Low-amplitude brittle deformations revealed by UAV surveys in alluvial fans along the northwest coast of Lake Baikal: Neotectonic significance and geological hazards

Lunina, Оksana V.; Gladkov, Anton A.; Bochalgin, Alexey V.

doi:10.1016/j.rse.2023.113897

Cited by 4 publications

(3 citation statements)

References 24 publications

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“…The previous section introduced several typical geological survey methods, which have varying degrees of application in mineral exploration. As a branch of remote sensing technology, remote sensing measurement based on UAV can make the acquisition of large-scale images more convenient and cost-effective, and has a wide range of applications in near surface geological surveys [10] . At the same time, deep learning, as a highly adaptable artificial intelligence method, is gradually being applied in the fields of geological feature discovery and mineral exploration.…”

Section: Mineral Exploration Methods Based On Uav and Deep Learningmentioning

confidence: 99%

Practical study of geological survey theory and method in mineral exploration

2024

Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024)

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Geological survey methods have been importantly applied and attempted in the field of mineral exploration. This paper compared and analyzed several typical geological survey methods and proposes a mineral exploration method based on UAV remote sensing technology and deep learning image recognition. By combining the super-pixel segmentation algorithm and CNN model, the efficiency and accuracy of remote sensing image feature recognition were improved, and the finding efficiency of mineral exploration was enhanced. The practical application results showed that the proposed method had a good performance in terms of mineral finding accuracy and applicability, and could make up for the shortcomings of traditional geological survey methods in mineral exploration.

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Section: Mineral Exploration Methods Based On Uav and Deep Learningmentioning

confidence: 99%

Practical study of geological survey theory and method in mineral exploration

2024

Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024)

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“…water permeability and fluctuations in groundwater levels, influencing surface runoff formation. Due to the lack of extensive weathering and stabilization, geotechnical materials within the new formation tend to be less compact and more susceptible to external factors such as rainfall, thereby heightening the likelihood of landslides [18][19][20]. Typically, older geological formations undergo extended periods of weathering and erosion, leading to diminished stability.…”

Section: Study Areamentioning

confidence: 99%

“…The new geological stratum remains relatively dynamic, with materials being relatively fresh and more responsive to water permeability and fluctuations in groundwater levels, influencing surface runoff formation. Due to the lack of extensive weathering and stabilization, geotechnical materials within the new formation tend to be less compact and more susceptible to external factors such as rainfall, thereby heightening the likelihood of landslides [18][19][20].…”

Section: Study Areamentioning

confidence: 99%

Susceptibility of Landslide Debris Flow in Yanghe Township Based on Multi-Source Remote Sensing Information Extraction Technology (Sichuan, China)

Guo,

Martínez-Graña

2024

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The extraction of real geological environment information is a key factor in accurately evaluating the vulnerability to geological hazards. Yanghe Township is located in the mountainous area of western Sichuan and lacks geological survey data. Therefore, it is important predict the spatial and temporal development law of landslide debris flow in this area and improve the effectiveness and accuracy of monitoring changes in landslide debris flow, this article proposes a method for extracting information on the changes in landslide debris flows combined with NDVI variation, which is based on short baseline interferometry (SBAS-InSAR) and optical remote sensing interpretation. In this article, we present relevant maps based on six main factors: vegetation index, slope, slope orientation, elevation, topographic relief, and formation lithology. At the same time, different remote sensing images were compared to improve the accuracy of landslide debris flow sensitivity assessments. The research showed that the highest altitude of the region extracted by multi-source remote sensing technology is 2877 m, and the lowest is 630 m, which can truly reflect the topographic relief characteristics of the region. The pixel binary model’s lack of regional restrictions enables a more accurate estimation of the Normalized Difference Vegetation Index (NDVI), bringing it closer to the actual vegetation situation. The study uncovered a bidirectional relationship between vegetation coverage changes and landslide deformation in the study area, revealing spatial–temporal evolution patterns. By employing multi-source remote sensing technology, the research effectively utilized changes in multi-period imagery and feature extraction methods to accurately depict the development process and distribution characteristics of landslide debris flow. This approach not only offers technical support but also provides guidance for evaluating the vulnerability of landslide debris flow in the region.

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