Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slope

Zhao, Mingyu; Chen, Jianping; Song, Shengyuan; Li, Yongchao; Wang, Fengyan; Wang, Sicong; Liu, Dianze

doi:10.1016/j.jag.2023.103558

Cited by 5 publications

(3 citation statements)

References 40 publications

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“…These dimensions are associated with standard characterization techniques, like imagery, UAV-based photogrammetry [20,21] and geological mapping, drilling and scanlines, and grid-based sampling, and consist in segmenting the dimensional space by counting and measuring elements within it. This task can be particularly difficult for granular materials with large grain-size variability, as stated by Wolcott and Church [22], in sediments with a fluvial origin, such as those analyzed in this paper.…”

Section: Introductionmentioning

confidence: 99%

Automatic Characterization of Block-In-Matrix Rock Outcrops through Segmentation Algorithms and Its Application to an Archaeo-Mining Case Study

Cristóbal,

Rigueira,

Pérez-Rey

et al. 2024

Geosciences

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The mechanical behavior of block-in-matrix materials is heavily dependent on their block content. This parameter is in most cases obtained through visual analyses of the ground through digital imagery, which provides the areal block proportion (ABP) of the area analyzed. Nowadays, computer vision models have the capability to extract knowledge from the information stored in these images. In this research, we analyze and compare classical feature-detection algorithms with state-of-the-art models for the automatic calculation of the ABP parameter in images from surface and underground outcrops. The outcomes of this analysis result in the development of a framework for ABP calculation based on the Segment Anything Model (SAM), which is capable of performing this task at a human level when compared with the results of 32 experts in the field. Consequently, this model can help reduce human bias in the estimation of mechanical properties of block-in-matrix materials as well as contain underground technical problems due to mischaracterization of rock block quantities and dimensions. The methodology used to obtain the ABP at different outcrops is combined with estimates of the rock matrix properties and other characterization techniques to mechanically characterize the block-in-matrix materials. The combination of all these techniques has been applied to analyze, understand and try, for the first time, to model Roman gold-mining strategies in an archaeological site in NW Spain. This mining method is explained through a 2D finite-element method numerical model.

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Section: Introductionmentioning

confidence: 99%

Automatic Characterization of Block-In-Matrix Rock Outcrops through Segmentation Algorithms and Its Application to an Archaeo-Mining Case Study

Cristóbal,

Rigueira,

Pérez-Rey

et al. 2024

Geosciences

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“…China frequently suffers from debris flow disasters (Zou et al, 2019), with a total of 899 incidents occurrences are reported alone in the year 2020 across the country. Among geological disasters, debris flow causes more casualties in Beijing (Xie et al, 2001;Zhu, 2018;Zhao et al, 2023). The research area for this study is Mentougou District, located in the southwestern part of Beijing, which is a mountainous region with abundant resources (Zhu, 2018).…”

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confidence: 99%

Assessment of debris flow risk in Mentougou District, Beijing, based on runout of potential debris flow

Li,

Zheng,

Guo

et al. 2024

Front. Earth Sci.

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Debris flow is a prevalent geological disaster in Beijing, particularly in the Mentougou District, situated in the mountainous southwestern region of Beijing City. The past irrational exploitation of minerals has led to a substantial accumulation of slag, providing abundant loose materials for the formation of debris flow in the study area. Different from the traditional method of using hazard and vulnerability to carry out debris flow risk assessment, this paper proposes a debris flow risk assessment method based on (a) the possibility of debris flow occurrence, (b) the value of the disaster-affected object, and (c) the destructiveness of the debris flow. The possibility of 41 gully debris flows occurring was determined through theoretical calculations. Using the SFLOW model, the runout of the potential debris flow was simulated. On this basis, an investigation of the value of the disaster-affected objects was carried out. At the same time, according to the simulated movement information of debris flow, its destructiveness was determined. According to the results of the occurrence possibility of the debris flow, its destructiveness, and the value of the disaster-affected object, the risk levels of 41 potential debris flow gullies in the Mentougou District were obtained. The research results can guide the warning systems for debris flows in the Mentougou District of Beijing.

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confidence: 99%

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Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slope

Cited by 5 publications

References 40 publications

Automatic Characterization of Block-In-Matrix Rock Outcrops through Segmentation Algorithms and Its Application to an Archaeo-Mining Case Study

Automatic Characterization of Block-In-Matrix Rock Outcrops through Segmentation Algorithms and Its Application to an Archaeo-Mining Case Study

Assessment of debris flow risk in Mentougou District, Beijing, based on runout of potential debris flow

Table2.DOCX

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