• Journal of Korean Society of Environmental Engineers
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• v.22 no.7
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• pp.1331-1343
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• 2000

Through the integration of USLE and GIS, the methodology to estimate the soil loss was developed, and applicated to the Sacheon river in Gangrung. Using GIS, spatial analysis such as watershed boundary determination, flow routing. slope steepness calculation was done. Spatial information from the GIS application was given for each grid. With soil and land use map, information about soil classification and land use was given for each grid too. Based upon these data, thematic maps about the factors of USLE were made. We estimated the soil loss by overlaying the thematic maps. In this manner, we can assess the degree of soil loss for each grid using GIS. Annual average soil loss of Sacheon river watershed is 1.36 ton/ha/yr. Soil loss in forest, dry field, and paddy field is 0.15 ton/ha/yr, 27.04 ton/ha/yr, 0.78 ton/ha/yr respectively. The area of dry field, which is 4% of total area, is $2.4km^2$. But total soil loss of dry field is 6561 ton/yr, and it occupies 84.9 % of total soil loss eroded in Sacheon river watershed. Comparing with the 11.2 ton/ha/yr of an average soil loss tolerance for cropland, provision for the soil loss in dry field is necessary. Run-off and water quality of Sacheon river were measured two times in flood season: from July 24, 1998 to July 28 and from September 29 to October 1. As the run-off of the river increased, SS, TN, TP concentrations and pollutant loadings increased. SS, TN, TP loads of Sacheon river discharged during the 2 heavy rains were 21%, 39%, and 19% of the total pollutant loadings generated in the Sacheon river watershed for one year. We can see that much pollutants are discharged in short period of flood season.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.4
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• pp.199-206
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• 2004

Factors of universal soil loss equation, USLE, and its revised version, RUSLE for Korean soils were reevaluated to estimate the national scale of soil loss based on digital soil maps. Rainfall erosivity factor, R, of 158 locations of cities and counties were spacially interpolated by the inverse distance weight method. Soil erodibility factor, K, of 1321 soil phases of 390 soil series were calculated using the data of soil survey and agri-environmental quality monitoring. Topographic factor, LS, was estimated using soil map of 1:25,000 scale with soil phase and land use type. Cover management factor, C, of major crops and support practice factor, P, were summarized by analyzing the data of lysimeter and field experiments for 27 years (1975-2001) in the National Institute of Agricultural Science and Technology. R factor varied between 2322 and 6408 MJ mm $ha^{-1}$ $yr^{-1}$ $hr^{-1}$ and the average value was 4276 MJ mm $ha^{-1}$ $yr^{-1}$ $hr^{-1}$. The average K value was evaluated as 0.027 MT hr $MJ^{-1}$ $mm^{-1}$. The highest K factor was found in paddy rice fields, 0.034 MT hr $MJ^{-1}$ $mm^{-1}$, and K factors in upland fields, grassland, and forest were 0.026, 0.019, and 0.020 MT hr $MJ^{-1}$ $mm^{-1}$, respectively. C factors of upland crops ranged from 0.06 to 0.45 and that of grassland was 0.003. P factor varied between 0.01 and 0.85.

• Journal of the Korean association of regional geographers
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• v.9 no.3
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• pp.373-384
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• 2003

This study analyses the soil loss due to cropland increase in the Hoeryeung area of northeast Korea, using Landsat images of 1987 TM and 2001 ETM, together with DTED, soil and geological maps, and rainfall data of 20 years. Items of land cover and land use were categorized as cropland, settlement, forest, river zone, and sand deposit by supervised classification with spectral bands 1, 2 and 3. RUSLE model is used for estimation of soil loss, and AML language for calculation of soil loss volumes. Fourier transformation method is used for unification of the geographical grids between Landsat images and DTED. GTD was selected from 1:50,000 topographic map. Main sources of soil losses over 100 ton/year may be the river zone and settlement in the both times of 1987 and 2001, but the image of the 2001 shows that sources areas have developed up to the higher mountain slopes. In the cropland average, increases of hight and gradient are 24m and $0.8^{\circ}$ from 1987 to 2001. In the case of new developed cropland, average increases are 75m and $2.5^{\circ}$, and highest soil loss has occurred at the elevation between 300 and 500m. The soil loss 57 ton of 1987 year increased 85 ton of 2001 year. Soil loss is highest in $30{\sim}50^{\circ}$ slope zones in both years, but in 2001 year, soil loss increased under $30^{\circ}$ zones. The size of area over 200 ton/year, indicating higher risk of landslides, have increased from $28.6km^2$ of 1987 year to $48.8km^2$ of 2001 year.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.1
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• pp.43-56
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• 2012

The purpose of this study was to propose management strategies through aesthetic landscape assessments for landscape units in the Han River riparian(HRR) area. First, this research reclassified the HRR into "natural," "artificial," "agricultural," and mixed landscape types and selected 37 representative case areas(about $1km{\times}1km$). This study found 71 landscape units in consideration of topography and land surface classification. Landscape assessment consisted of landscape quality and landscape integration assessment. The criteria for assessing landscape quality were "naturalness," "interest," "uniqueness," and "landscape function." "Landscape quality" was ranked into five grades using a matrix. The landscape integration assessment consisted of an inner integration assessment in each landscape unit and outer integration assessment among landscape units. As a result of the field study, case sites were found to have 4,288 landscape units and an area of $42.8km^2$. The forest area was found to have the most space with $11,580,905m^2$(27.1%), while the wet lands had just $52,348m^2$(0.1%). In the landscape quality assessment, about 30.5% of the total area consisted of landscape units that scored highest in "naturalness". In the landscape integration assessment, about 39.3% of the total area consisted of landscape units which scored highest in "integration", denoting visual interrelation and harmony. The existence of disparities in landscape quality in accordance with the form of the landscaping was determined using a Oneway ANOVA, with "naturalistic" landscaping scoring the highest and "artificial" landscaping scoring lowest. This study may contribute to making the HRR area a more ecologically sound and visually attractive landscape space. It is recommended that the aesthetical and ecological value of the landscape unit should be assessed simultaneously in the future.

• The Korean Journal of Mycology
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• v.23 no.1 s.72
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• pp.92-104
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• 1995

Ten species of Cordyceps species were collected throughout Kangwon province including Chuncheon Dongsanmyun KNU forest experiment from June to September, 1993. Collected Cordyceps species were identified as Cordyceps militaris, C. roseostromata, C. kyushuensis, C. scarabaeicola, Phytocordyceps ninchukiospora, C. nutans, Paecilomyces tenuipes, C. sphecocephala, Hymenostilbe odonatae, Torrubiella sp.. C. militaris, type species of Cordyceps species, was mainly formed on pupae of Lepidoptera and found after the rainy season around July. Fruiting body of C. roseostromata was morphologically similar to those of C. militaris, but relatively small in size and they were also found on lawn or pupa of Lepidoptera. Fruiting body of C. scarabaeicola was found on adult Scarabaeidae specifically and collect fruiting bodies of C. kyushuensis were on larva of moth. C. nutans and C. sphecocephala had host specificity on Hemiptera and Hymenoptera, respectively. Each species formed elliptical fertile part attach to the slim and carneous stalk and they were collected the most in specimen number through whole season of the summer. Ascospore of Phytocordyceps ninchukiospora on seed was characterized by two viable, multiseptate, fusiform units linked end-to-end by a long, filiform connective. Paecilomyces tenuipes, imperfect stage of the genus Cordyceps is multi-infective fungi that attack all stages of all groups of insects. Hymenostilbe odonatae attacks only adult Odonata and Torrubiella sp. formed on spider was difficult to collect because it was found the back side of leaf. As results of cultural test PDA medium showed the best mycelial growth. In the experiment of effect of the acidity inside of the media, C. militaris was good on pH 5, C. nutans and Phytocordyceps ninchukiospora were good on pH 6 and Paecilomyces tenuipes was on pH 7 and C. scarabaeicola was on pH 9. All isolates tested showed the best mycelial growth at $20^{\circ}C$. Morphologically similar isolates were used to analyze protein banding pattern among and within species. As a result, C. militaris, C. roseostromata and C. kyushuensis were clustered into close species and C. scarabaeicola and Phytocordyceps ninchukiospora were relatively distant from those species.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.117-132
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• 2019

The study examines the significance and limits of modern park planning by analyzing major planning documents of Gyeongseong in the Japanese colonial era. Among seven selected documents from 1925 to 1940, which show the contents related with park planning, documents of 1930 and 1940 presented the official park plan of Gyeongseong. By the 1920s, the park plan was not a major concern in urban planning of Gyeongseong; however, as the planning law as enacted in 1934, the park plan legally became a part of the official master planning process in the 1930s. In 1940, the most comprehensive park plan for Gyeongseong was published. In the beginning of modern urban planning, a park was mainly perceived as a sanitation utility. From the 1920s to the 1930s, the park planning system was significantly improved including systemic classification of parks, guideline development considering spatial planning, and introduction of a concept of infra-structural green space. Despite of the improvement in the park planning, the actual quantity of the overall green spaces barely changed and there was a huge discrepancy between the planning ideal and the reality. The Gyeongseong stadium was the only facility newly built in the 1920s, and only two parks were constructed in the 1930s. The plan to build 38 new parks in the 1930, and 140 in the 1940 was barely realized. However, there were efforts to improve parks and green spaces of Gyeongseong: Such as appropriating natural forest as parks, designating royal palaces as parks, and focusing on constructing smaller scale children's parks. Even though the ideal plan could not be fully implemented due to the war time situation and tight budget, the park system of Gyeongseong provided the framework of park planning of Seoul after the independence.

• Korean Journal of Environment and Ecology
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• v.33 no.1
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• pp.75-85
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• 2019

The purpose of this study is to understand the vegetation characteristics of ridges (Gyeongsusan-Seonunsan-Gaeipalsan) in the Seonunsan Provincial Park and to establish reference information for the management of the park in the future. We designated 62 plots with the area of $100m^2$ were installed and analyzed them to investigate the vegetation characteristics. The results of community classification based on TWINSPAN showed seven categories of vegetation communities in the surveyed region: Quercus dentata-Deciduous broad-leaved Community, Quercus variabilis-Pinus thunbergii-Quercus serrata Community, Pinus densiflora Community, Deciduous broad-leaved Community-I, Carpinus tschonoskii-Castanea crenata-Quercus aliena Community, Deciduous broad-leaved Community-II, and Carpinus tschonoskii-Carpinus laxiflora Community. In the vegetation of Seonunsan Provincial Park, coniferous trees such as Pinus thunbergii and Pinus densiflora have been gradually losing their population as part of ecological succession to deciduous broad-leaved trees such as Quercus spp., Carpinus tschonoskii, and Carpinus laxiflora. Moreover, Carpinus turczaninowii, Mallotus japonicus, and others were identified as vegetation reflecting the geographical characteristics of the region neighboring the west coast. The estimated age is 30-60 years, and the oldest tree Pinus densiflora is 63-years old. The index of diversity ($100m^2$) was 0.7942 for Carpinus tschonoskii-Carpinus laxiflora Community, 0.8406 for Carpinus tschonoskii-Castanea crenata-Quercus aliena Community, 0.8543 for Quercus dentata-Deciduous broad-leaved Community, 0.9434 for Quercus variabilis-Pinus thunbergii-Quercus serrata Community, 0.9520 for Deciduous broad-leaved Community-I, 0.9633 for Pinus densiflora Community, and 1.0340 for Deciduous broad-leaved Community-II in the ascending order.

• Economic and Environmental Geology
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• v.55 no.5
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• pp.551-561
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• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.311-323
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• 2023

In order to reduce disaster damage by localized heavy rains, floods, and urban inundation, it is important to know in advance whether natural disasters occur. Currently, heavy rain watch and heavy rain warning by the criteria of the Korea Meteorological Administration are being issued in Korea. However, since this one criterion is applied to the whole country, we can not clearly recognize heavy rain damage for a specific region in advance. Therefore, in this paper, we tried to reset the current criteria for a special weather report which considers the regional characteristics and to predict the damage caused by rainfall after 1 hour. The study area was selected as Gyeonggi-province, where has more frequent heavy rain damage than other regions. Then, the rainfall inducing disaster or hazard-triggering rainfall was set by utilizing hourly rainfall and heavy rain damage data, considering the local characteristics. The heavy rain damage prediction model was developed by a decision tree model and a random forest model, which are machine learning technique and by rainfall inducing disaster and rainfall data. In addition, long short-term memory and deep neural network models were used for predicting rainfall after 1 hour. The predicted rainfall by a developed prediction model was applied to the trained classification model and we predicted whether the rain damage after 1 hour will be occurred or not and we called this as 1ST-Model. The 1ST-Model can be used for preventing and preparing heavy rain disaster and it is judged to be of great contribution in reducing damage caused by heavy rain.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."