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Red Relief Image Maps of the Ruinon Landslide, Northern Italy (2021-2022)

Authors: Yordanov, Vasil; Xuan, Quang Truong; Brovelli, Maria Antonia;

Red Relief Image Maps of the Ruinon Landslide, Northern Italy (2021-2022)

Abstract

Red Relief Image Maps of the Ruinon Landslide, Northern Italy. The maps are from UAV surveys carried out above the landslide on the following dates: 06 July 2021 29 October 2021 02 May 2022 05 July 2022 05 October 2022 29 October 2022 The maps are in WGS 84/ UTM zone 32N (EPSG:32632). They are not finely co-registered. The map production process details are discussed in Yordanov, V.; Truong, Q.X.; Brovelli, M.A. Estimating Landslide Surface Displacement by Combining Low-Cost UAV Setup, Topographic Visualization and Computer Vision Techniques. Drones 2023, 7, 85. https://doi.org/10.3390/drones7020085 The maps are produced as part of the "Geoinformatics and Earth Observation for Landslide Monitoring" Italy-Vietnam. The work is partially funded by the Italian Ministry of Foreign Affairs and International Cooperation within the project “Geoinformatics and Earth Observation for Landslide Monitoring” CUP D19C21000480001 (Italian side) and partially funded by the Ministry of Science and Technology of Vietnam (MOST) (Vietnamese side) by the Bilateral Scientific Research project between Vietnam and Italy, code: NÐT/IT/21/14

{"references": ["Yordanov, Vasil et al. (2023) stimating Landslide Surface Displacement by Combining Low-Cost UAV Setup, Topographic Visualization and Computer Vision Techniques. https://doi.org/10.3390/drones7020085"]}

Keywords

landslides, UAV, survey, RRIM, computer vision, displacement, monitoring, optical flow, survey, FOSS

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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