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Ananta Man Singh Pradhan,김윤태 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.6
Soil thickness is a major parameter to better understand slope stability, surface erosion, groundwater storage, and vegetation growth. In this study, the main focus is the development and application of a relative relief (RR)-based spatial soil thickness model. Intensive field works were also carried out to gather ground-truthing soil thickness data using traditional drilling and excavation methods. The spatial distribution of soil thickness obtained from the RR model was validated with the results of the field measurements, and compared with the predictions derived from S and multiple linear regression (MLR) models, which are already known in the literature. In this study, we tested how raster resolutions (5, 10, 20, 30, 50, 60 and 90 m) influence the spatial prediction of soil thickness. Based on the comparison between the predicted soil thickness and the measured soil thickness, a map of 10 m resolution contributed reasonable delineation of soil thickness over the study area. A comparison of the predicted results was performed using the agreement coefficient (AC) which showed that the RR model has a better predictive ability (AC = 0.970) than the S (AC = 0.945) and MLR (AC = 0.710) soil thickness models. The results indicate that an adjustment to the soil thickness and spatial resolution can significantly improve the modelling efficiency.
GIS-based landslide susceptibility model considering effective contributing area for drainage time
Pradhan, Ananta Man Singh,Kim, Yun-Tae Informa UK (TaylorFrancis) 2018 Geocarto international Vol.33 No.8
<P>This study employed GIS modelling to ascertain landslide susceptibility on Mt. Umyeon, south of Seoul, South Korea. In this study, an effective contributing area (ECA) for certain drainage time was purposed as a temporal causative factor and then used for modelling in combination with spatial causative factors such as elevation, slope, plan curvature, drainage proximity, forest type, soil type and geology. Landslide inventory map of 163 landslide locations was prepared using aerial photographic interpretation and field verifications after that digitized using GIS environment in 1:5000 scale. A presence-only-based maximum entropy model was used to establish and analyse the relationship between landslides and causative factors. Before final modelling, a jackknife test was performed to measure the variable contributions, which showed that the slope was the most significant spatial causative factor, and ECA with a drainage time of 12h was the most significant temporal causative factor. The performances of the final models, with and without significant ECA, were assessed by plotting a receiver operating characteristic curve to be 75.5 and 81.2%, respectively.</P>
( Ananta Man Singh Pradhan ),( Yun-tae Kim ),( Ji-sung Lee ) 대한지질공학회 2019 대한지질공학회 학술발표회논문집 Vol.2019 No.2
Rainfall-induced shallow landslides are common in many mountainous countries. Highly concentrated precipitation triggers landslides and debris flows in worldwide. Every year, several flow-type shallow slides occur in Busan, South Korea during heavy rainfall. To reduce and prevent associated damage, we developed a matrix-based approach of rainfall threshold and landslide susceptibility. This study collects landslide inventories which consist of information of 260 landslide location, 35 landslide event times, and corresponding rainfall intensities and durations. An error ellipse based rainfall threshold warning levels were established using rainfall intensities and durations associated with 35 historical slides, and categorised as null (< 5%), watch (5-20%), attention (20-50%), and alarm ( > 50%). We used a back propagation deep nerual network machinelearning algorithm to explore the effects of 14 causative factors on flow type slide distribution. The area under the curve was used to assess accuracy, and accuracy was found to be 89.12%. The derived rainfall threshold warning levels were assigned in rows and the susceptibility classes were used in columns of the matrix. The combined result represents the flow type slide hazards to rainfall threshold warning levels with a varying likelihood to shallow slide initiation. The results aim to raise awareness towards landslide hazards and to support regional decision for the land-use planning.