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Pradhan B.,Institute for Cartography | Lee S.,Korea Institute of Geoscience and Mineral Resources
Environmental Modelling and Software | Year: 2010

Data collection for landslide susceptibility modeling is often an inhibitive activity. This is one reason why for quite some time landslides have been described and modelled on the basis of spatially distributed values of landslide-related attributes. This paper presents landslide susceptibility analysis in the Klang Valley area, Malaysia, using back-propagation artificial neural network model. A landslide inventory map with a total of 398 landslide locations was constructed using the data from various sources. Out of 398 landslide locations, 318 (80%) of the data taken before the year 2004 was used for training the neural network model and the remaining 80 (20%) locations (post-2004 events) were used for the accuracy assessment purpose. Topographical, geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. Eleven landslide occurrence related factors were selected as: slope angle, slope aspect, curvature, altitude, distance to roads, distance to rivers, lithology, distance to faults, soil type, landcover and the normalized difference vegetation index value. For calculating the weight of the relative importance of each factor to the landslide occurrence, an artificial neural network method was developed. Each thematic layer's weight was determined by the back-propagation training method and landslide susceptibility indices (LSI) were calculated using the trained back-propagation weights. To assess the factor effects, the weights were calculated three times, using all 11 factors in the first case, then recalculating after removal of those 4 factors that had the smallest weights, and thirdly after removal of the remaining 3 least influential factors. The effect of weights in landslide susceptibility was verified using the landslide location data. It is revealed that all factors have relatively positive effects on the landslide susceptibility maps in the study. The validation results showed sufficient agreement between the computed susceptibility maps and the existing data on landslide areas. The distribution of landslide susceptibility zones derived from ANN shows similar trends as those obtained by applying in GIS-based susceptibility procedures by the same authors (using the frequency ratio and logistic regression method) and indicates that ANN results are better than the earlier method. Among the three cases, the best accuracy (94%) was obtained in the case of the 7 factors weight, whereas 11 factors based weight showed the worst accuracy (91%). © 2009 Elsevier Ltd. All rights reserved.

Ahn J.S.,Korea Institute of Geoscience and Mineral Resources
Environmental Geochemistry and Health | Year: 2012

Bedrock groundwaters in Geumsan County, Korea, were surveyed to investigate the distribution and geochemical behaviors of arsenic and fluoride, mobilized through geogenic processes. The concentrations were enriched up to 113 μg/L for arsenic and 7.54 mg/L for fluoride, and 16% of 150 samples exceeded World Health Organization drinking water guidelines for each element. Simple Ca-HCO 3 groundwater types and positive correlations with pH, Ca, SO 4, and HCO 3 were characteristics of high (>10 μg/L) As groundwaters. The oxidation reaction of sulfide minerals in metasedimentary rocks and locally mineralized zones seems to be ultimately responsible for the existence of arsenic in groundwater. Desorption process under high pH conditions may also control the arsenic mobility in the study area. High (>1.5 mg/L) F groundwaters were found in the Na-HCO 3 type and with greater depth. Fluoride seemed to be enriched by deep groundwater interaction with granitic rocks, and continuous supply to shallow Ca-HCO 3-type groundwater kept the concentration high. In the study area, drinking water management should include periodic As and F monitoring in groundwater. © 2011 Springer Science+Business Media B.V.

Jeong S.W.,Korea Institute of Geoscience and Mineral Resources
Engineering Geology | Year: 2013

Viscosity is generally recognized as an indicator of landslide mobilization. Viscous behavior at relatively low (high) shear rates is an important predictor of the motion of slow- (fast)-moving landslides. The viscosity in a modified Bingham model at low and high shear rates was examined. The viscous characteristics are primarily dependent on the physico-chemical properties of the materials in question (e.g., grain size, mineralogy, salinity). In this context, the viscous characteristics of low- to medium-activity and high-activity clays (bentonite with different salinities) were compared. Empirical relationships exist between the liquidity index and the plastic viscosity regardless of the mineralogical composition. This study also demonstrated a positive relationship between the liquidity index and the viscosity in a modified Bingham model with n=. 1. The results showed that low- to medium-activity and high-activity clays fall into a similar range for fine-grained sediments mixed with salt water (30. g/L). However, an effect of salinity was evident when using high-activity clays mixed with fresh water. Modified Bingham model is a useful and powerful tool for describing pre- and post-yield viscosity in engineering practice. By correlating the geotechnical and rheological properties of fine-grained sediments, index properties can help to estimate the appropriate values for the rheological parameters of these soils. © 2012 Elsevier B.V.

Luo J.,Northwestern University | Jang H.D.,Northwestern University | Jang H.D.,Korea Institute of Geoscience and Mineral Resources | Huang J.,Northwestern University
ACS Nano | Year: 2013

Graphene is considered a promising ultracapacitor material toward high power and energy density because of its high conductivity and high surface area without pore tortuosity. However, the two-dimensional (2D) sheets tend to aggregate during the electrode fabrication process and align perpendicular to the flow direction of electrons and ions, which can reduce the available surface area and limit the electron and ion transport. This makes it hard to achieve scalable device performance as the loading level of the active material increases. Here, we report a strategy to solve these problems by transforming the 2D graphene sheet into a crumpled paper ball structure. Compared to flat or wrinkled sheets, the crumpled graphene balls can deliver much higher specific capacitance and better rate performance. More importantly, devices made with crumpled graphene balls are significantly less dependent on the electrode mass loading. Performance of graphene-based ultracapacitors can be further enhanced by using flat graphene sheets as the binder for the crumpled graphene balls, thus eliminating the need for less active binder materials. © 2013 American Chemical Society.

Lee S.,Korea Institute of Geoscience and Mineral Resources
Environmental Earth Sciences | Year: 2013

The purpose of this study is to detect landslide locations from satellite images and use them for landslide susceptibility mapping in the Sagimakri area, Korea using a geographic information system and a data-driven weight of evidence model. The landslide location areas were identified from Korea multipurpose satellite images by means of change detection technique and further verified by extensive field survey. Subsequently, landslide locations were randomly selected in a 70:30 ratio for training and validation of the model, respectively. A spatial database was constructed, which is composed of topography, forest, soil, and land cover, and 14 landslide-related factors were extracted from the database. The relationships between the detected landslide locations and the factors were identified and quantified by weights of evidence model. Tests of conditional independence were performed for the selection of factors, allowing five different combinations of factors to be analyzed. The relationships were used as the contrast values, W + and W - of factor ratings in the overlay analysis to create landslide susceptibility indexes and maps. The results of the analysis were validated by comparison with known landslide locations that were not used directly in the analysis. © 2013 Springer-Verlag Berlin Heidelberg.

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