• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.274-277
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• 2007

This study is to estimate the spatial distribution of soil loss using the land use data produced from QuickBird satellite imagery. For a small agricultural watershed (1.16 $km^2$) located in the upstream of Gyeongan-cheon watershed, a precise agricultural land use map were prepared using QuickBird satellite image of April 5 of 2003. RUSLE (Revised Universal Soil Loss Equation) was adopted for soil loss estimation. The data (DEM, soil and land use) for the RUSLE were prepared for 5 m and 30 m spatial resolution. The results were compared with each other and the result of 30 m Landsat land use data.

• Journal of Industrial Technology
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• v.19
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• pp.147-154
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• 1999

The soil loss by rainfalls or runoffs has been one of the main environment problems in 20th century. The soil loss cause the various problems those are decreasing of the agricultural productivity, desolating of pasture land and disturbing of water flowing. Therefore, it is very important to measure properly various factors those are affecting to soil loss and to recognize a seriousness of soil loss problem. In this study, we use the USLE(Universal Soil Loss Equation) as a basic approaching way for soil loss analysis in a watershed, and the GSIS(Geo-Spatial Information System) technique is applied to evaluate for factors those are related to the USLE. The results of this study are consisted of three parts those are to build up the various topographical information that is needed for analysis of wide area soil loss by using the USLE, to evaluate the factors those are needed to the USLE, to estimate the soil loss condition of subbasin in the watershed.

• Journal of Korean Society of Rural Planning
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• v.11 no.2 s.27
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• pp.9-19
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• 2005

The purpose of this study is to analyze the potential soil loss and hazard zone by the Revised Universal Soil Loss Equation(RUSLE) for preservation and management of land resources which is the base of ecosystem, and to grasp the relationship between RUSLE factors in the Nakdong River Basin. All thematic maps used in RUSLE are constructed through GIS and spatial analysis method derived from digital topographic maps, detailed soil maps, land-cover maps, and mean annual precipitation of 30 years collected respectively from National Geographic Information Institute, National Institute of Agricultural Science and Technology, and Ministry of Environment. The slope length of LS-factor that takes much times by the study area's wideness was calculated automatically through AML(Arc Macro Language) program developed by Van Remortel et al.(2001, 2003). The results are as follows; First, according to the soil loss estimation by the RUSLE, it shows that approximately 82% of the study area have relatively lower possibility of soil loss which is the 1 ton/ha in annual soil loss. While, 9.4% ($2,228km^2$) needed intensive and continuous management for soil loss. Because the amount of their annual soil loss was greater than 10 ton/ha that is optimum level suggested by Morgan(1995). For these areas, the author believe that a new approach which can minimize environmental impacts from soil loss through improvement of cultivation process and buffer forest zone should be applied. Second, according to the relationship between the RUSLE factors, topographical(LS-factor) and cover management(C-factor) conditions have a lot of influence on soil loss in case of the Nakdong River Basin. However, because of RUSLE factor's influence that affect to soil loss might be different based on the variety of spatial hierarchy and extent, it is necessary to analyze and evaluate factor's relationship in terms of spatial hierarchy and extent through field observations and further studies.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.11-16
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• 2003

Soil loss by the rains has effect on natural environment. But It is difficult to find out the data that is surveyed in watershed. In this paper, we choose USLE erosion model, which could be connected easily with GSIS and available generally, and extracted factors which is entered model by using GSIS spatial analysis method. Especially, As revised USLE model, It should be applied in watershed and as it calculated soil loss before Idlest fire and behind, it analysed the degree that it have an effect on soil loss. As each analyzed factors and the result of soil loss estimate consist of 22m-pixel size, we could identify soil loss by each pixel and distribution pattern.

• Spatial Information Research
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• v.17 no.3
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• pp.261-268
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• 2009

This study accomplished to draw a soil erosion map and a grade map of soil loss hazard in Korea. RUSLE and Rainfall-runoff (R) factor, which was estimated by using the rainfall data observed in 59 meteorological stations from 1977 to 2006 (for 30 years). FARD was used to analyze the frequency, and the whole country R factor was estimated according to the frequency. In the analysis of estimating the whole country R factor, Nakdong river has the smallest vaule, but Han river has the biggest value. According to the result of analyzing soil loss, soil loss occurred in a grass land, a bare land and a field in size order, and also approximately 17.2 ton/ha soil loss happened on the whole area. The average soil loss amount by the unit area takes place in a bare land and a grass land a lot. The total amount of soil loss in 5-year-frequency rainfall yields 15,000 ton and, what is more, a lot of soil loss happens in a paddy field, a forest and a crop field. The grade map of soil loss hazard is drawn up by classifying soil loss hazard grade by 5. As a result of analyzing soil loss, the moderate area which is the soil loss hazard grade 2 takes up the largest part, 72.8% of the total soil loss hazard area, on the contrary, the severe soil loss hazard area takes up only $1,038km^2$ (1.1%) of the whole area. The severe soil loss hazard area by land cover shows $93.5km^2$ in a bare land, $168.1km^2$ in a grass land and $327.4km^2$ in a crop field respectively.

• Spatial Information Research
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• v.13 no.1 s.32
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• pp.79-90
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• 2005

The purpose of this study is to estimate quantitatively soil loss and sediment yield in alpine farmland. For this purpose, Naerinchon watershed in Gangwon province was selected as our study area and total annual soil loss and sediment yield was estimated respectively by the Revised Universal Soil Loss Equation (RUSLE) model and the Sediment Delivery Distributed (SEDD) model. The results of this study clearly show that dry field areas have significant impact on the total soil erosion and sediment yield compared with other land use. Dry field areas represent only $2.6\%$ of the total area of the watershed but soil loss and sediment yield account for $10.9\%$ and $33.12\%$ of the total amount respectively Especially as with alpine farmland, this result is more clearly shown. These areas account for $1.8\%$ of the entire watershed but contribute to $7.7\%$ and $15\%$ of the total soil loss and sediment yield respectively. From the above results, we can know that alpine farmland is important source of soil loss and sediment yield and it is need to prevent and control. soil erosion from alpine filmland urgently.

• Spatial Information Research
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• v.2 no.2
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• pp.165-174
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• 1994

Soil loss was estimated by using universal soil loss equation(USLE) through GIS technique in Buyeu area. The expected soil loss is determined from six environmental factors: rainfall, erodibility of selected soil, length and steepness (gradient) of ground slope, crop grown in soil, and land practices used. A scoring system for assessing soil lossrisk has been developed for calculating SLI(Soil Loss Index) by GIS. The scores of six factors multiplied to give a total score which was compared with an chosen classification system to categorize areas of low, moderate and high risk. Finally, a soil loss assessment map was produced by GIS cartographic simulation technique, and this map could be applied in the establishment of regional land use planning.

• Spatial Information Research
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• v.10 no.2
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• pp.301-316
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• 2002

Soil Loss by outflow of water or rainfall has caused many environmental problems as declining agricultural productivity, damaging pasture and preventing flow of water. Also, validity pondage of reservoir or dam is decreased by rivers inflow of eroded soil. Revised Universal Soil Loss Equation(RUSLE) is mainly used to presume soil loss amount of basin using GIS. But, because comparison with survey data is difficult, it is no large meaning that estimate calculated soil loss amount as quantitative. This research used unit sediment deposit survey data of Bo-seong basin for quantitative conclusion of soil loss amount that calculate on RUSLE. Through comparison examination with unit sediment yield that calculate on RUSLE and unit sediment deposit survey data, we can estimate resolution far RUSLE Model. As a result, cell size of 150m was estimated by thing which is most suitable.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.353-358
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• 2003

Soil loss by the rains has effect on natural environment. But It is difficult to find out the data that is surveyed in watershed. In this paper, we chose USLE erosion model, which could be connected easily with GSIS and available generally, and extracted factors which is entered model by using GSIS spatial analysis method. Especially, As revised USLE model, It should be applied in watershed and as it calculated soil loss before forest fire and behind, it analysed the degree that it have an effect on soil loss. Each analyzed factors and the result of soil loss estimate consist of 22m-pixel size, we could identify soil loss by each pixel and distribution form.

• Spatial Information Research
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• v.14 no.4 s.39
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• pp.363-377
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• 2006

Mean annual soil loss was calculated and critical soil erosion areas were identified for the Congaree River Basin in South Carolina, USA using the Revised Universal Soil Loss Equation (RUSLE) model. In the RUSLE model, the mean annual soil loss (A) can be calculated by multiplying rainfall-runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), crop-management (C), and support practice (P) factors. The critical soil erosion areas can be identified as the areas with soil loss amounts (A) greater than the soil loss tolerance (T) factor More than 10% of the total area was identified as a critical soil erosion area. Among seven subwatersheds within the Congaree River Basin, the urban areas of the Congaree Creek and the Gills Creek subwatersheds as well as the agricultural area of the Cedar Creek subwatershed appeared to be exposed to the risk of severe soil loss. As a prototype model for examining future effect of human and/or nature-induced changes on soil erosion, the RUSLE model customized for the area was embedded into ESRI ArcGIS ArcMap 9.0 using Visual Basic for Applications. Using the embedded model, users can modify C, LS, and P-factor values for each subwatershed by changing conditions such as land cover, canopy type, ground cover type, slope, type of agriculture, and agricultural practice types. The result mean annual soil loss and critical soil erosion areas can be compared to the ones with existing conditions and used for further soil loss management for the area.