• Title, Summary, Keyword: Landslide

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Landslide Stability Analysis and Prediction Modeling with Landslide Occurrences on KOMPSAT EOC Imagery

  • Chi, Kwang-Hoon;Lee, Ki-Won;Park, No-Wook
    • Korean Journal of Remote Sensing
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    • v.18 no.1
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    • pp.1-12
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    • 2002
  • Landslide prediction modeling has been regarded as one of the important environmental applications in GIS. While, landslide stability in a certain area as collateral process for prediction modeling can be characterized by DEM-based hydrological features such as flow-direction, flow-accumulation, flow-length, wetness index, and so forth. In this study, Slope-Area plot methodology followed by stability index mapping with these hydrological variables is firstly performed for stability analysis with actual landslide occurrences at Boeun area, Korea, and then Landslide prediction modeling based on likelihood ratio model for landslide potential mapping is carried out; in addition, KOMPSAT EOC imagery is used to detect the locations and scalped scale of Landslide occurrences. These two tasks are independently processed for preparation of unbiased criteria, and then results of those are qualitatively compared. As results of this case study, land stability analysis based on DEM-based hydrological variables directly reflects terrain characteristics; however, the results in the form of land stability map by landslide prediction model are not fully matched with those of hydrologic landslide analysis due to the heuristic scheme based on location of existed landslide occurrences within prediction approach, especially zones of not-investigated occurrences. Therefore, it is expected that the resets on the space-robustness of landslide prediction models in conjunction with DEM-based landslide stability analysis can be effectively utilized to search out unrevealed or hidden landslide occurrences.

DETECTING LANDSLIDE LOCATION USING KOMSAT 1AND IT'S USING LANDSLIDE-SUSCEPTIBILITY MAPPING

  • Lee, Sa-Ro;Lee, Moung-Jin
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.840-843
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    • 2006
  • The aim of this study was to detect landslide using satellite image and apply the landslide to probabilistic landslide-susceptibility mapping at Gangneung area, Korea using a Geographic Information System (GIS). Landslide locations were identified by change detection technique of KOMSAT-1 (Korea Multipurpose Satellite) EOC (Electro Optical Camera) images and checked in field. For landslide-susceptibility mapping, maps of the topography, geology, soil, forest, lineaments, and land cover were constructed from the spatial data sets. Then, the sixteen factors that influence landslide occurrence were extracted from the database. Using the factors and detected landslide, the relationships were calculated using frequency ratio, one of the probabilistic model. Then, landslide-susceptibility map was drawn using the frequency ration and finally, the map was verified by comparing with existing landslide locations. As the verification result, the prediction accuracy showed 86.76%. The landslide-susceptibility map can be used to reduce hazards associated with landslides and to land cover planning.

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Landslide Risk Assessment Using HyGIS-Landslide (HyGIS-Landslide를 이용한 산사태 발생 위험도 평가)

  • Park, Jung-Sool;Kim, Kyung-Tak;Choi, Yun-Seok
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.1
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    • pp.119-132
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    • 2012
  • Recently, forest soil sediment disasters resulting from locally concentrated heavy rainfall have been occurring frequently in steep slope areas. The importance of landslide hazard map is emerging to analyze landslide vulnerable areas. This study was carried out to develop HyGIS-Landslide based on Hydro Geographic Information System in order to analyze forest soil sediment disaster in the mountainous river basin. HyGIS-Landslide is one of HyGIS components designed by considering the landslide hazard criteria of Korea Forest Service. It could show the distribution of landslide hazard areas after calculating the spatial data. In this system, the user could reset the weight of hazard criteria to reflect the regional characteristics of the landslide area. This component provided user interface that could make the latest spatial data available in the area of interest. HyGIS-Landslide could be applied to the surveyor's compensation score and it was possible to reflect the landslide risk exactly through it. Also, it could be used in topographic analysis techniques providing spatial analysis and making topographical parameters in HyGIS. Finally the accuracy could be acquired by calculating the landslide hazard grade map and landslide mapping data. This study applied HyGIS-Landslide at the Gangwon-do province sample site. As a result, HyGIS-Landslide could be applied to a decision support system searching for mountainous disaster risk region; it could be classified more effectively by re-weighting the landslide hazard criteria.

Landslide susceptibility mapping using Logistic Regression and Fuzzy Set model at the Boeun Area, Korea (로지스틱 회귀분석과 퍼지 기법을 이용한 산사태 취약성 지도작성: 보은군을 대상으로)

  • Al-Mamun, Al-Mamun;JANG, Dong-Ho
    • Journal of The Geomorphological Association of Korea
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    • v.23 no.2
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    • pp.109-125
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    • 2016
  • This study aims to identify the landslide susceptible zones of Boeun area and provide reliable landslide susceptibility maps by applying different modeling methods. Aerial photographs and field survey on the Boeun area identified landslide inventory map that consists of 388 landslide locations. A total ofseven landslide causative factors (elevation, slope angle, slope aspect, geology, soil, forest and land-use) were extracted from the database and then converted into raster. Landslide causative factors were provided to investigate about the spatial relationship between each factor and landslide occurrence by using fuzzy set and logistic regression model. Fuzzy membership value and logistic regression coefficient were employed to determine each factor's rating for landslide susceptibility mapping. Then, the landslide susceptibility maps were compared and validated by cross validation technique. In the cross validation process, 50% of observed landslides were selected randomly by Excel and two success rate curves (SRC) were generated for each landslide susceptibility map. The result demonstrates the 84.34% and 83.29% accuracy ratio for logistic regression model and fuzzy set model respectively. It means that both models were very reliable and reasonable methods for landslide susceptibility analysis.

Development of Landslide Hazard Map Using Environmental Information System: Case on the Gyeongsangbuk-do Province (환경정보시스템을 이용한 산사태 발생위험 예측도 작성: 경상북도를 중심으로)

  • Bae, Min-Ki;Jung, Kyu-Won;Park, Sang-Jun
    • Journal of Environmental Science International
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    • v.18 no.11
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    • pp.1189-1197
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    • 2009
  • The purpose of this research was develop tailored landslide hazard assessment table (LHAT) in Gyeongsangbuk-do Province and propose building strategies on environmental information system to estimate landslide hazard area according to LHAT. To accomplish this purpose, this research investigated factors occurring landslide at 172 landslide occurred sites in 23 city and county of Gyeongsangbuk-do Province and analyzed what factors effected landslide occurrence quantity using the multiple statistics of quantification method(I). The results of analysis, factors affecting landslide occurrence quantity were shown in order of slope position, slope length, bedrock, aspect, forest age, slope form and slope. And results of the development of LHAT for predict mapping of landslide-susceptible area in Gyeongsangbuk-do Province, total score range was divided that 107 under is stable area(IV class), 107~176 is area with little susceptibility to landslide(III class), 177~246 is area with moderate susceptibility to landslide(II class), above 247 area with severe susceptibility to landslide(I class). According to LHAT, this research built landslide attribute database and made 7 digital theme maps at mountainous area located in Goryeong Gun, Seongju-Gun, and Kimcheon-City. The results of prediction on degree of landslide hazard using environmental information system, area with little susceptibility to landslide(III class) occupied 65.56% and severe susceptibility to landslide(I class) occupied 0.51%.

Recognition of Landslide Activites in Bonggye Area Using Isopleth Mapping Techniques (Isopleth Mapping기법에 의한 봉계지역의 Landslide 활동성 연구)

  • 김윤종;유일현
    • Korean Journal of Remote Sensing
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    • v.5 no.2
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    • pp.123-131
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    • 1989
  • The inventory maps of landslide deposits show where landsliding has occured in the past, and serve as a general guide to slope stability. Isopleth maps derived from those inventory maps, generalized and quantify the areal distribution of landslide deposits in contour form. Isopleth maps can provide an economical means for the recognition of landslide activity and assessing the degree of landslide hazard in a large area, especially rural areas. Isopleth maps of Bonggye area, where the degree of landslide hamedial efforts during the period of 1954-1971.

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Landslide prediction, monitoring and early warning: a concise review of state-of-the-art

  • Chae, Byung-Gon;Park, Hyuck-Jin;Catani, Filippo;Simoni, Alessandro;Berti, Matteo
    • Geosciences Journal
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    • v.21 no.6
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    • pp.1033-1070
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    • 2017
  • Landslide is one of the repeated geological hazards during rainy season, which causes fatalities, damage to property and economic losses in Korea. Landslides are responsible for at least 17% of all fatalities from natural hazards worldwide, and nearly 25% of annual casualties caused by natural hazards in Korea. Due to global climate change, the frequency of landslide occurrence has been increased and subsequently, the losses and damages associated with landslides also have been increased. Therefore, accurate prediction of landslide occurrence, and monitoring and early warning for ground movements are very important tasks to reduce the damages and losses caused by landslides. Various studies on landslide prediction and reduction in landslide damage have been performed and consequently, much of the recent progress has been in these areas. In particular, the application of information and geospatial technologies such as remote sensing and geographic information systems (GIS) has greatly contributed to landslide hazard assessment studies over recent years. In this paper, the recent advances and the state-of-the-art in the essential components of the landslide hazard assessment, such as landslide susceptibility analysis, runout modeling, landslide monitoring and early warning, were reviewed. Especially, this paper focused on the evaluation of the landslide susceptibility using probabilistic approach and physically based method, runout evaluation using volume based model and dynamic model, in situ ground based monitoring techniques, remote sensing techniques for landslide monitoring, and landslide early warning using rainfall and physical thresholds.

A Comparative Analysis of Landslide Susceptibility Assessment by Using Global and Spatial Regression Methods in Inje Area, Korea

  • Park, Soyoung;Kim, Jinsoo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.6
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    • pp.579-587
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    • 2015
  • Landslides are major natural geological hazards that result in a large amount of property damage each year, with both direct and indirect costs. Many researchers have produced landslide susceptibility maps using various techniques over the last few decades. This paper presents the landslide susceptibility results from the geographically weighted regression model using remote sensing and geographic information system data for landslide susceptibility in the Inje area of South Korea. Landslide locations were identified from aerial photographs. The eleven landslide-related factors were calculated and extracted from the spatial database and used to analyze landslide susceptibility. Compared with the global logistic regression model, the Akaike Information Criteria was improved by 109.12, the adjusted R-squared was improved from 0.165 to 0.304, and the Moran’s I index of this analysis was improved from 0.4258 to 0.0553. The comparisons of susceptibility obtained from the models show that geographically weighted regression has higher predictive performance.

LAND SLIDE DISPLACEMENT DETECTION USING TIME SERIES DIGITAL SURFACE MODEL ACQUIRED BY A TERRESTRIAL LASER SCANNER

  • Jeong, Jong-Hyeok;Takagi, Masataka
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.567-569
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    • 2006
  • Recently, the terrestrial laser scanner is considered as useful measurement equipment for acquiring a three-dimensional data. In this study, a terrestrial laser scanner which has +/- 2.5cm accuracy is examined whether the terrestrial laser scanner is reliable to present the tendency of landslide movement. The test area is covered by protection blocks, and they are being moved by landslide movement. Landslide movement was detected by measuring the movement of protection blocks. Totally three scenes of test area were acquired during 2004 and 2006. The three scenes of the protection blocks were registered in global coordinate system, then the landslide movement was investigated. The landslide movement detected in the three scenes was evaluated by comparing with landslide movement measured by a total station. Although the measurement accuracy of landslide using the terrestrial laser scanner was worse than the total station, the scanning data showed the tendency of landslide movement of the test area.

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An Estimation of Landslide's Vulnerability by Analysis of Static Natural Environmental Factors with GIS (GIS를 이용한 정적 자연환경인자의 분석에 의한 산사태 취약성 평가)

  • Yang, In-Tae
    • 한국지형공간정보학회:학술대회논문집
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    • pp.61-72
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    • 2005
  • The landslide risk assessment process consists of hazard risk assessment and vulnerability analysis. landslide hazard risk is location dependent. Therefore, maps and spatial technologies such as GIS are very important components of the risk assessment process. This paper discusses the advantages of using GIS technology in the risk assessment process and illustrates the benefits through case studies of live projects undertaken. The goal of this study is to generate a map of landslide vulnerability map by analysis of static natural factors with GIS. A simple and efficient algorithm is proposed to generate a landslide potentialities map from DEM and existing maps. The categories of controlling factors for landslides, aspect of slope, soil, vegetation are defined. The weight values for landslide potentialities are calculated from AHP method. Slope and slope-direction are extracted from DEM, and soil informations are extracted from digital soil map. Also, vegetation informations are extracted from digital vegetation map. Finally, as overlaying, landslide potentialities map is made out, and it is verified with landslide place.

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