Estelle Ployon

Digital Tools for Managing and Promoting Karst Geosites in Southeast France

This article provides an overview of the various digital tools we have used and developed to study and promote a range of karst geosites. Our work focused on the very high heritage value endokarst sites (caves or karst networks) in France’s Ardèche département (Chauvet Cave, Aven d’Orgnac) and Chartreuse (Granier cave network), Vercors (Choranche Caves) and Bauges (Prérouge Cave) Regional Parks. These tools were developed using innovative, high-tech digital monitoring and 3D modelling technologies and combined laser scanners, digital cameras and sensors with specialised software. The resulting tools are now being used in the management and promotion of these sites, which are important territorial and heritage resources in areas where geotourism is increasing and being integrated into local planning strategies.

3D displacement retrieval on glacial areas by airborne multi-view photogrammetry

With the development of photogrammetry and computer vision, Unmanned Aerial Vehicle (UAV) embedded with digital compact camera plays an important role on gathering geographic information [1]. In this context, a novel method is proposed in this article for monitoring displacement of natural environment by airborne multi-view photogrammetry. The method is implemented for calculating 3D displacement of a glacier area in one month and a half. We illustrate the application of Micmac, a powerful and free photogrammetry software, for point cloud reconstruction. With the GPS embedded on the UAV whose precision is not quiet high, we succeed in georeferencing point clouds. As we do not have any ground control point in land, two different ways of registration have been introduced to align point clouds. Afterwards, a set of tools is presented for calculating 2D displacement maps from point clouds. We introduce at last an inversion processing to calculate a 3D displacement map. The final result shows the 3D displacement of each pixel in the entire scene. Since final result is influenced by the precision of point cloud registration, this paper also highlights useful improvements to do in the future to obtain the 3D displacement with higher precision.