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26 August 2020 Accuracy validation of digital elevation models for effective forest road management
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Proceedings Volume 11524, Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020); 115240S (2020) https://doi.org/10.1117/12.2571007
Event: Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020), 2020, Paphos, Cyprus
Abstract
Digital Elevation Models (DEMs) have become a widely used tool and product in the last 20 years. They provide a snapshot of the landscape and landscape features while also providing elevation values. They have allowed us to better visualize and interrogate topographic features. A landscape feature is a road and the location of the road is the “foundation” of any road. A road constructed in a poor location can fail and cause serious environmental damage, as well as add financial strain from continuous and costly maintenance problems. The forest managers know that forest roads must be inspected regularly and maintained as necessary to minimize erosion of the road surface, otherwise, they will require costly repairs. Forest roads represent a significant investment by forest owners and as such, this investment must be preserved. Nowadays forest managers expect the field survey also use DEM and orthophotos datasets to better understand the condition of the road network and to set maintenance and upgrade priorities. In this study, we validate several DEMs and we compare them to the measurements of a detailed road surveying with geodesic GPS. The aim is to use DEMs to spot troubles in the forest road network and relieve the forest owner from the cost of periodic field survey of the forest roads.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vasileios Giannoulas, Christos Stamatiou, Sarantis-Angelos Liampas, and Theodora Stalioglou "Accuracy validation of digital elevation models for effective forest road management", Proc. SPIE 11524, Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020), 115240S (26 August 2020); https://doi.org/10.1117/12.2571007
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