• Journal of Korean Society of Forest Science
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• v.63 no.1
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• pp.51-60
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• 1984

Analysing the reports of disaster-related, average annual death of lives due to the meteorological disasters amounted to be 250, of which about 90 were due to landslide. According to the last 10-year reports, the average area of landslide occurred reaches 275 hectares per year in Korea. The total cost for rehabilitation could annually require more than about 2 billion Won (about US$ 2.5 million). The basic countermeasure policy against such heavy disasters should be definitely taken on prevention rather than rehabilitation after being damaged. However, prevention countermeasures against landslide-related disasters have not been strengthened in Korea although being important. Areas of high landslide hazard must be designated with increase in number from current 10 (35 cities and counties) to 17 (68 cities and counties included : Table 3). Number of regional Erosion Control Stations taking full charge of rehabilitating works on the damaged land resulted from landslide disaster has to increase from currently 15 stations to 25. The stone buttressed terrace structures on the hillside slopes, being typical erosion control measures in Korea have been recently recognized as one of the most effective rehabilitation measures for the land damaged by landslides.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.3
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• pp.23-29
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• 2015

Due to the characteristics of landslide disasters including debris flow, the rapid speed to downward and difficulty to respond or evacuate from them, it is imperative to identify their potential hazards and prepare the reduction plans. However, the current landslide hazards generated by a variety of methods has been raised its accuracy because of the complexity of input data and their analyses, and the simplification of the landslide model. The main objective of this study is, therefore, to evaluate the preliminary landslide hazard based on the identification of geomorphological features. Especially, two methodologies based on the statistics of the directional data, Vector dispersion and Planarity analyses, are used to find some relationships between geomorphological characteristics and the landslide hazard. Results show that both methods well discriminate geomorphological features between stable and unstable domains in the landslide areas. Geomorphological features are closely related to the landslide hazard and it is imperative to maximize their characteristics by adapting multiple models rather than individual model only. In conclusions, the mechanism of landslide is not determined solely by a simple cause but the complex natural phenomenon caused by the interactions of the numerous factors and it is of primary importance to require additional researches for the outbreaking mechanism that are based on various methodologies.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.97-97
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• 2023

최근 재해분야에서 인공신경망(ANN), 기계학습(ML), 딥러닝(DL) 등 AI 기술이 활용성이 점차 증가하고 있으며, 센싱정보와 연계한 시설물 안전관리, 원격탐사와 연계한 재해감시(녹조, 산사태, 산불 등), 수문시계열(수위, 유량 등) 예측, 레이더·위성강수 자료의 보정과 예측, 상하수도 관망누수예측 등 다양한 분야에서 AI 기술이 적용되고 그 활용성이 검증된 바 있다. 본 연구에서는 ML, DL, 물리기반신경망(Pysics-informed Neural Networks, PINNs)을 이용한 다양한 재해분석 사례를 소개하고, 그 활용성과 한계에 대해서 논의하고자 한다. 주요사례로는 (1) SAR영상과 기계학습을 이용한 재해피해지역(울진 산불) 감지, (2) 국가 디지털 정보를 이용한 산사태 위험지역 판별(인제 산사태) (3) 기계학습 및 딥러닝 기법을 이용한 위성강수 자료의 보정·예측 및 유출해석, (4) 수리해석을 위한 수치해석분야에서의 PINNs의 적용성(1차원 Saint-Venant 식 해석) 평가 연구결과를 공유한다. 특히, 자료의 입·출력 자료만으로 학습된 인공신경망 모형 대신 지배방정식(물리방정식)을 만족하도록 강제한 PINNs의 경우, 인공신경망 모형보다 우수한 모의능력을 보여주었으며, 향후 복잡한 수리모델링 등 수치해석분야에서 그 활용가능성이 매우 높을 것으로 판단된다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.300-302
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• 2013

자연재해의 예방에 대한 인식이 화두가 되면서 최근 재해 경보 시스템을 다루는 새로운 연구들이 활발히 진행되고 있다. 제안하는 알고리듬은 영상을 통해 얻은 정보를 이용하여 산사태를 초기에 검출하는 방법이다. 기존의 검출 방법은 사람이 직접 모니터링을 해야 하기 때문에 많은 인력과 시간을 필요로 하고 접근성이나 비용문제 등의 각종 제약이 따른다. 따라서 효율적인 산사태 감지를 위해 산사태 발생 가능 지역에 비디오 기반의 감지 시스템을 통해서 자동으로 검출하는 시스템이 필요하다. 감지 시스템에서는 신뢰성 있는 재난영역의 검출이 매우 중요하다고 볼 수 있다. 본 연구는 산사태를 검출하기 위하여 먼저 블록단위의 영역 움직임 검출을 하여, 움직임 맵을 만들고 일정한 시간 간격으로 반복적으로 변하는 영역의 움직임 맵을 기록한다. 또한 움직임 방향뿐만 아니라 발생 순서를 기록하여 더욱더 정확한 움직임을 판단할 수 있다. 제안된 알고리듬은 비디오영상 실험을 통해 탐지영역의 산사태 검출이 잘 이루어짐을 확인하였다.

• Journal of Korean Society of societal Security
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• v.1 no.4
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• pp.57-64
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• 2008

Korea has been suffered from serious damages of lives and properties, due to landslides that are triggered by heavy rains in every monsoon season. This study developed the physically based landslide prediction model which consists of 3 parts, such as slope stability analysis model, groundwater flow model and soil depth model. To evaluate its applicability to the prediction of landslides, the data of actual landslides were plotted on the areas predicted on the GIS map. The matching rate of this model to the actual data was 84.8%. The relation between hydrological and landform factors and potential landslide were analyzed.

• Journal of Sensor Science and Technology
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• v.24 no.5
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• pp.291-298
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• 2015

There are many landslides occurred by typhoons and intense rainfall during the summer seasons in Korea. To predict a landslide triggering it is important to understand mechanisms and potential areas of landslides by the geological approaches. However, recent climate changes make difficult to predict landslide based on only conventional prediction methods. Therefore, the importance of a real-time monitoring of landslide using various sensors is emphasized in recent. Many researchers have studied monitoring techniques of landslides and suggested several monitoring systems which can be applicable to the natural terrain. Most sensors of landslide monitoring measure slope displacement, hydrogeologic properties of soils and rocks, changes of stress in soil and rock fractures, and rainfall amount and intensity. The measured values of each sensor are transmitted to a monitoring server in real-time. The ultimate goal of landslide monitoring is to warn landslide occurrence in advance and to reduce damages induced by landslides. This study introduces the current situation of landslide monitoring techniques in each country.

• Spatial Information Research
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• v.3 no.1
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• pp.81-90
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• 1995

Landslide data base system is necessitated to make a mid-long term master plan to prevent landslide from past landslide data and their statistical analysis. This paper emphasis on application of the efficient management system of GIS to reduce landslide disasters basis on the result of survey analysis of landslide problems. In this paper explains landslide data base system by the cause of landslide from past landslide data & application of GIS to it.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.353-356
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• 2008

최근 대규모 산림재해로 인한 산림환경 훼손 및 산림 농가의 피해는 물론 산림생태계에도 나쁜 영향을 미치고 있으며 이는 사회적으로 매우 민감한 환경문제로서 국민의 주요 관심사가 되고 있다. 본 연구에서는 울진군 전체를 대상으로 GIS 및 RS 기법을 이용하여 다양한 산사태 관련 인자들을 추출 하여 이를 기반으로 GIS 중첩 및 가중치 분석을 통하여 울진군의 산사태 발생 가능 위험지역의 분포도를 작성하고자 한다.

• Journal of Korean Society of societal Security
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• v.2 no.1
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• pp.75-80
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• 2009

The objectives of this research are to develop hazard prediction map S/W for mountain river road. This mountain river road disaster happens by debris flow, landslide, debris accumulation and this cause are locally rainfall and heavy rainfall. System is constructed to GIS base. This research app lied to Kangwondo. We developed protocol to analyze calamity danger in mountain district area and examined propriety system. Furthermore examined the DB required and expression plan for hazard map creation SW construction by mountain rivers road.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.10 no.2
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• pp.57-62
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• 1992

As population is increased, land use types are changed mountainous areas from flatland in Korea. Because natural disaster as landslides occur of life, property, and environmental damage, prediction of landslides have become increasingly important. We focus on the issue for assessment of landslides, not slope stability analysis for a simple slope site. In this study, we could know the correlations of mean, standard deviation for brightness value of imagery by aerial photo scanning. The range of brightness values and standard deviation of landslide area is 35~65 and tend to increment of value, in the every years. When evaluating large regions with past occurrence of landslides, it is possible to search for correlation of site conditions such as degree of slope, soil characteristics, vegetative cover, and rainfall conditions in aerial photo interpretation data.