• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.5
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• pp.101-108
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• 2017

Recently, the occurrence of landslides has been increasing over the years due to the extreme weather event. Developments of landslides monitoring technology that reduce damage caused by landslide are urgently needed. Therefore, in this study, a strain ratio sensor was developed to predict the ground behavior during the slope failure, and the change in surface ground displacement was observed as slope failed on the field model experiment. As a result, in the slope failure, the ground displacement process increases the risk of collapse as the inverse displacement approaches zero. It is closely related to the prediction of precursor. In all cases, increase in displacement and reverse speed of inverse displacement with time was observed during the slope failure, and it is very important event for monitoring collapse phenomenon of risky slopes. In the future, it can be used as disaster prevention technology to contribute in reduction of landslide damage and activation of measurement industry.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1303-1322
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• 2020

Indonesia is more prone to natural disasters due to its geological condition under the three main plates, making Indonesia experience frequent seismic activity, causing earthquakes, volcanic eruption, and tsunami. Those disasters could lead to other disasters such as landslides, floods, land subsidence, and coastal inundation. Monitoring those disasters could be essential to predict and prevent damage to the environment. We reviewed the application of remote sensing and Geographic Information System (GIS) for detecting natural disasters in the case of Indonesia, based on 43 articles. The remote sensing and GIS method will be focused on InSAR techniques, image classification, and susceptibility mapping. InSAR method has been used to monitor natural disasters affecting the deformation of the earth's surface in Indonesia, such as earthquakes, volcanic activity, and land subsidence. Monitoring landslides in Indonesia using InSAR techniques has not been found in many studies; hence it is crucial to monitor the unstable slope that leads to a landslide. Image classification techniques have been used to monitor pre-and post-natural disasters in Indonesia, such as earthquakes, tsunami, forest fires, and volcano eruptions. It has a lack of studies about the classification of flood damage in Indonesia. However, flood mapping was found in susceptibility maps, as many studies about the landslide susceptibility map in Indonesia have been conducted. However, a land subsidence susceptibility map was the one subject to be studied more to decrease land subsidence damage, considering many reported cases found about land subsidence frequently occur in several cities in Indonesia.

• Smart Media Journal
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• v.12 no.3
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• pp.77-84
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• 2023

Forest fires are representative natural disasters resulting from dramatic global climate change in these modern times. When forest formation is insufficient due to forest damage caused by fire, secondary damages such as landslides occur during the winter thawing period and heavy rains. In most countries, only a limited area is managed as CCTV-centered monitoring systems for forest management. For the landslide prediction, markers containing 3D spatial coordinates were located on the slopes of the danger areas in advance. Then 3D mapping and angle of repose were obtained by periodic drone imaging. The recognition range and angle of view of markers were defined, and a new method for predicting signs of landslides in advance was presented in this study.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.619-620
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• 2012

This paper proposes a model of the real time monitoring system based on Ubiquitous Sensor Network (USN) for the detection and prediction of landslides. For this purpose, the real time monitoring system with tilting sensor and USN was set up and the performance was conducted. The performance was accomplished by conducting both field examinations and the experimental evaluation of the monitoring system. The results of this study show that the movements detected by the sensor module coincide with the actual displacement of field and the data measured from the sensor modules through USN transfer to the monitoring system without errors.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.106-117
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• 2021

The purpose of this study is prediction of landslide occurrence reflecting the subsurface flow characteristics within the soil layer in the future due to climate change in a large scale watershed. To do this, we considered the infinite slope stability theory to evaluate the landslide occurrence with predicted soil moisture content by SWAT model based on monitored data (rainfall-soil moisture-discharge). The correlation between the SWAT model and the monitoring data was performed using the coefficient of determination (R²) and the model's efficiency index (Nash and Sutcliffe model efficiency; NSE) and, an accuracy analysis of landslide prediction was performed using auROC (area under Receiver Operating Curve) analysis. In results comparing with the calculated discharge-soil moisture content by SWAT model vs. actual observation data, R² was 0.9 and NSE was 0.91 in discharge and, R² was 0.7 and NSE was 0.79 in soil moisture, respectively. As a result of performing infinite slope stability analysis in the area where landslides occurred in the past based on simulated data (SWAT analysis result of 0.7~0.8), AuROC showed 0.98, indicating that the suggested prediction method was resonable. Based on this, as a result of predicting the characteristics of landslide occurrence by 2050 using climate change scenario (RCP 8.5) data, it was calculated that four landslides could occur with a soil moisture content of more than 75% and rainfall over 250 mm/day during simulation. Although this study needs to be evaluated in various regions because of a case study, it was possible to determine the possibility of prediction through modeling of subsurface flow mechanism, one of the most important attributes in landslide occurrence.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.724-731
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• 2006

The purpose of this study is to estimate a landslide using the SLOPILE program from the slope reinforced by slope stability systems such as soil nailing and pile. To do this, cutting slope located at Donghae-Highway in Kwangwon-Do was considered. The behavior of slope was monitored for a long term by using instrumentation according to the reinforcement stages. The sequence of reinforcement stages was followed as pile installation, boring, soil nailing installation, anchoring and embankment. The result from this case study shows that the safety factor of slope depends on the reinforcement stage more or less.

• Economic and Environmental Geology
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• v.24 no.3
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• pp.309-318
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• 1991

Analysis for landslides was studied in framework of Chungju dam right abutment, 6.5km northeast of Chungju city. $5.5{\times}10^6m^3$ landslide materials were excavated during dam construction for safety of the Chungju dam. Geology of study area is composed mainly of meta sediments such as dolomitic limestone, quartzite and schist which are dipping toward the Nam Han river. Scanline survey of discontinuities was performed for slope stability, resistivity exploration was performed for the evaluation of potential failure plane, and direct shear strength test of rocks and soils was performed for the effect on landslide. Monitoring systems of tiltmeter, tensiometer, ground water observation hole and level monument were installed during dam construction and interpreted for the evaluation of slope instability. Kinematic solution of the geological structure and evaluation using safety factor for slope may prove the failure of the slope.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.365-374
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• 2022

Mining activity causes environmental pollution and geological hazards such as ground subsidence or landslide of which continuous monitoring is necessary. In this study, the activity on the Fushun West Open-Pit Mine (FWOPM), one of the largest open-pit coal mines in Asia located in Fushun, Liaoning Province, China, was analyzed by using a time-series Sentinel-1 InSAR coherence dataset. By using the difference between the two Digital Elevation Models (DEM) of the area, it was possible to confirm that there was a stockpiling activity in the western area of the FWOPM while excavation activity in the eastern area. By using RGB composite images using the yearly-averaged InSAR coherence images, the activity of the mine was confirmed by period, which was confirmed by Google Earth optical images. As a result, it was possible to confirm three landslides and the related activities on the northwest slope and the dumping activity on the west slope of FWOPM.

• Journal of Korean Society of societal Security
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• v.2 no.2
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• pp.85-90
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• 2009

In recent days, climatic change cause abnormal weather all over the world and we have a great loss of life and property every year. In Korea, we suffer from landslide problem because large regions of Korea Peninsula are composed of mountain. In order to detect rapidly and to take follow-up measures of disaster, the remote sensing is being used actively as conventional field survey has many restrictions in accessibility because of more time and man power requirement. In additions interferometric SAR is one of the techniques that have our attention because it can provide many kinds of accurate surface information without restriction of atmospheric and ground conditions by using L-band. In this study, we aimed to monitor the displacement of mountain area in Kangwondo and this results will be used for detecting landslide. Also we build the web system for detecting and analyzing the landslide.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.365-374
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• 2017

SAR (Synthetic Aperture Radar) is an effective tool for monitoring areas damaged by disasters. Full PolSAR (Polarimetric SAR) enhances SAR's capabilities by providing specific scattering mechanisms. Thus, full PolSAR data have been widely used to analyze the situation when disasters occur. To interpret full PolSAR data, model-based decomposition methods are frequently used due to its easy physical interpretation of PolSAR data and computational efficiency. However, these methods present problems. One of the key problems is the overestimation of the volume scattering component. To minimize the volume scattering component, the OA (Orientation Angle) compensation method is widely utilized. This paper shows that the effect of the OA compensation was analyzed over landslide affected areas. In this paper, the OA compensation is applied by using the OA estimated from the maximum relative Hellinger distance. We conducted an experiment using two full polarimetric ALOS/PALSAR (Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar)-2 data collected over Mocoa, Colombia which was seriously damaged by the 2017 Mocoa landslide. After OA compensation, the experimental results showed volume scattering power decreased, while the double-bounce and surface scattering power increased. Particularly, significant changes were noted in urban areas. In addition, after OA compensation, the separability of the double-bounce and surface scattering components are improved over the damaged building areas. Furthermore, changes in the OA can discriminate visually between the damaged building areas and undamaged areas. In conclusion, we demonstrated that the effect of OA compensation improved the influence of the double-bounce and surface scattering components, and OA changes can be useful for detecting damaged building areas.