Geographic Information Sciences Commons^™

Panel 1 Paper 1.3: Le Paysage Rural Patrimonial, Outil Et Projet Au Service De La Lutte Contre Le Réchauffement Climatique, Régis Ambroise

ISCCL Scientific Symposia and Annual General Meetings // Symposiums scientifiques et assemblées générales annuelles de l'ISCCL // Simposios científicos yy las Asambleas Generales Anuales

Cette intervention fait référence au paragraphe de la résolution19GA 2017/30 du Conseil International des Monuments et des Sites indiquant que « la 19° Assemblée générale de l’ICOMOS… salue l’adoption de l’accord de Paris et encourage tous les membres de l’ICOMOS à renforcer leurs efforts pour appuyer sa mise en œuvre et identifier les réponses qui s’appuient sur le patrimoine ou les paysages culturels… ». Elle prend l’exemple de la façon dont les paysages de terrasses ont été abordés ces dernières années dans trois situations différentes : en France, dans le Guizhou en Chine et dans le Priorat en Espagne.

En …

Crowdsourcing The Georeferencing Of Historical Pictures, Timothée Produit, Nicolas Blanc, Sarah Composto, Jens Ingensand, Loic Furhoff

Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings

Countless organizations own archive pictures which are not used due to the difficulty of localizing them. Only the participation of volunteers can help to identify the image content. Through an accessible web interface called smapshot, citizens are able to georeference historical images without any prior specific competence. To avoid the volunteers to face the complexity of 3D digitization and navigation, we implemented a state of the art photogrammetry camera orientation algorithm in the platform. Currently several thousand images from all around Switzerland have been georeferenced by the crowd. At this time the tool is mainly used by the population for …

Robust Railroad Cable Detection In Rural Areas From Mls Point Clouds, Máté Cserép, Péter Hudoba, Zoltán Vincellér

Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings

Monitoring of the railroad infrastructure is crucial for safety concerns and accident prevention. This task requires regular surveillance which is nowadays still carried out by expensive and time consuming manual visual inspections in many countries. The problem of railroad cable recognition (contact cables, catenary cables, return current cables) in rural areas based on LiDAR point clouds has it own methods, but current state of the art solutions suffer from extremely high computational load due the extensive size of the datasets. In this study we analyzed and compared novel robust solutions focusing on minimizing the assumptions (positions and distances of track …