Presentation + Paper
26 October 2022 Synergistic use of UAV and TLS data for precise rockfall monitoring over a hanging monastery
Aggeliki Kyriou, Konstantinos Nikolakopoulos, Ioannis Koukouvelas
Author Affiliations +
Abstract
The preservation of cultural heritage and landscapes, which are constantly endangered by man-made hazards and natural disasters (earthquakes, landslides, floods, fires, urbanization, etc.) is a strategic priority for humanity. Nowadays, remote sensing stands out as an important, innovative and cost-effective tool with great potentialities for the protection and monitoring of cultural heritage as well as the prevention of monuments and sites, due to non-invasiveness in such a vulnerable research objective. In this context, remote sensing data, acquired by Unmanned Aerial Vehicles (UAV) and Terrestrial Laser Scanning (TLS) surveys were utilized for the precise mapping and monitoring of rockfalls occurred over an eleventh-century BC. Holy Monastery. The monastery is built on a rocky slope, which hangs over the bank of the ancient river Triton, and it is located a few kilometers away of the village of Andritsena within the Region of Western Greece. Significant damages to the dome of the monastery were detected after the occurrence of rockfalls in late January 2021. Remote sensing data were collected over the monastery area and were processed appropriately. UAV and TLS point cloud were generated and change detection methods were applied for the precise mapping of the rockfalls. Moreover, UAV and TLS point clouds were integrated towards a more comprehensive mapping.
Conference Presentation
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Aggeliki Kyriou, Konstantinos Nikolakopoulos, and Ioannis Koukouvelas "Synergistic use of UAV and TLS data for precise rockfall monitoring over a hanging monastery", Proc. SPIE 12268, Earth Resources and Environmental Remote Sensing/GIS Applications XIII, 122680A (26 October 2022); https://doi.org/10.1117/12.2636150
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KEYWORDS
Unmanned aerial vehicles

Clouds

3D modeling

Cultural heritage

Georeferencing

Landslides

Remote sensing

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