• Journal of Korean Society on Water Environment
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• v.23 no.4
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• pp.467-473
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• 2007

Although the dominant land use at the Imha-dam watershed is forest areas, soil erosion has been increasing because of intensive agricultural activities performed at the fields located along the stream for easy-access to water supply and relatively favorable topography. In addition, steep topography at the Imha-dam watershed is also contributing increased soil erosion and sediment loads. At the Imha-dam watershed, outflow has increased sharply by the typhoons Rusa and Maemi in 2002, 2003 respectively. In this study, the Soil and Water Assessment Tool (SWAT) model was evaluated for simulation of flow and sediment behaviors with long-term temporal and spatial conditions. The precipitation data from eight precipitation observatories, located at Ilwol, Subi and etc., were used. There was no significant difference in monthly rainfall for 8 locations. However, there was slight differences in rainfall amounts and patterns in 2003 and 2004. The topographical map at 1:5000 scale from the National Geographic Information Institute was used to define watershed boundaries, the detailed soil map at 1:25,000 scale from the National Institute of Highland Agriculture and the land cover data from the Korea Institute of Water and Environment were used to simulate the hydrologic response and soil erosion and sediment behaviors. To evaluate hydrologic component of the SWAT model, calibration was performed for the period from Jan. 2002 to Dec. 2003, and validation for Jan. 2004 to Apr. 2005. The $R^2$ value and El value were 0.93 and 0.90 respectively for calibration period, and the $R^2$ value and El value for validation were 0.73 and 0.68 respectively. The $R^2$ value and El value of sediment yield data with the calibrated parameters was 0.89 and 0.84 respectively. The comparisons with the measured data showed that the SWAT model is applicable to simulate hydrology and sediment behaviors at Imha dam watershed. With proper representation of the Best Management Practices (BM Ps) in the SWAT model, the SWAT can be used for pre-evaluation of the cost-effective and sustainable soil erosion BMPs to solve sediment issues at the Imha-dam watershed. In Korea, the Universal Soil Loss Equation (USLE) has been used to estimate the soil loss for over 30 years. However, there are limitations in the field scale mdel, USLE when applied for watershed. Also, the soil loss changes temporarily and spatially, for example, the Imha-dam watershed. Thus, the SW AT model, capable of simulating hydrologic and soil erosion/sediment behaviors temporarily and spatially at watershed scale, should be used to solve the muddy water issues at the Imha-dam watershed to establish more effective muddy water reduction countermeasure.

• Journal of the Korean GEO-environmental Society
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• v.18 no.6
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• pp.21-30
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• 2017

This study analyzed the ground characteristics region by designating 3 research areas, Anrim-dong in Chungju City, Busa-dong in Daejeon Metropolitan City and Sinan-dong in Andong City out of the areas subject to concentrated management to prepare for sediment disaster in downtown areas. The correlation between ground characteristics were observed by using characteristics (crown density, root cohesion, rainfall characteristics, soil characteristics) and the risk areas were predicted through sediment disaster prediction modeling. Landslide MAPping (LSMAP), Stability Index MAPping (SINMAP) and Landslide Hazard MAP (LHMAP) were used for the comparative analysis of the hazard prediction model for sediment disaster. As a result of predicting the sediment disaster danger, in case of SINMAP which was generally used, excessive range was predicted as a hazardous area and in case of the Korea Forest Service's landslide hazard map (LHMAP), the smallest prediction area was assessed. LSMAP predicted a medium range of SINMAP and LHMAP as hazardous area. The difference of the prediction results is that the analysis parameters of LSMAP is more diverse and engineering than two comparative models, and it is found that more precise prediction is possible.

• 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.

• Economic and Environmental Geology
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• v.34 no.4
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• pp.385-394
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• 2001

There are serious damage of people and properties every year due to landslides that are occurred by heavy rain. Because these phenomena repeat and the heavy rain is not an atmospheric anomaly, the counter plan becomes necessary. The study area, Ulsan, is one of the seven metropolitan, and largest cities of Korea and has many large facilities such as petrochemical complex and factories of automobile and shipbuilding. So it is necessary assess the landslide hazard potential. In the study. the three steps of landslide hazard assessment techniques such as susceptibility, possibility, and risk were performed to the study area using GIS. For the analyses, the topographic, geologic, soil, forest, meteorological, and population and facility spatial database were constructed. Landslide susceptibility representing how susceptible to a given area was assessed by overlay of the slope, aspect, curvature of topography from the topographic DB, type, material, drainage and effective thickness of soil from the soil DB, lype age, diameter and density from forest DB and land use. Then landslide possibility representing how possible to landslide was assessed by overlay of the susceptibility and rainfall frequency map, Finally, landslide risk representing how dangerous to people and facility was assessed by overlay of the possibil. ity and the population and facility density maps The assessment results can be used to urban and land use plan for landslide hazard prevention.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.47-57
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• 2010

The aim of this study is to detect landslide using digital aerial photography and apply the landslide to landslide susceptibility mapping by artificial neural network (ANN) and geographic information system (GIS) at Jinbu area where many landslides have occurred in 2006 by typhoon Ewiniar, Bilis and Kaemi. Landslide locations were identified by visual interpretation of aerial photography taken before and after landslide occurrence, and checked in field. For landslide susceptibility mapping, maps of the topography, geology, soil, forest, lineament, and landuse were constructed from the spatial data sets. Using the factors and landslide location and artificial neural network, the relative weight for the each factors was determinated by back-propagation algorithm. As the result, the aspect and slope factor showed higher weight in 1.2-1.5 times than other factors. Then, landslide susceptibility map was drawn using the weights and finally, the map was validated by comparing with landslide locations that were not used directly in the analysis. As the validation result, the prediction accuracy showed 81.44%.

• 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.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.138-140
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• 2003

The aim of this study is to evaluate the effect of spatial resolutions on the accuracy to landslide susceptibility mapping. For this, landslide locations were identified in the Boun, Korea from interpretation of aerial photographs and field surveys. The topographic, soil, forest, geologic, linearment and land use data were collected, processed and constructed into a spatial database using GIS and remote sensing data. The 15 factors that influence landslide occurrence were extracted and calculated from the spatial database with 5m, 10m, 30m, 100m and 200m spatial resolutions. Landslide hazardous area were analysed and mapped using the landslide-occurrence factors by probability model, likelihood ratio, for the five cases spatial resolutions. The results of the analysis were verified using the landslide location data. In the cases of spatial resolution 5m, 10m and 30m, the verification results was similar, but in the cases of 100m and 200m the results worse than the others. Because the scale of input data was 1:5,000 ? 1:50,000, so the cases of 5m, 10m and 30m have similar accuracy but the cases of 100m and 200m have the lower accuracy. From this, there is an effect of spatial resolutions on accuracy and landslide susceptibility mapping the result is dependent on input map.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.2
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• pp.107-118
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• 2010

The purpose of this study was to set the boundary of the coastal sand dunes and to analyze the change characteristics of land cover types using aerial photographs on Osan and Dongho coastal sand dunes in Yangyang. The boundaries of sand dunes were established using digital soil map, and land cover maps were made for each year using aerial photographs. As results of analysis, both beach and farmland areas have been decreased, since 1974 and forest area was relatively increased due to planting and forest growth. Facilities and bare land have been greatly increased since 1992. Loss of wetland, and beach due to these changes had an impact on the ecosystem destruction of sand dunes.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.153-161
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• 2008

Agriculture and forest are basis for livelihood in Nepal while both sectors constitute around 40 percent of the national product and over two-thirds of the economically active population is dependent on agriculture. However, radical changes in land use, depletion in crops production and food availability are major threats due to loss of soil fertilityand severe environmental degradation. In this study, we used time series data from 1986/87 to 2005/06 about food crop production and population published by Government of Nepal, Ministry of Agriculture and Cooperatives and Central Bureau of Statistics. Descriptive statistics and ArcGIS were used to assess and map the food security status of Nepalese Terai based on the local food demand and supply system. Food supply to demand ratio(FSDR) was the main idea of assessment. Our results showed that out of 20 districts, only 8 districts were categorised under secured food districts whereas 5 districts were still under food unsecured situation. The analysis further revealed that 7 districts had faced food deficit more than 8-16 times during the last 20 year periods. Data further showed that there was surplus food supply relative to the requirements dictated by FSDR. However, the average FSDR was less than 1.2(less than 20% surplus) exploring fact that most of the districts were not producing sufficient food to cope up the food shock and after 1995 it was relatively stagnant. Our prediction reveals that food supply in Terai even in the future would remain at almost the same level as now, and there will not more than 16-17% surplus by 2021 considering medium vibrant population growth. The findings thus, indicate that Terai may not be a food secure region in the future, even though the region is considered as a food storage house of Nepal. In addition, this paper suggests ways to make future comprehensive case studies more widely comparable in Terai, Nepal.

• Economic and Environmental Geology
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• v.37 no.4
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• pp.425-436
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• 2004

The purpose of this study is to analyze the spatial relationship between the landslides occurred by typhoon, Rusa in 2002 and geospatial dataset. Landslide locations were detected using satellite image and field survey. Topogra-phy, soil, forest, geology and land use data sets were constructed as a spatial database in GIS. From the database, slope, aspect, curvature, water system, type of topography, texture, material, drainage, effective thickness of soil, type, age, diameter, density of wood, lithology, lineament of geology, land use and lineament were used as the land-slide occurrence factors. Using a frequence ratio model, the spatial relationships between the landslides and the factors were extracted. The spatial relationships is helpful to explain the characteristics of the landslide, and to make landslide susceptibility map.