• The Journal of Engineering Geology
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• v.34 no.1
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• pp.51-65
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• 2024

Landslides are natural disasters that causes significant property damage worldwide every year. In Korea, damage due to landslides is increasing owing to the effects of climate change, and it is important to identify the factors that increase the prevalence of landslides in order to reduce the damage they cause. Therefore, this study used a random forest model to analyze the importance of 14 factors in influencing landslide damage in a specific area of Chungju, Chungcheongbuk-do province, Korea. The random forest model performed accurately with an AUC of 0.87 and the most-important factors were ranked in the order of aspect, slope, distance to valley, and elevation, suggesting that topographic factors such as aspect and slope more greatly influence landslide damage than geological or soil factors such as rock type and soil thickness. The results of this study are expected to provide a basis for mapping and predicting landslide damage, and for research focused on reducing landslide damage.

• Journal of Conservation Science
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• v.34 no.5
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• pp.333-343
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• 2018

This study was conducted to evaluate the conservation environment by monitoring temperature and humidity for two years and mapping the remaining pigments of mural paintings to diagnose the conservation state of mural paintings of Royal Tombs in Neungsan-ri. We evaluated the characteristics of condensation in the tomb. Compared with the results of a 2008 survey, we conducted state change of mural paintings in the tomb. The temperature in the main room, which has an annual average soil temperature distribution at 5 m depth in Korea, is maintained at $13{\sim}18^{\circ}C$. The temperature range of the main room was between less than $0.1^{\circ}C$ to $0.5^{\circ}C$, and the diurnal variation of temperature between summer (June to September) and winter (December to January) is the greatest. Condensation is more concentrated in the summer because the outdoor air was typically at higher temperatures than the main room inflows in the tomb. Mapping the remaining pigment composition and particle distribution of mural paintings showed that it was in the range of 36.72~39.53% of the wall area. The pigment range was confirmed to be the same as it was in 2008, through ultraviolet fluorescence reaction and infrared ray investigation. Therefore, the underground environment that receives dew condensation in the summer has been stable since 2008. However, continuous monitoring is needed because the deterioration of mural painting proceeds considerably after excavation and only a small percentage of the pigments survive.

• Geomechanics and Engineering
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• v.10 no.4
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• pp.527-546
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• 2016

This paper discusses improvements of compressibility, permeability, static and liquefaction strengths of in-situ soils by grouting. Both field testing and laboratory evaluation of the on-site samples were conducted. The improvement of soils was influenced by two main factors, i.e., the grout materials and the injection mechanisms introduced by the field grouting. On-site grout mapping revealed the major mechanism was fracturing accompanied with some permeation at deeper zones of sandy soils, where long-gel time suspension grout and solution grout were applied. The study found the compressibility and swelling potential of CL soils at a 0.5 m distance to grout hole could be reduced by 25% and 50%, respectively, due to the grouting. The effect on hydraulic conductivity of the CL soils appeared insignificant. The grouting slightly improved the cohesion of the CL soils by 10~15 kPa, and the friction angle appeared unaffected. The grouting had also improved the cohesion of the on-site SM soils by 10~90 kPa, while influences on the friction angle of soils were uncertain. Liquefaction resistances could be enhanced for the sandy soils within a 2~3 m extent to the grout hole. Average improvements of 40% and 20% on the liquefaction resistance were achievable for the sandy soils for earthquake magnitudes of 6 and ${\geq}7.5$, respectively, by the grouting.

• Environmental Engineering Research
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• v.23 no.1
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• pp.84-91
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• 2018

The present study deals with the management of groundwater resources of an important agriculture track of north-western part of Saudi Arabia. Due to strategic importance of the area efforts have been made to estimate aquifer proneness to attenuate contamination. This includes determining hydrodynamic behavior of the groundwater system. The important parameters of any vulnerability model are geological formations in the region, depth to water levels, soil, rainfall, topography, vadose zone, the drainage network and hydraulic conductivity, land use, hydrochemical data, water discharge, etc. All these parameters have greater control and helps determining response of groundwater system to a possible contaminant threat. A widely used DRASTIC model helps integrate these data layers to estimate vulnerability indices using GIS environment. DRASTIC parameters were assigned appropriate ratings depending upon existing data range and a constant weight factor. Further, land-use pattern map of study area was integrated with vulnerability map to produce pollution risk map. A comparison of DRASTIC model was done with GOD and AVI vulnerability models. Model validation was done with $NO_3$, $SO_4$ and Cl concentrations. These maps help to assess the zones of potential risk of contamination to the groundwater resources.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.357-364
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• 2017

The purpose of the study is to develop and validate landslide susceptibility map of Bhotang village development committee, Nepal using FR (Frequency Ration) and SI (Statistical Index) methods. For the purpose, firstly, a landslide inventory map was constructed based on mainly high resolution satellite images available in Google Earth Pro, and rest fieldwork as verification. Secondly, ten conditioning factors of landslide occurrence, namely: altitude, slope, aspect, mean topographic wetness index, landcover, normalized difference vegetation index, dominant soil, distance to river, distance to lineaments and rainfall, were derived and used for the development of landslide susceptibility map in GIS (Geographic Information System) environment. The landslide inventory of total 116 landslides was divided randomly such that 70% were used for training and remaining 30% for validating result by receiver operating characteristics curve analysis. The area under the curve were found to be greater than 0.7 indicating an acceptable susceptibility maps obtained using FR and SI methods in GIS for hilly region of Nepal.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.87-94
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• 2012

This study is to evaluate flood inundation and to recommend measures of damage reduction on sediment by concentrated torrential rainfall at Gonjiamcheon Watershed (183.4 $km^2$). Firstly, the SWAT (Soil and Water Assessment Tool) was simulated streamflow and sediment at upstream. Then, we produced a map of floodplain boundary by using HEC-RAS (Hydrologic Engineering Centers River Analysis System) at downstream. The SWAT model was calibrated with 2 years (2008~2009) daily streamflow and validated for another years (2010~2011. 7. 31). The SWAT model was simulated with 3 years (2008~2010) by monthly water quality (Sediment) at Gonjiamcheon water quality station. The streamflow and sediment from SWAT model were input as boundary conditions to HEC-RAS. The results of HEC-RAS indicated that mapping of floodplain boundary was Jiwol and Jiwol 2 district. Additionally, inundation area and depth were assessed and applied BMPs scenario for managing the sediment yield.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.294-297
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• 2004

The purpose of this study was to develop landslide susceptibility analysis techniques using artificial neural networks and then to apply these to the selected study area of Janghung in Korea. We aimed to verify the effect of data selection on training sites. Landslide locations were identified from interpretation of satellite images and field survey data, and a spatial database of the topography, soil, forest, and land use was constructed. Thirteen landslide-related factors were extracted from the spatial database. Using these factors, landslide susceptibility was analyzed using an artificial neural network. The weights of each factor were determined by the back-propagation training method. Five different training datasets were applied to analyze and verify the effect of training. Then, the landslide susceptibility indices were calculated using the trained back-propagation weights and susceptibility maps were constructed from Geographic Information System (GIS) data for the five cases. The results of the landslide susceptibility maps were verified and compared using landslide location data. GIS data were used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool to analyze landslide susceptibility.

• Spatial Information Research
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• v.6 no.1
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• pp.25-33
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• 1998

The study region encompasses about 5,900$km^2$ including the topographic maps of Kimhae, Pusan, Miryang, Yangsan, Panguhjin, Tonggok, Uhnyang, Ulsan, Youngchon, Kyongju, Pulguksa, and Kampo, all at a scale of 1:50,000. The paper discusses how to have prepared the four thematic maps, landslide and unstable slope distribution map, slope classification amp, soil classification map, and lineament density map. Using all the above maps and GIS, the relative slope-stability map for the study regiun was produced at a scale of 1:100,000 ; the map can be utilized for the regional land-use planning in the study region.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.2 s.14
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• pp.93-100
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• 1999

Forest fires have been threats to natural resources, endangered species, properties and even to human lives. Efficient management of forest fires requires a complete understanding of the environmental and human related activities, as well as complicate spatial relationships among them. A geo-spatial information system(GSIS) is an appropriate method of being able to mapping and to analyze the spatial data for forest fires. Therefore, this study is to provide and classify the terrain, vegetation, life environment soil and geology factors, and to analyze spatial distribution for forest fire areas by applying the GSIS and the Remote Sensing technology. On the other hands, causes of increasing numbers of forest fires being occurred after In were assessed by comparing the normalized difference vegetation index((NDVI).

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.77-82
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• 2003

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural network and to apply the developed techniques to the study area of janghung in Korea. Landslide locations were identified in the study area from interpretation of satellite image and field survey data, and a spatial database of the topography, soil, forest and land use were consturced. The 13 landslide-related factors were extracted from the spatial database. Using those factors, landslide susceptibility was analyzed by artificial neural network methods, and the susceptibility map was made with a e15 program. For this, the weights of each factor were determinated in 5 cases by the backpropagation method, which is a type of artificial neural network method. Then the landslide susceptibility indexes were calculated using the weights and the susceptibility maps were made with a GIS to the 5 cases. A GIS was used to efficiently analyze the vast amount of data, and an artificial neural network was turned out be an effective tool to analyze the landslide susceptibility.