• Korean Journal of Remote Sensing
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• v.5 no.1
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• pp.1-12
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• 1989

The objective of this study is to develop the application techniques, such as geometrical correction, image overlapping etc., of LANDSAT Thematic Mapper image data especially useful to the geomorphological study of tidal flats. The developed processing techniques were applied to the Kum river estuary. The results of this study are as follows. 1) According to the analysis of the distribution and topographical profiles of the tidal flats, the geomorphological characteristics of the study area seem to be different depending on their location. 2) Even though the geomorphological changes were not always observable on the satellite images, several areas of undoubtful short-term deposition could be detected on the analytical map-image which compares two different situations of tidal flats. 3) Even though a further ditailed study is necessary, the distribution and dispersal patterns of suspended materials and sea surface temperature distribution patterns due to tidal and other meteorological conditions were analyzed by LANDSAT TM channel 3 and 6.

• The Journal of Engineering Geology
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• v.14 no.2
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• pp.211-222
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• 2004

In this study, a probabilistic prediction model for debris flow occurrence was developed using a logistic regression analysis. The model can be applicable to metamorphic rocks and granite area. order to develop the prediction model, detailed field survey and laboratory soil tests were conducted both in the northern and the southern Gyeonggi province and in Sangju, Gyeongbuk province, Korea. The seven landslide triggering factors were selected by a logistic regression analysis as well as several basic statistical analyses. The seven factors consist of two topographic factors and five geological and geotechnical factors. The model assigns a weight value to each selected factor. The verification results reveal that the model has 90.74% of prediction accuracy. Therefore, it is possible to predict landslide occurrence in a probabilistic and quantitative manner.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.249-253
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• 2008

최근 국내에서 사용되고 있는 격자분포형 강우-유출 모형 $Vflo^{TM}$을 실무에 효율적으로 적용하기 위하여 매개변수값의 결정과 그 민감도를 분석하고, 중랑천 유역의 토지이용 및 지형특성을 고려한 적정 크기의 격자에 대한 연구를 수행하였다. 연구대상유역으로는 토지이용현황이 상이한 중랑천 상류(자연유역), 우이천(복합유역) 및 청계천(도시유역) 유역을 선택하였다. $2003{\sim}2006$년까지 5개 호우사상의 실측자료로부터 매개변수값의 최적화를 실시하였으며 수치모의된 결과로 부터 조도계수, 투수계수, 초기함수비 등의 매개변수에 의한 계산치의 민감도를 분석하였다. 검토결과 지표면 조도계수가 가장 예민했으며, Green-Ampt식에 적용되는 투수계수의 영향이 큰 것으로 분석되었다. 또한, 수문학적 지형특성 반영을 위한 적정 격자크기는 자연유역(중랑천 상류)과 복합유역(우이천)에서는 100과 200 m에서 관측 유출수문곡선과 대체로 일치하나, 격자크기가 300 m에서는 지형특성을 반영하지 못해 유출수문곡선이 왜곡되는 경향을 나타내어 불투수율 80% 이하인 자연 및 복합유역에서는 DEM 격자크기를 $200{\sim}300\;m$이하로 적용하는 것이 적정하다고 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.229-229
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• 2022

우리나라의 지형 특성상 국토의 약 64%가 산지 지형이며 최근 10년 기준으로 연평균 강우량의 약 51%인 651.9mm가 여름철에 집중되고 있으며, 급격한 기후변화로 인한 집중호우와 태풍에 의한 영향으로 산사태와 토석류에 의한 생활권 주변의 도로나 주택가에 많은 피해를 발생시키고 있다. 따라서 무엇보다 토석류의 피해를 줄이기 위해 재해 발생 예상지역이나 피해 정도 및 규모에 대한 예측이 중요하며 이를 위해서는 토석류 수치모의를 통해 토석류의 피해지역을 예측할 필요가 있다고 판단된다. 본 연구에서는 태풍 미탁으로 인해 토석류가 발생한 강원도 삼척시 원덕읍을 대상으로 토석류 피해지역을 해석하기 위한 연구를 수행하기 위해 2차원 토석류 해석이 가능한 FLO-2D를 적용하여 토석류의 이동, 퇴적 및 하류부 피해해석을 수행하였다. 피해지역의 수치지도와 실측자료를 활용하여 지형자료를 구축하고 FLO-2D 모형을 이용하여 토석류 발생이 하류부에 미치는 영향을 분석하고 토석류 유동특성을 분석하여 피해지역의 실측자료와 비교분석하였다. 그 결과 모형을 통해 모의된 부분과 피해면적이 유사하게 나타났다.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.202-202
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• 2011

상습침수지역 산사태위험지역 등 지형적인 여건 등으로 인해 재해가 발생할 우려가 있는 지역을 관리하기 위하여 "자연재해대책법"에 의해 지정되는 지구를 자연재해위험지구라 하며 특히 집중호우에 의한 도심지 주변 상습침수지역에 대한 체계적인 연구와 해석방법이 요구되는 실정이다. 이에 본 연구에서는 강원도 삼척시의 상습침수지역인 오십천 주변 자원동일대를 대상으로 수문학적 인자인 강우자료와 지형자료를 조사하고 도시유역 유출해석모형인 XP-SWMM을 적용하여 유출부에서의 본류수심을 고려한 재해위험지역의 하천범람과 내수침수 범위를 산정하였다. 연구지역은 GIS 프로그램인 ArcView를 이용하여 총 16개의 소유역으로 구분하고 총 노드 75개 총 링크 74개를 생성하고 분석하였다. 그 결과 2002년, 2003년의 태풍발생에 의해 침수된 지역의 특성을 하류지역의 경우 잘 반영하였으며 상류지역의 경우는 얕은 침수심을 갖으며 좀 더 넓게 침수피해가 발생하는 것으로 분석되었다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.3
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• pp.225-231
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• 2000

Soil loss by the rains has effect on natural environment. But It is difficult to find out the data that is surveyed in watershed. In this study, we combine RUSLE and GSIS, develop a program to automatically extract geo-factors to predict soil loss, and perform recurrent analysis against actual sediment load to bring out the relativity between soil loss and sediment load. Each factors need to RUSLE conducted by grid analysis. As the process to extract terrain factor became programming, the efficiency is rised.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.2
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• pp.207-214
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• 2002

Development of the shore in western sea is decreasing of silt and is threatening sea ecosystem. Large size land-reclamation work by industralization have caused weather changes and sea changes, and have generated much changes topography of sea bottom and coastline. Also, It is influencing to route of ship. In this research, line for 0 m, 2 m, and coastline of land portion is digitalized. It is divided in four block, and is analyzed severally to know the degree of coastal changes by new airport construction, new town construction, and tide embankment construction.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.299-316
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• 2019

The purpose of this study was to analyze landslide susceptibility in the Pyeongchang area using Weight of Evidence (WOE) and Evidential Belief Function (EBF) as probability models and Artificial Neural Networks (ANN) as a machine learning model in a geographic information system (GIS). This study examined the widespread shallow landslides triggered by heavy rainfall during Typhoon Ewiniar in 2006, which caused serious property damage and significant loss of life. For the landslide susceptibility mapping, 3,955 landslide occurrences were detected using aerial photographs, and environmental spatial data such as terrain, geology, soil, forest, and land use were collected and constructed in a spatial database. Seventeen factors that could affect landsliding were extracted from the spatial database. All landslides were randomly separated into two datasets, a training set (50%) and validation set (50%), to establish and validate the EBF, WOE, and ANN models. According to the validation results of the area under the curve (AUC) method, the accuracy was 74.73%, 75.03%, and 70.87% for WOE, EBF, and ANN, respectively. The EBF model had the highest accuracy. However, all models had predictive accuracy exceeding 70%, the level that is effective for landslide susceptibility mapping. These models can be applied to predict landslide susceptibility in an area where landslides have not occurred previously based on the relationships between landslide and environmental factors. This susceptibility map can help reduce landslide risk, provide guidance for policy and land use development, and save time and expense for landslide hazard prevention. In the future, more generalized models should be developed by applying landslide susceptibility mapping in various areas.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.1 s.39
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• pp.39-46
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• 2007

Most areas in Kangwon Province are mountainous and vulnerable to landslide due to the rainy season in summer and the localized torrential downpour triggered by abnormal climate. In particular, the rainfall is one of direct reasons for landslide. In accordance with the analysis of the relevance between the landslide areas and the accumulated rainfall for four months, there are severe damages of landslide to the areas having more than 1,100 mm of rainfall during three(3) months. Further, it indicates that the more the accumulated rainfall is the greater the size of landslide. These analyses show that the rainfall causes the possible and potential landslide in the vulnerable areas. And also, it means that there exist strong possibilities of landslide even in the areas of lower vulnerability if the amount of rainfall is above certain standard level. Accordingly, in this study we stored the GIS database on the causes and factors of landslide in the southern parts of Kangwon province and conducted simulations on the change of distribution of vulnerable areas by varying the rainfall conditions and by using the evaluation data of landslide vulnerability. As such a result, we found that the landslide could potentially occur if the amount of rainfall is 200 mm and more.

• Economic and Environmental Geology
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• v.43 no.4
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• pp.381-391
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• 2010

Probabilistic prediction methods of landslides which have been developed in recent can be reliable with premise of detailed survey and analysis based on deep and special knowledge. However, landslide susceptibility should also be analyzed with some reliable and simple methods by various people such as government officials and engineering geologists who do not have deep statistical knowledge at the moment of hazards. Therefore, this study suggests an evaluation chart of landslide susceptibility with high reliability drawn by accurate statistical approaches, which the chart can be understood easily and utilized for both specialists and non-specialists. The evaluation chart was developed by a quantification method based on canonical correlation analysis using the data of geology, topography, and soil property of landslides in Korea. This study analyzed field data and laboratory test results and determined influential factors and rating values of each factor. The quantification analysis result shows that slope angle has the highest significance among the factors and elevation, permeability coefficient, porosity, lithology, and dry density are important in descending order. Based on the score assigned to each evaluation factor, an evaluation chart of landslide susceptibility was developed with rating values in each class of a factor. It is possible for an analyst to identify susceptibility degree of a landslide by checking each property of an evaluation factor and calculating sum of the rating values. This result can also be used to draw landslide susceptibility maps based on GIS techniques.