• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.59-64
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• 2008

Soil erosion is a major problem in the case of forests in hilly terrains. Soil erosion removes the fertile topsoil, making unsuitable for growth and establishment of vegetation. In the present study, erosion prone areas in a forest region situated in the Moyar sub-watershed of Western ghats was identified using GIS with data collected from India. The thematic layers such as forest cover, slope and drainage density were used for analysis. In the erosion prone map, majority of area (48%) was under medium category, and about 35% of area was under high erosion prone category. Very high erosion prone category occupied 7% of the forest area. This erosion prone map would be an ideal spatial data to take up necessary management actions at appropriate places in this watershed to prevent erosion.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.664-667
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• 2004

This paper is aimed at analyzing the soil erosion hazard zone in farm land. RUSLE was used for an analysis of soil erosion amount, and for the spatial data of basin, soil erosion amount was calculated by extracting the respect topography space related factors of RUSLE using DEM, Landuse, Soil map as base map. As a result of analysis on the calculated soil erosion amount according to land use type, it was analyzed that the most soil erosion occurred in orchard area, i.e., 40.08ton/ha/yr at average. It was classified into 5 classes depending on the calculated soil erosion amount. of which Class V was decided as soil erosion hazard zone, and for this area, 72.5ha or so, $2.4\%$ of the entire farm land was assessed as erosion hazard zone.

• Journal of Environmental Impact Assessment
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• v.25 no.6
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• pp.525-531
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• 2016

This study integrates the Universal Soil Loss Equation(USLE) with GIS method to assess the soil erosion for national land cover map between 2007 and 2014. The land cover change map and C factors of USLE were applied to the estimation of spatial distribution of sediment yield. However, they generated distinct results because of differences in their applied methods and calculation processes of national land cover map. To generate the USLE model, C factors of MOE(Ministry of Environment) were compared with soil erosion of Inje stadium development area at the Naerin watershed in Gangwon province to 2014. The several thematic maps of research area such as land cover map, topographic and soil maps, together with tabular precipitation data used for soil erosion calculation. The land cover change were carried with level-2 and high level land cover map of MOE and estimated maximum double of soil erosion.

• Water Engineering Research
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• v.2 no.1
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• pp.49-61
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• 2001

A grid-based KIneMatic wave soil-water EROsion and deposition Model(KIMEROM) that predicts temporal variation and spatial distribution of sediment transport in a watershed was developed. This model uses ASCII-formatted map data supported from the regular gridded map of GRASS (U.S. Army CERL, 1993)-GIS(Geographic Information Systems), and generates the distributed results by ASCII-formatted map data. For hydrologic process, the kinematic wave equation and Darcy equation were used to simulated surface and subsurface flow, respectively (Kim, 1998; Kim et al., 1998). For soil erosion process, the physically-based soil erosion concept by Rose and Hairsine (1988) was used to simulate soil-water erosion and deposition. The model adopts single overland flowpath algorithm and simulates surface and subsurface water depth, and sediment concentration at each grid element for a given time increment. The model was tested to a 162.3 $\textrm{km}^2$ watershed located in the tideland reclaimed ares of South Korea. After the hydrologic calibration for two storm events in 1999, the results of sediment transport were presented for the same storm events. The results of temporal variation and spatial distribution of overland flow and sediment areas are shown using GRASS.

• Journal of Korea Water Resources Association
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• v.38 no.11
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• pp.927-935
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• 2005

Soil erosion by rainfall is important factor for basin management because it reduces reservoir capacity and breaks out the contamination of water caused by turbid water. Recently, soil erosion study with GIS is in progress but does not consider soil erosion source area. This study calculated soil erosion amount using GIS-based soil erosion model in Imha basin and examined soil erosion source area using SPOT 5 High-resolution satellite image and land cover map. As a result of analysis, dry field showed high-density soil erosion area and we could easily investigate source area using satellite image. Also we could examine the suitability of soil erosion area by applying field survey method in common areas such as dry field and orchard area those are difficult to confirm soil erosion source area using satellite image.

• Proceedings of the KSRS Conference
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• v.2
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• pp.760-763
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• 2006

In this paper, a small portion of coastline on the EAST SEA was studied using CORONA panoramic satellite photo and 1:5000 Korean National Topographic Map. The project site near Kangneung city was 3 Km shoreline on the Kangmoon Beach and the SongJeong Beach, which have suffered from severe erosion. The first and the most important step was to rectify a CORONA image over the project site. A rigid mathematical model and a heuristic polynomial transformation were used for the purpose. The rectified image was overlaid with 1:5000 Korean National Topographic Map produced by aerial mapping. Among numerous methods for shoreline erosion measurement, area-based approach was chosen and used for the computation for annual shoreline recession. The final result of the analysis was that the average recession in the period of 1963-1998 was 33.6m and the annual rate was 0.96m.

• Journal of Cadastre & Land InformatiX
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• v.46 no.1
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• pp.59-74
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• 2016

The collapses of retaining walls or embankments, the soil erosion and landslides around urban areas are occurring by heavy rainfalls because of the recent climate change. This study conducts the soil erosion modeling, while applying the spatial information such as soil maps, DEM and landcover maps to the RUSLE model. Especially this study draws up the soil erosion grade map and the unit soil erosion grade map by parcels through coupling the soil erosion with the cadastral map, and by that can calculate the number of parcels by soil erosion grades. Also the sediment disaster information system based on the mobile GIS is developed to identify the soil erosion grades of site in the urban plannings and the construction fields. The sediment disaster information system can identify the present conditions of the registers of lands, buildings and roads, and confirm the RUSLE factors, the soil erosion, the sediment disaster grades by parcels. Also it is anticipated that this system can support the sediment disaster work of site effectively through searching the locations and attributes of the specific parcels by Administrative Dong and the soil erosion grades.

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05a
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• pp.25-34
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• 2001

A grid-based KIneMatic wave soil-water EROsion and deposition Model (KIMEROM) that predicts temporal variation and spatial distribution of sediment transport in a watershed was developed. This model uses ASCII-formatted map data supported from the regular gridded map of GRASS (U.S. Army CERL, 1993)-GIS (Geographic Information Systems), and generates the distributed results by ASCIIl-formatted map data. For hydrologic process, the kinematic wave equation and Darcy equation were used to simulate surface and subsurface flow, respectively (Kim, 1798; Kim et al., 1993). For soil erosion process, the physically-based soil erosion concept by Rose and Hairsine (1988) was used to simulate soil-water erosion and deposition. The model adopts sing1e overland flowpath algorithm and simulates surface and subsurface water depth, and sediment concentration at each grid element (or a given time increment. The model was tested to a 162.3 km$^2$ watershed located in the tideland reclaimed area of South Korea. After the hydrologic calibration for two storm events in 1999, the results of sediment transport were presented for the same storm events. The results of temporal variation and spatial distribution of overland flow and sediment areas are shown using GRASS.

• Korean Chemical Engineering Research
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• v.43 no.3
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• pp.412-418
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• 2005

The tube thickness map of water wall has been measured in a commercial circulating fluidized bed combustor (200 ton steam/hr, $4.97{\times}9.90{\times}28.98m$ height) with ultrasonic method and tube erosion has been discussed. Severe tube erosion took place in the splash region on all waterwalls including wingwalls. Erosion on the lower part of front and rear walls, close to both side walls, was more serious than other places. Erosion of some tubes around the gas exit was found to be noticible. Tube erosion increased on the wingwall as the position of the tube become closer to the center of the combustor crosssection.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.7
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• pp.3-12
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• 2004

The need to predict the rate of soil erosion, both under existing conditions and those expected to occur following soil conservation practice, has been led to the development of various models. In this study Morgan model especially developed for field-sized areas on hill slopes was applied to assess the rate of soil erosion using RS/GIS environment in the Dukchun river basin, one of two tributaries flowing into Jinyang lake. In order to run the model, land cover mapping was made by the supervised classification method with Landsat TM satellite image data, the digital soil map was generated from scanning and screen digitizing from the hard copy of soil maps, digital elevation map (DEM) in order to generate the slope map was made by the digital map (DM) produced by National Geographic Information Institute (NGII). Almost all model parameters were generated to the multiple raster data layers, and the map calculation was made by the raster based GIS software, IL WIS which was developed by ITC, the Netherlands. Model results show that the annual soil loss rates are 5.2, 18.4, 30.3, 58.2 and 60.2 ton/ha/year in forest, paddy fields, built-up area, bare soil, and upland fields respectively. The estimated rates seemed to be high under the normal climatic conditions because of exaggerated land slopes due to DEM generation using 100 m contour interval. However, the results were worthwhile to estimate soil loss in hilly areas and the more precise result could be expected when the more accurate slope data is available.