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Cartographier l'occupation du sol à grande échelle : optimisation de la photo-interprétation par segmentation d'image.

Abstract : Over the last fifteen years, the emergence of remote sensing data at Very High Spatial Resolution (VHRS) and the democratization of Geographic Information Systems (GIS) have helped to meet the new and growing needs for spatial information. The development of new mapping methods offers an opportunity to understand and anticipate land cover change at large scales, still poorly known. In France, spatial databases about land cover and land use at large scale have become an essential part of current planning and monitoring of territories. However, the acquisition of this type of database is still a difficult need to satisfy because the demands concern tailor-made cartographic productions, adapted to the local problems of the territories. Faced with this growing demand, regular service providers of this type of data seek to optimize manufacturing processes with recent image-processing techniques. However, photo interpretation remains the favoured method of providers. Due to its great flexibility, it still meets the need for mapping at large scale, despite its high cost. Using fully automated production methods to substitute for photo interpretation is rarely considered. Nevertheless, recent developments in image segmentation can contribute to the optimization of photo-interpretation practice. This thesis presents a series of tools that participate in the development of digitalization assistance for the photo-interpretation exercise. The assistance results in the realization of a pre-cutting of the landscape from a segmentation carried out on a VHRS image. Tools development is carried out through three large-scale cartographic services, each with different production instructions, and commissioned by public entities. The contribution of these automation tools is analysed through a comparative analysis between two mapping procedures: manual photo interpretation versus digitally assisted segmentation. The productivity gains brought by segmentation are evaluated using quantitative and qualitative indices on different landscape configurations. To varying degrees, it appears that whatever type of landscape is mapped, the gains associated with assisted mapping are substantial. These gains are discussed both technically and thematically from a commercial perspective.
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Maxime Vitter. Cartographier l'occupation du sol à grande échelle : optimisation de la photo-interprétation par segmentation d'image.. Géographie. Université de Lyon, 2018. Français. ⟨NNT : 2018LYSES011⟩. ⟨tel-02094240⟩

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