• Economic and Environmental Geology
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• v.35 no.1
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• pp.67-74
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• 2002

The purpose of this study is to determine the weights of the factors for landslide susceptibility analysis using artificial neural network. Landslide locations were identified from interpretation of aerial photographs, field survey data, and topography. The landslide-related factors such as topographic slope, topographic curvature, soil drainage, soil effective thickness, soil texture, wood age and wood diameter were extracted from the spatial database in study area, Yongin. Using these factors, the weights of neural networks were calculated by backpropagation training algorithm and were used to determine the weight of landslide factors. Therefore, by interpreting the weights after training, the weight of each landslide factor can be ranked based on its contribution to the classification. The highest weight is topographic slope that is 5.33 and topographic curvature and soil texture are 1 and 1.17, respectively. Weight determination using backprogpagation algorithms can be used for overlay analysis of GIS so the factor that have low weight can be excluded in future analysis to save computation time.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.379-386
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• 2007

In this paper, topographic factors over 3-dimensional hills were estimated through wind tunnel tests. Topographic models having five different slopes of $5.71^{\circ}, \;11.31^{\circ},\;16.70^{\circ},\;21.80^{\circ}$, and $26.57^{\circ}$ which were based on Korean Building Code(KBC(2005), were made for wind tunnel tests. From the result of wind tunnel tests, topographic factors over 3-dimensional hills were obtained at various locations, and the ranges of topographic effects were decided. The ranges of topographic effects was whole area of the hills in the horizontal ranges and heights of 3.5 times of the hills in the vortical ranges. Topographic effects was large at the top of hills, and wind velocity was increased 57% over hill of $5.71^{\circ}$, 75% over hill of $11.31^{\circ}$, 79% over hill of $16.70^{\circ}$, 81% over hill of $21.80^{\circ}$, and 61% over hill of $26.57^{\circ}$. Wind velocity was bigger over surface of across-wind direction of hills than one over surface of wind direction of hills, and wind velocity was increased $10{\sim}30%$ at locations of across-wind direction.

• Journal of Forest and Environmental Science
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• v.33 no.2
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• pp.130-135
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• 2017

In temperate monsoon regions, extensive shallow landslides triggered by heavy rainfall are recurrent phenomena in mountainous areas. 1,357 landslides over Jinbu area, Korea that totaled 127 km2 were identified from aerial photographs and field survey. We examined characteristics of rainfall-induced shallow landslides and casual factors affecting landslide distribution with respect to topographic and forest settings, and land use. Most landslides occurred in the study area were the results of a complex combination of precondition, preparatory factors and triggering factors. Cumulative rainfall and high intensity rainfall during short period of time made the study area very sensitive to landslides and played as catalysts to enable other factors including topographic and forest settings, and land use to act more effectively. In addition, some landslides at lower elevation involved channel incision or bank erosion influenced by land use changes such as deforestation and intensification of agriculture surrounding riparian forests or hillslopes. The results suggest that most of landslide were triggered by heavy rainstorms while topographic, forest settings, and land use affected landslide distribution occurred in the study area.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.314-317
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• 2004

The aim of this study was to evaluate the susceptibility from landslides in the Lai Chau region of Vietnam, using Geographic Information System (GIS) and remote sensing data, focusing on the relationship between tectonic fractures and landslides. Landslide locations were identified from an interpretation of aerial photographs and field surveys. Topographic and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS data and image processing techniques, and a scheme of the tectonic fracturing of the crust in the Lai Chau region was established. In this scheme, Lai Chau was identified as a region with low crustal fractures, with the grade of tectonic fracture having a close relationship with landslide occurrence. The factors found to influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature, distance from drainage, lithology, distance from a tectonic fracture and land cover. Landslide prone areas were analyzed and mapped using the landslide occurrence factors employing the probability-likelihood ratio method. The results of the analysis were verified using landslide location data, and these showed a satisfactory agreement between the hazard map and existing landslide location data.

• Korean Journal of Ecology and Environment
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• v.49 no.2
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• pp.142-146
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• 2016

The purpose of this study is to evaluate topographic characteristics revealed in the predicted distribution areas of Aporia crataegi, according to climate change. Towards this end, this study compared the differences of topographic factors, such as altitude, mountain slope and the aspect of slope, in the distribution areas with different potential inhabitation possibilities of the Aporia crataegi. The inhabitation possibilities of the Aporia crataegi were different, according to altitude and topographic slope, and the inhabitation possibility is judged to be affected more by the topographic conditions including altitude and mountain slope than by the aspect of slope. Especially, the inhabitation possibility of the Aporia crataegi was higher in the higher altitude area, as time goes on furthermore. The reason is that the current climate environment, which is suitable for the potential inhabitation of the Aporia crataegi, is forecast to be formed with an area with high altitude. Although the difference in the aspect of slope was not statistically significant according to inhabitation possibility, the reason why the inhabitation possibility of the Aporia crataegi varies in the mainly southeast slope is conjectured to be derived from the warmer heat environmental condition to grow from a larva into an imago. The result drawn in this study is expected to be utilized as basic data to establish a policy soundly preserving and managing the habitat of biospecies in consideration of climate change and topographic conditions in the natural ecosystem field by using the already built up various biological resources information.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.65-70
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• 2003

The weight-of-evidence model one of the Bayesian probability model was applied to the task of evaluating landslide susceptibility using GIS. Using the location of the landslides and spatial database such as topography, soil, forest, geology, land use and lineament, the weight-of-evidence model was applied to calculate each factor's rating at Boun area in Korea where suffered substantial landslide damage fellowing heavy rain in 1998, The factors are slope, aspect and curvature from the topographic database, soil texture, soil material, soil drainage, soil effective thickness, and topographic type from the soil database, forest type, timber diameter, timber age and forest density from the forest map, lithology from the geological database, land use from Landsat TM satellite image and lineament from IRS satellite image. Tests of conditional independence were performed for the selection of the factors, allowing the 43 combinations of factors to be analyzed. For the analysis, the contrast value, W$\^$＋/and W$\^$-/, as each factor's rating, were overlaid to map laudslide susceptibility. The results of the analysis were validated using the observed landslide locations, and among the combinations, the combination of slope, curvature, topographic, timber diameter, geology and lineament show the best results. The results can be used for hazard prevention and planning land use and construction

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.73-83
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• 2022

The factors influencing landslide occurrence were analyzed for six points on the upper slope and the 24 points on the lower slope along a forest road around Sangsan village in Chungju, Korea, where landslides have occurred due to heavy rainfall. In terms of physico-mechanical properties of the soil layer, the lower slope seemed to loosen owing to the higher porosity, lower unit weight, and lower friction angle compared with the upper slope. With respect to topographic characteristics, the lower slope had thicker regolith, more concave profile and plan curvatures, lower slope angles, and higher topographic wetness index values than the upper slope. Therefore, all the properties (except for the slope angle) appear to make the lower slope of the forest road more vulnerable to landslides than the upper slope. Apart from the physico-mechanical and topographic characteristics, inadequate maintenance and management of drainage facilities are also considered as further major factors influencing landslide occurrence.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.507-514
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• 2018

TSI (TPI-Slope Index) which is the combination of TPI (Topographic Position Index) and slope was newly proposed for landslide and applied to a landslide susceptibility model. To do this, we first compared the TPIs with various scale factors and found that TPI350 was the best fit for the study area. TPI350 was combined with slope to create TSI. TSI was evaluated using logistic regression. The evaluation showed that TSI can be used as a landslide factor. Then a logistic regression model was developed to assess the landslide susceptibility by adding other topographic factors, geological factors, and forestial factors. For this, landslide-related factors that can be extracted from DEM (Digital Elevation Model), soil map, and forest type map were collected. We checked these factors and excluded those that were highly correlated with other factors or not significant. After these processes, 8 factors of TSI, elevation, slope length, slope aspect, effective soil depth, tree age, tree density, and tree type were selected to be entered into the regression analysis as independent variables. Three models through three variable selection methods of forward selection, backward elimination, and enter method were built and evaluated. Selected variables in the three models were slightly different, but in common, effective soil depth, tree density, and TSI was most significant.

• Proceedings of the KSRS Conference
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• v.1
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• pp.504-507
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• 2006

Airborn Lidar technology has been applied to diverse applications with the advantages of accurate 3D information. Further, Lidar intensity, backscattered signal power, can provid us additional information regarding target's characteristics. Lidar intensity varies by the target reflectance, moisture condition, range, and viewing geometry. This study purposes to generate normalized airborne LiDAR intensity image considering those influential factors such as reflectance, range and geometric/topographic factors (scan angle, ground height, aspect, slope, local incidence angle: LIA). Laser points from one flight line were extracted to simplify the geometric conditions. Laser intensities of sample plots, selected by using a set of reference data and ground survey, werethen statistically analyzed with independent variables. Target reflectance, range between sensor and target, and surface slope were main factors to influence the laser intensity. Intensity of laser points was initially normalized by removing range effect only. However, microsite topographic factor, such as slope angle, was not normalized due to difficulty of automatic calculation.

• Journal of The Geomorphological Association of Korea
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• v.17 no.1
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• pp.73-84
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• 2010

This paper is to analyze effectiveness and efficiency of topographic features in visibility analysis. For this research aim, this paper compares the analysis results of topographic features and relationships between topographic features and their visibility analysis on surfaces. This paper employs peak, pass, pit, ridge and valley features from the topographic features for which five areas including mountain and plain areas in Britain are selected and their DEM data are generated. The summaries of the analysis results are as follows: Firstly, it is clear that relationship between high elevation points and their visibility is not highly correlated. This means that highly elevated points are not necessarily better visible areas and they are not suitable for searching for large visible areas. Secondly, the positions that can see large visible areas are highly correlated with their elevation and are distributed within a certain range which has small deviation of their correlation between visibility and elevation. This means that to search for large visible areas, it is necessary to employ the positions located at relatively high elevation area. Thirdly, for all of the five areas, the visibility results of the topographic features are compared with maximal visibility resulted from a while surface areas, and it is identified that topographic features show similar visibility performances of that maximal visibility. From the results stated above, it can be inferred that topographic features and its topographic characteristics are enable to be a research motivation to the visibility analysis topics. Furthermore, the results of this paper can be contributed to explore suitable variables and factors for solving multiple viewshed problems.