• Title/Summary/Keyword: lineament

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The First Discovery of Quaternary Fault in the Western Part of the South Yangsan Fault - Sinwoo Site (양산단층 남부 이서 지역에서 최초로 발견된 제4기 단층 - 신우지점)

  • Choi, Sung-Ja;Ghim, Yong Sik;Cheon, Youngbeom;Ko, Kyoungtae
    • Economic and Environmental Geology
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    • v.52 no.3
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    • pp.251-258
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    • 2019
  • During the detailed geological survey around the southern Yangsan Fault, we newly found a Quaternary fault outcrop, which cuts unconsolidated sediments. The fault named the Sinwoo site, located in the Sinwoo pasture, Miho-ri, Duseo-myeon, Ulsan metropolitan city, is the first discovered Quaternary fault near the western part of the south Yangsan Fault. In this study, we provide information on characteristics of fault geometry and unconsolidated sediment at Sinwoo site based on the analysis data of topography, drainage, and lineament around the study site. The fault site is situated at pediment slope, but fan-shaped middle terrace, as well as thick sediment exposed at low terrace, indicates that the unconsolidated sediments have been deposited in the alluvial fan environment. The drainage develops to the third-order drainage system, and the first and the second drainage system meet at right angles to each other and form a radial drainage pattern. In addition, the NE-SW direction lineaments can be identified on the basis of the curvature of the river and the step of the topographic relief, running over the Sinwoo site. The fault of $N30-35^{\circ}E/79-82^{\circ}SE$ shows ~ 5.8 m apparent vertical offset and dominantly reverse-slip sense based on slickenline, rotation of pebbles, and drag folding at footwall. However, some discontinuous sediments observed in the footwall are interpreted as fissure-filling materials due to the strike-slip movement. Now, we are under multidisciplinary investigations of additional field survey and age dating in order to determine the evolution of Sinwoo site fault during the Quaternary.

Landslide Susceptibility Mapping Using Deep Neural Network and Convolutional Neural Network (Deep Neural Network와 Convolutional Neural Network 모델을 이용한 산사태 취약성 매핑)

  • Gong, Sung-Hyun;Baek, Won-Kyung;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.38 no.6_2
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    • pp.1723-1735
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    • 2022
  • Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

Characterization of Fault Kinematics based on Paleoseismic Data in the Malbang area in the Central Part of the Ulsan Fault Zone (고지진학적 자료를 이용한 울산단층대 중부 말방지역에서의 단층운동 특성 해석)

  • Park, Kiwoong;Prasanajit, Naik Sambit;Gwon, Ohsang;Shin, Hyeon-Cho;Kim, Young-Seog
    • Journal of the Korean earth science society
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    • v.43 no.1
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    • pp.151-164
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    • 2022
  • According to the records of historical and instrumental earthquakes, the southeastern part of the Korean Peninsula is considered the highest seismic activity area. Owing to recent reports of numerous Quaternary faults along the Yangsan and Ulsan fault zones, paleoseismological studies are being actively conducted in these areas. The study area is located in the central part of the Ulsan fault zone, where the largest number of active faults have been reported. Based on lineament and geomorphic analysis using LiDAR images and aerial photographs, fault-related landforms showing topographic relief were observed and a trench survey was conducted. The trench length 20 m, width 5 m, depth 5 m is located approximately 300 m away to the northeast from the previously reported Malbang fault. From the trench section, we interpreted the geometric and kinematic characteristics of the fault based on the deformed features of the Quaternary sedimentary layers. The attitude of the reverse fault, N26°W/33°NE, is similar to those of the reported faults distributed along the Ulsan fault zone. Although a single apparent displacement of approximately 40 cm has been observed, the true displacement could not be calculated due to the absence of the slickenline on the fault plane. Based on the geochronological results of the cryogenic structure proposed in a previous study, the most recent faulting event has been estimated as being earlier than the late Wurm glaciation. We interpreted the thrust fault system of the study area as an imbrication structure based on the previous studies and the fault geometry obtained in this additional trench. Although several previous investigations including many trench surveys have been conducted, they found limited success in obtaining the information on fault parameters, which could be due to complex characteristics of the reverse fault system. Additional paleoseismic studies will contribute to solving the mentioned problems and the comprehensive fault evolution.