• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.248-248
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• 2023

In recent years, the number of landslides in Korea has been increasing due to extreme weather events such as localized heavy rainfall and typhoons. Landslides often occur with debris flows, land subsidence, and earthquakes. They cause significant damage to life and property. 64% of Korea's land area is made up of mountains, the government wanted to predict landslides to reduce damage. In response, the Korea Forest Service has established a 'Landslide Information System' to predict the likelihood of landslides. This system selects a total of 13 landslide factors based on past landslide events. Using the LR technique (Logistic Regression) to predict the possibility of a landslide occurrence and the accuracy is known to be 0.75. However, most of the data used for learning in the current system is on landslides that occurred from 2005 to 2011, and it does not reflect recent typhoons or heavy rain. Therefore, in this study, we will apply a total of six machine learning techniques (KNN, LR, SVM, XGB, RF, GNB) to predict the occurrence of landslides based on the data of Inje, Gangwon-do, which was recently produced by the National Institute of Forest. To predict the occurrence of landslides, it is necessary to process converting landslide events and factors data into a suitable form for machine learning techniques through ArcGIS and Python. In addition, there is a large difference in the number of data between areas where landslides occurred or not. Therefore, the prediction was performed after correcting the unbalanced data using Tomek Links and Near Miss techniques. Moreover, to control unbalanced data, a model that reflects soil properties will use to remove absolute safe areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• The Journal of Engineering Geology
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• v.25 no.1
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• pp.115-129
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• 2015

The cut-slope of a large-sectional tunnel portal is recognized as a potential area of weakness due to unstable stress distribution and possible permanent displacement. This paper presents a case study of a slope failure and remediation for a large-scale cut-slope at a tunnel portal. Extensive rock-slope brittle failure occurred along discontinuities in the rock mass after 46 mm of rainfall, which caused instability of the upper part of the cut-slope. Based on a geological survey and face mapping, the reason for failure is believed to be the presence of thin clay fill in discontinuities in the weathered rock mass and consequent saturationinduced joint weakening. The granite-gneiss rock mass has a high content of alkali-feldspar, indicating a vulnerability to weathering. Immediately before the slope failure, a sharp increase in displacement rate was indicated by settlement-time histories, and this observation can contribute to the safety management criteria for slope stability. In this case study, emergency remediation was performed to prevent further hazard and to facilitate reconstruction, and counterweight fill and concrete filling of voids were successfully applied. For ultimate remediation, the grid anchor-blocks were used for slope stabilization, and additional rock bolts and grouting were applied inside the tunnel. Limit-equilibrium slope stability analysis and analyses of strereographic projections confirmed the instability of the original slope and the effectiveness of reinforcing methods. After the application of reinforcing measures, instrumental monitoring indicated that the slope and the tunnel remained stable. This case study is expected to serve as a valuable reference for similar engineering cases of large-sectional slope stability.

• Geophysics and Geophysical Exploration
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• v.13 no.3
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• pp.268-276
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• 2010

Earthquake Hazard Mitigation Law was activated into force on March 2009. By the law, the obligation to monitor the effect of earthquake on the facilities was extended to many organizations such as gas company and local governments. Based on the estimation of National Emergency Management Agency (NEMA), the number of free-surface acceleration stations would be expanded to more than 400. The advent of internet protocol and the more simplified operation have allowed the quick and easy installation of seismic stations. In addition, the dynamic range of seismic instruments has been continuously improved enough to evaluate damage intensity and to alert alarm directly for earthquake hazard mitigation. For direct visualization of damage intensity and area, Real Time Intensity COlor Mapping (RTICOM) is explained in detail. RTICOM would be used to retrieve the essential information for damage evaluation, Peak Ground Acceleration (PGA). Destructive earthquake damage is usually due to surface waves which just follow S wave. The peak amplitude of surface wave would be pre-estimated from the amplitude and frequency content of first arrival P wave. Earthquake Early Warning (EEW) system is conventionally defined to estimate local magnitude from P wave. The status of EEW is reviewed and the application of EEW to Odesan earthquake is exampled with ShakeMap in order to make clear its appearance. In the sense of rapidity, the earthquake announcement of Korea Meteorological Agency (KMA) might be dramatically improved by the adaption of EEW. In order to realize hazard mitigation, EEW should be applied to the local crucial facilities such as nuclear power plants and fragile semi-conduct plant. The distributed EEW is introduced with the application example of Uljin earthquake. Not only Nation-wide but also locally distributed EEW applications, all relevant information is needed to be shared in real time. The plan of extension of Korea Integrated Seismic System (KISS) is briefly explained in order to future cooperation of data sharing and utilization.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1827-1836
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• 2022

Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.

• Progress in Medical Physics
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• v.20 no.4
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• pp.298-307
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• 2009

By using the MR T2 map technique, this study intends, first, to measure the change of T2 values of cartilage between healthy people and patients with osteoarthritis and, second, to assess the form and the damage of cartilage in the knee-joint, through which this study would consider the utility of the T2 map technique. Thirty healthy people were selected based on their clinical history and current status and another thirty patients with osteoarthritis of the knee who were screened by simple X-ray from November 2007 to December 2008 were selected. Their T2 Spin Echo (SE hereafter) images for the cartilage of the knee joint were collected by using the T2 SE sequence, one of the multi-echo methods (TR: 1,000 ms; TE values: 6.5, 13, 19.5, 26, 32.5. 40, 45.5, 52). Based on these images, the changes in the signal intensity (SI hereafter) for each section of the cartilage of the knee joint were measured, which yielded average values of T2 through the Origin 7.0 Professional (Northampton, MA 01060 USA). With these T2s, the independent samples T-test was performed by SPSS Window version 12.0 to run the quantitative analysis and to test the statistical significance between the healthy group and the patient group. Closely looking at T2 values for each anterior and lateral articular cartilage of the sagittal plane and the coronal plane, in the sagittal plane, the average T2 of the femoral cartilage in the patient group with arthritis of the knee ($42.22{\pm}2.91$) was higher than the average T2 of the healthy group ($36.26{\pm}5.01$). Also, the average T2 of the tibial cartilage in the patient group ($43.83{\pm}1.43$) was higher than the average T2 in the healthy group ($36.45{\pm}3.15$). In the case of the coronal plane, the average T2 of the medial femoral cartilage in the patient group ($45.65{\pm}7.10$) was higher than the healthy group ($36.49{\pm}8.41$) and so did the average T2 of the anterior tibial cartilage (i.e., $44.46{\pm}3.44$ for the patient group vs. $37.61{\pm}1.97$ for the healthy group). As for the lateral femoral cartilage in the coronal plane, the patient group displayed the higher T2 ($43.41{\pm}4.99$) than the healthy group did ($37.64{\pm}4.02$) and this tendency was similar in the lateral tibial cartilage (i.e., $43.78{\pm}8.08$ for the patient group vs. $36.62{\pm}7.81$ for the healthy group). Along with the morphological MR imaging technique previously used, the T2 map technique seems to help patients with cartilage problems, in particular, those with the arthritis of the knee for early diagnosis by quantitatively analyzing the structural and functional changes of the cartilage.