging from natural light to deep-sea environments using three underwater datasets acquired from real-world scenarios and one synthetic dataset. We also compare the performance of the proposed approach with that of a wide range of existing state-of-the-art methods. The results demonstrate a consistent benefit of exploiting multiple views across a spectrum of objective metrics. Our code is publicly available at github.com/clementinboittiaux/sucre.

The seismic hazard posed by submarine faults and the capacity of submarine earthquakes to trigger mass wasting are poorly understood because we lack detailed characterizations of coseismic ruptures at the seafloor. Here, we present comprehensive mapping of a seafloor rupture caused by the 2004M_w6.3 Les Saintes earthquake on the Roseau normal fault in the Lesser Antilles. We report the visual characteristics, displacement profile, and note pronounced asymmetry of the rupture that bears similarities with well-studied subaerial normal fault ruptures. We also identify footwall-derived mass wasted debris that locally cover the coseismic rupture, and show that ground accelerations of 0.1–0.2 g can trigger submarine mass wasting events in well consolidated bedrock along unstable, over-steepened, scarps. Our study demonstrates the potential of underwater vehicles for detailed mapping of seafloor ruptures and hints at a key role for earthquakes in shaping submarine bedrock landscapes by triggering mass wasting events.

This paper addresses the lack of “push-button” software for optical marine imaging, which currently limits the use of photogrammetric approaches by a wider community. It presents and reviews an open source software, Matisse, for creating textured 3D models of complex underwater scenes from video or still images. This software, developed for non-experts, enables routine and efficient processing of underwater images into 3D models that facilitate the exploitation and analysis of underwater imagery. When vehicle navigation data are available, Matisse allows for seamless integration of such data to produce 3D reconstructions that are georeferenced and properly scaled. The software includes pre-processing tools to extract images from videos and to make corrections for color and uneven lighting. Four datasets of different 3D scenes are provided for demonstration. They include both input images and navigation and associated 3D models generated with Matisse. The datasets, captured under different survey geometries, lead to 3D models of different sizes and demonstrate the capabilities of the software. The software suite also includes a 3D scene analysis tool, 3DMetrics, which can be used to visualize 3D scenes, incorporate elevation terrain models (e.g., from high-resolution bathymetry data) and manage, extract, and export quantitative measurements for the 3D data analysis. Both software packages are publicly available.