• Journal of the Korean GEO-environmental Society
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• v.23 no.3
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• pp.15-22
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• 2022

This study aims to observe the swelling representative rocks in Korea and to suggest improvements in the use of test methods and prior analysis in relation to the weathering of rocks. The swelling test and analysis were performed on the drilling cores obtained for the ground investigation at the domestic highway construction site. For the method of determining the absorption expansion index of rocks, the method proposed in "Standard Methods for Sample Collection and Specimen Preparation" of ISRM and Korean Rock Engineers Standard Rock Test Method was used. The specimen for the measurement of the expansion displacement was cylindrical with a height of 10 cm and a diameter of 5 cm. The existing swelling analysis method evaluates the sensitivity to weathering by using the maximum expansion displacement, but since the classification by bedrock grade is unclear, it is reasonable to use the rate of change of the expansion displacement according to the immersion time. It is necessary to conduct an experiment to distinguish between weathering and fault deterioration. In addition, long-term weathering prediction technology for each cancer type is needed through the expansion displacement analysis of the chemical weathering stage.

• Journal of the Korean association of regional geographers
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• v.4 no.2
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• pp.49-64
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• 1998

Bing-gye valley(Kyongbuk Province, South Korea) is well known as a tourist attraction because of its meteorologic characteristics that show subzero temperature during midsummer. Also, there are some interesting geomorphic features in the valley area. Therefore, the valley is worth researching in geomorphology field. The aim of this paper is to achieve two purposes. These are to clarify geomorphic features on talus within Bing-gye valley area, and to infer the origin of Bing-gye valley. The main results are summarized as follows. 1) The formation of Bing-gye valley It would be possible to infer the following two ideas regarding the formation of Bing-gye valley. One is that the valley was formed by differential erosion of stream along fault line, and the other is that the rate of upheaval comparatively exceeded the rate of stream erosion. Especially, the latter may be associated with the fact that the width of the valley is much narrow. Judging that the fact the width of the valley is much narrow, compared with one of its upper or lower valley, it is inferred that Bing-gye valley is transverse valley. 2) The geomorphic features of talus (1) Pattern It seems to be true that the removal of matrix(finer materials) by the running water beneath the surface can result in partly collapse hollows. Taluses are tongue-shaped or cone-shaped in appearance. They are $120{\sim}200m$ in length, $30{\sim}40m$ in maximum width. and $32{\sim}33^{\circ}$ in mean slope gradient. The component blocks are mostly homogeneous in size and shape(angular), which reflect highly jointed free face produced by frost action under periglacial environment. (2) Origin On the basis of previous studies, the type of the talus is classified into rock fall talus. When considered in conjunction with the degrees of both weathering of blocks and hardness of blocks, it can be explained that the talus was formed under periglacial environment in pleistocene time. (3) The inner structure of block accumulation I recognize a three-layered structure in the talus as follows: (a) superficial layer; debris with openwork texture at the surface, 1.3m thick. (b) intermediate layer: small debris(about 5cm in diameter) with fine matrix(including humic soil), 70cm thick. (c) basal layer: over 2m beneath surface, almost pure soil horizon without debris (4) The stage of landform development Most of the blocks are now covered with lichen, and/or a mantle of weathering. It is believed that downslope movement by talus creep well explains the formation of concave slope of the talus. There is no evidence of present motion in the deposit. Judging from above-mentioned facts, the talus of this study area appears to be inactive and fossil landform.

• 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.