Landslide Risk Assessment in Inje Using Logistic Regression Model

이환길,; 김기홍,

doi:10.7848/ksgpc.2012.30.3.313

Cited by 9 publications

(2 citation statements)

References 3 publications

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“…Risk evaluation is mainly achieved through three steps, namely landslide susceptibility evaluation, hazard evaluation, and vulnerability evaluation. All the above steps are based on probabilistic statistics, and the weight of evidence of the data-driven model is used to determine the magnitude of the likelihood of occurrence of landslides in different geological units [24][25][26]. The landslide risk evaluation system established in this study is as follows: Firstly, complete basic data collection (including grid data of environmental conditions that induce landslides, landslide list, inducing factors, and threat objects), secondly, complete the selection and weight assignment of each evaluation factor.…”

Section: Methodsmentioning

confidence: 99%

Landslide Risk Mapping Using the Weight-of-Evidence Method in the Datong Mining Area, Qinghai Province

Jiang

et al. 2023

Sustainability

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Qinghai is rich in mineral resources, but frequent and large-scale mineral mining has caused secondary damage to the fragile primary surface and produced a large number of landslide disasters. In complex geological environments such as glacier ablation and frequent tectonic movements, a complete quantitative evaluation method for landslide risk in high-cold mining areas has not yet been formed. In view of this, this article uses the field survey and remote sensing data of the Datong mining area in Qinghai Province in 2012 as the basic data. We comprehensively considered five first-level factors (13 s-level factors) including topography, lithological structure, mining engineering activities, land use, and dynamic deformation as evaluation indicators for landslide susceptibility in mining areas, and used the Topographic Wetness Index (TWI) and the Human Engineering Activity Intensity (HEAI) to quantitatively estimate the hazard of landslide according to the landslide trigger mechanism. The weight-of-evidence approach was used for landslide hazard and risk mapping under different landslide--inducing conditions. The results indicate that the extremely high-hazard areas induced by human engineering activities account for 14% of the total area, and the extremely high-risk areas account for 13% of the total area in the Datong mining area, and the area of the extremely high-risk area is large; the landslide risk assessment mapping model constructed in this study can effectively evaluate the probability of slope instability caused by rainfall and human engineering activities. The effective value of the receiver operating characteristic (ROC) curve of the sensitivity assessment model reaches 0.863, and the evaluation results are consistent with reality; using the weight-of-evidence model for landslide risk assessment is more in line with the actual situation in alpine mining areas, and is more suitable for guiding landslide risk management and disaster prevention and mitigation in mining areas.

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Section: Methodsmentioning

confidence: 99%

Landslide Risk Mapping Using the Weight-of-Evidence Method in the Datong Mining Area, Qinghai Province

Jiang

et al. 2023

Sustainability

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“…Rainfall was considered in conjunction with spatial information in previous studies 25 because it is difficult to anticipate the time and location of occurrence solely using spatial information-based analysis. Landslide susceptibility caused by rainfall differs depending on weathered soil type 26 and geomorphological characteristics 27 of shallow landslides in Italy 28 . The dynamic susceptibility map for extreme rainfall changed by performing a logistic regression analysis based on rainfall and GIS in the Deokjeok-ri and Chuncheon regions in the Republic of Korea 7 .…”

Section: Introductionmentioning

confidence: 99%

Dynamic landslide susceptibility analysis that combines rainfall period, accumulated rainfall, and geospatial information

Lee

Song

Yun

et al. 2022

Sci Rep

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Worldwide, catastrophic landslides are occurring as a result of abnormal climatic conditions. Since a landslide is caused by a combination of the triggers of rainfall and the vulnerability of spatial information, a study that can suggest a method to analyze the complex relationship between the two factors is required. In this study, the relationship between complex factors (rainfall period, accumulated rainfall, and spatial information characteristics) was designed as a system dynamics model as variables to check the possibility of occurrence of vulnerable areas according to the rainfall characteristics that change in real-time. In contrast to the current way of predicting the collapse time by analysing rainfall data, the developed model can set the precipitation period during rainfall. By setting the induced rainfall period, the researcher can then assess the susceptibility of the landslide-vulnerable area. Further, because the geospatial information features and rainfall data for the 672 h before the landslide's occurrence were combined, the results of the susceptibility analysis could be determined for each topographical characteristic according to the rainfall period and cumulative rainfall change. Third, by adjusting the General cumulative rainfall period (DG) and Inter-event time definition (IETD), the preceding rainfall period can be adjusted, and desired results can be obtained. An analysis method that can solve complex relationships can contribute to the prediction of landslide warning times and expected occurrence locations.

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A Prediction and Analysis for Functional Change of Ecosystem in South Korea

Park¹

2013

Journal of the Korean Association of Geographic Information Stu

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Rapid industrialization and economic growth have led to serious problems including reduced open space, environmental degradation, traffic congestion, and urban sprawl. These problems have been exacerbated by the absence of effective conservation and governance, and have resulted in various social conflicts. In response to these challenges, many scholar and government hope to achieve sustainable development through the establishment and management of environment-friendly planning. For this purpose, we would like to analyze functional change for ecosystem by future landuse/cover changes in South Korea. Toward this goal, we predicted land-use/cover changes from 2010 to 2060 using the future population of Statistics Korea and urban growth probability map created by logistic regression analysis and analyzed ecosystem service value using costanza's coefficient. In the case of scenario 1, ecosystem service value represented 6,783~7,092 million USD. In the case of scenario 2, ecosystem represented 6,775~7,089 million USD, 2.9~7.6 million USD decreased compared by scenario 1. This was the result of area reduction for farmland and wetland which have high environmental value relatively according to urban growth by development point of view. The results of this analysis indicate that environmentally sustainable systems and urban development must be applied to achieve sustainable development and environmental protection. Quantitative analysis of environmental values in accordance with environmental policy can help inform the decisions of policy makers and urban developers. Furthermore, forecasting urban growth based on future demand will provide more precise predictive analysis.

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Landslide Risk Assessment in Inje Using Logistic Regression Model

Cited by 9 publications

References 3 publications

Landslide Risk Mapping Using the Weight-of-Evidence Method in the Datong Mining Area, Qinghai Province

Landslide Risk Mapping Using the Weight-of-Evidence Method in the Datong Mining Area, Qinghai Province

Dynamic landslide susceptibility analysis that combines rainfall period, accumulated rainfall, and geospatial information

A Prediction and Analysis for Functional Change of Ecosystem in South Korea

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