• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.57-66
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• 2016

Harmonized World Soil Database (HWSD) including the global soil information has been implemented to the runoff analysis in many watersheds of the world. However, its accuracy can be a critical issue in the modeling because of the limitation the low resolution reflecting the physical properties of soil in a watershed. Accordingly, this study attempted to assess the effect of HWSD in modeling by comparing parameters of the rainfall-runoff model using HWSD with the detailed soil map. For this, Grid based Rainfall-runoff Model (GRM) was employed in the Hyangseok watershed. The results showed that both of two soil maps in the rainfall-runoff model are able to well capture the observed runoff. However, compared with the detailed soil map, HWSD produced more uncertainty in the GRM parameters related to soil depth and hydraulic conductivity during the calibrations than the detailed soil map. Therefore, the uncertainty from the limited information on soil texture in HWSD should be considered for better calibration of a rainfall-runoff model.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.259-266
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• 2002

It is crucial to know spatial soil variability for precision farming. However, it is time-consuming, and difficult to measure spatial soil properties. Therefore, there are needs fur sensing technology to estimate spatial soil variability, and for electronic mapping technology to store, manipulate and process the sampled data. This research was conducted to develop a real-time soil organic matter sensor and an electronic mapping system. A soil organic matter sensor was developed with a spectrophotometer in the 900∼1,700 nm range. It was designed in a penetrator type to measure reflectance of soil at 15cm depth. The signal was calibrated with organic matter content (OMC) of the soil which was sampled in the field. The OMC was measured by the Walkeley-Black method. The soil OMCs were ranged from 0.07 to 7.96%. Statistical partial least square and principle component regression analyses were used as calibration methods. Coefficient of determination, standard error prediction and bias were 0.85 0.72 and -0.13, respectively. The electronic mapping system was consisted of the soil OMC sensor, a DGPS, a database and a makeshift vehicle. An algorithm was developed to acquire data on sampling position and its OMC and to store the data in the database. Fifty samples in fields were taken to make an N-fertilizer dosage map. Mean absolute error of these data was 0.59. The Kring method was used to interpolate data between sampling nodes. The interpolated data was used to make a soil OMC map. Also an N-fertilizer dosage map was drawn using the soil OMC map. The N-fertilizer dosage was determined by the fertilizing equation recommended by National Institute of Agricultural Science and Technology in Korea. Use of the N-fertilizer dosage map would increase precision fertilization up to 91% compared with conventional fertilization. Therefore, the developed electronic mapping system was feasible to not only precision determination of N-fertilizer dosage, but also reduction of environmental pollution.

• 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

• Spatial Information Research
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• v.10 no.4
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• pp.533-550
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• 2002

Soil organic matter (SOM) content and other physical soil properties were extracted from a digital soil database, the Soil Survey Geographic (SSURGO) database, to map the amount of SOM and determine its relationship with topographic positions in floodplain areas along a river basin in Douglas County, Kansas. In the floodplains, results showed that slope and SOM content had a significant negative relationship. Soils near river channels were deep and nearly level, and they had the greatest SOM content in the floodplain areas. For the whole county, SOM content was influenced primarily by soil depth and percent SOM by weight. Among different slope areas, soils on mid-range slopes (10-15%) and ridgetops had the highest SOM content because they had relatively high percent SOM content by weight and very deep soils, respectively. SOM content was also significantly variable among different land cover types. Forest/woodland had significantly higher SOM content than others, followed by cropland, grassland, and urban areas.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.31-35
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• 2000

We investigate the groundwater distribution and chemical characteristics for 3 or 5 districts every year and make the hydrogeologic map on a scale of 1:50,000. We draw the hydrogeologic digital map based on "The Handbook for the Drawing and Management of Hydrogeologic Map" which was published by MOCT and KOWACO in 1998. But, the Stiff diagram and well's notation are difficult to be presented in the digital map using the commercial Arcview GIS tools. So we develop the script file with Avenue language to represent them in Arcview GIS tool. At first, we design the database for the chemical analysis result of groundwater and well identification, and make the program code with Avenue language to display them on the digital map. And next we test the usefulness of the program code. As a result, we find that the script file is very useful for drawing the symbols and diagrams in hydrogeologic digital map using ArcView GIS.

• Korean Journal of Soil Science and Fertilizer
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• v.32 no.2
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• pp.95-108
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• 1999

Field experiments were conducted in the 101 tobacco fields(51 fields in 1985 and 50 fields in 1986) of chief tobacco producing counties of Chungbuk province(Jincheon, Eumseong, Goesan, and Joongweon counties), Chungnam province(Cheonweon county), and Kyongbuk province (Cheongdo, Seongju, and Andong counties) for two years from 1985 to 1986 in order to evaluate soil fertility using chemical properties and soil map database. Pot experiments also on the same soils were conducted and the results were compared to those of field experiments. The yield of tobacco in the plots of no fertilization was considered as a basic factor representing the soil fertility and was evaluated by nineteen independent variables, that was 9 chemical properties and 10 soil map databases. These independent variables were classified into two groups, 11 quantitative indexes and 9 qualitative indexes, and were analyzed by multiple linear regression(MLR) of SAS by REG and GLM models. The yield of tobacco in the plot of no fertilization showed high variations, e.g. the difference between minimum and maximum yields was about 5.0-5.5 times in the pot experiment and 8.2-14.9 times in the field experiment. The indexes indicating close link between yield of tobacco and soil chemical indexes, was selected but it was not well matched by the years or between pot and field experiments. Also, the standardized partial regression coefficients of quantitative indexes for the yield of field were less than 1.0, suggesting that it is difficult to develop an available single index for the evaluation of soil fertility. Evaluation for the soil fertility of field by MLR was better than that of single regression and it was gradually improved by adding chemical properties, quantitative indexes, and qualitative indexes of soil map. For example, the coefficient of determination ($R^2$) of MLR for the yield of 1985 was increased to 0.422 with chemical indexes, 0.503 by addition of quantitative indexes, and 0.633 by the additional adding of qualitative indexes of soil map, compared to 0.244 of single index, $NO_3-N$ content of soil. Consequently, it is assumed that this approach by MLR with quantitative and qualitative indexes including chemical properties and soil map databases was available as an evaluation model of soil fertility for tobacco field.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.100-100
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• 2003

The purpose of this study is to reveals spatial relationships between landslides and geospatial data set, map the landslide susceptibility using the relationships and verify the landslide susceptibility using the landslide occurrence data in Bosun area in 1998. Landslide locations were detected from aerial photography and field survey and topography, soil, forest, and land use data sets were constructed as a spatial database using GIS. As the landslide occurrence factors, slope, aspect, curvature and type of topography, texture, material, drainage and effective thickness of soil, type, age, diameter and density of wood and land use were used. Is extract the relationship between landslides and geospatial database, Bayesian probability methods, likelihood ratio and weight of evidence, were applied and the ratio and contrast value that is W$\^$＋/- W$\^$-/ were calculated. The landslide susceptibility index was calculated by summation of the likelihood ratio and contrast value and the landslide susceptibility maps were generated using the index. As a result, it is expected that spatial relationships between landslides and geospatial database is helpful to explain the characteristics of landslide and the landslide susceptibility map is used to reduce associated hazards, and to plan land use and construction.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.302-305
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• 2004

The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.479-495
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• 2021

To improve on the efficient management of forest resources, it is necessary to create a forest soil map, which represents a comprehensive database of forest lands. Although a 1:25,000 scale forest site map has been used in Korea, the need for a large-scale forest soil map with high precision and information on forest lands that is specialized for individual purposes has been identified. Moreover, to keep pace with the advancement in forest management and transition to a digital society, it is essential to develop a method for constructing new forest soil maps that can diversify its use. Therefore, this paper presented a developmental process and used a 1:5,000 scale forest soil map to propose future directions. National maps showing the soil type, depth, and texture were produced based on the survey and analysis of forest soils, followed by the Forest Land Soil Map (1:5,000) Production Standard Manual. Alternatively, forest soil map data were the basis on which various other maps that can be used to prevent and predict forest disasters and evaluate environmental capacities were developed. Accordingly, ways to provide appropriate information to achieve the national forest plan, secure forestry big data, and accomplish sustainable forest management that corresponds to the national development plan are proposed based on results from the current study.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.298-301
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• 2004

The aim of this study is to cross-validate of spatial probability model, artificial neural network at Boun, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the Boun, Janghung and Youngin areas from interpretation of aerial photographs, field surveys, and maps of the topography, soil type, forest cover and land use were constructed to spatial data-sets. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography, were calculated from the topographic database. Topographic type, texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter, age and density of forest were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using the landslide­occurrence factors by artificial neural network model. For the validation and cross-validation, the result of the analysis was applied to each study areas. The validation and cross-validate results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.