L’article ‘Volumetric obscurance as a new tool to better visualize relief from Digital Elevation Models’ par Rolland et al. publié dans Remote Sensing

Identification d’un motif gravé grâce à la VO, en faisant varier l’exagération et le rayon d’influence (Shalabolino, Sibérie)
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Dans le cadre de son travail de doctorat Tanguy Rolland et collaborateurs ont développé une technique permettant de mettre en lumière les variations de relief d’une surface. Le concept est issu du monde des jeux vidéo. Il s’agit de l’occlusion ambiante, et plus particulièrement de la Volumetric Obscurance. Les modèles numériques de terrain, qu’ils intéressent une petite surface ou une grande, sont traités en quelques secondes, au pire quelques minutes, et les surfaces concaves et convexes sont identifiées très facilement. Un point fort de cette étude: elle est accompagnée d’un logiciel fonctionnant sous Windows, d’un plugin QGIS, et du code Python 3 (voir ici).

Abstract: The use of digital elevation models (DEMs) has become much more widespread in recent years, thanks to technological developments that facilitate their creation and availability. To exploit these data, a set of processing techniques has been developed to reveal the characteristic structures of the relief. This paper presents a new method based on the volumetric approach, and two derivatives. These methods are evaluated on three DEMs at different resolutions and scales: a freely accessible DEM from JAXA DEM covering part of North-East Tanzania, a DEM corresponding to rock art in Siberia, and a DEM of an archaeological Bronze Age funeral structure. Our results show that with the volumetric approach, concave and convex areas are clearly visible, with contrast marking slope breaks, while the overall relief is attenuated. Furthermore, the use of volume reduces the impact of noise, which can occur when processing is based on sky visibility (e.g., sky-view factor or positive openness) or second derivatives. Finally, the volumetric approach allows the implementation of a vertical exaggeration factor, the result of which will enhance the particular characteristics of the landscape. The present study comes with a standalone executable program for Windows, a QGIS plugin, and the scripts written in Python, including GPU compute capability (via CUDA) for faster processing.

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