• Journal of Environmental Impact Assessment
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• v.25 no.4
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• pp.233-247
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• 2016

The purpose of this study is to offer the basic data for management of National Park by surveying and analysing the change of flora of damaged lands in Juwangsan National Park, Korea. In cause of occurring the damaged lands, site-1 was the vegetation damage by stamping, the removing Gwangamsa of site-2, 3, 4 and the removing Naewon village of site-5, 6, 7. Whole sites are caused by the artificial disturbance and interference. The numbers of flora were summarized as 135 taxa including 52 families, 109 genera, 116 species, 2 subspecies and 17 varieties in whole sites. The status of flora by sites, site-6 is the largest number of 52 taxa, site-1 is the lowest of 23 taxa. The rare plant is 1 taxa, 4 taxa of endemic plants, 10 taxa of specific plants by floristic region, 9 taxa of naturalized plants and 1 taxa of invasive alien plant. In the results of analysis about the change of coverage ratio, for this shrub layer, site-7 was changed to the most $0%{\rightarrow}50%$, and the herb layer, site-5 was changed to the most $75%{\rightarrow}95%$. In case of the change of species numbers, most sites tended to increase in the sites introduced different species or generated by the growth. It is contemplated that is similar to the restoration with the surrounding natural vegetation that is in progress is a transition occurs with the passage of time. In the dominant species, the shrub layer is Fraxinus sieboldiana, Lespedeza bicolor, Rhus javanica, Lespedezamaximowiczii, Salix koreensis and Zelkova serrata, and Miscanthus sinensis var. purpurascens, Oplismenus undulatifolius, Artemisia princeps, Bothriochloa ischaemum and Erigeron annuus of herb layer. In the results of analysing Naturalized Index(NI) and Urbanized Index(UI), NI was increased or decreased this phenomenon with the lapse of time, UI was the most increase. In particular, the increase in UI is due to the transition process, the pioneering plant, naturalized plant was imported to continue.

• Journal of Korean Society of Forest Science
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• v.27 no.1
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• pp.5-14
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• 1975

Eroded sloping faces in hillsides including cut-bank slopes are liable to both surface erosion and land-slides and the key to control of these form of erosion lies with drainages of excessive run-off and dense vegetation establishment including surface mulching on the slopes. Micro-plots having $1.6m^2$ (1 metre in width and 1.6 metres in slope length, and 1:1.2 in gradient) of banking slopes on coarse sand soil are used to establish the order of magnititude of the difference in controlling of soil erosion and water runoff, and in rating of survival, performed on the repetetions of three-experiment plots consisted of such three levels as 90% (Dense), 70% (Moderate), and 50% Sparse of the density of the coarse straw-mat mulchings. The main results obtained may be summarized as follows: 1. The rates of surface runoff are calculated as 13.13% from the dense mulchings, 14.21% from the moderate mulchings, and 15.57% from the sparse mulchings respectively. 2. The total amounts of soil loss are measured as about 1.24 tons/ha. from the dense mulchings, about 1.33 tons/ha. from the moderate mulchings, and about 1.44 tons/ha. from the sparse mulchings respectively. The amounts of soil loss under these treatments are much lower than the standard of erosion in USDA (1939 Bennet). 3. Average numbers of germination by treatment are counted as 80 seedlings at the dense mulchings. 132 at the moderates and 121 at the sparse respectively. Large numbers of seedling are suppressed and died during the growing at the dense mulchings due to mainly mechanical obstruction. 4. Coarse straw-mat having about 70% of coverage density is the most suitable mulches in both soil erosion control and vegetation establishment. 5. The method of coarse straw-mat mulching is the most recommendable measure for establishing the vegetation cover with less soil erosion on the denuded gentle slopes in hillsides at present in Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.295-305
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• 2024

This study aims to analyze the micro-sedimentary structures of the Hwangdo tidal flats using ultra-high resolution unmanned aerial vehicle (UAV) data. Tidal flats, located in the transitional area between land and sea, constantly change due to tidal activities and provide a unique environment important for understanding sedimentary processes and environmental conditions. Traditional field observation methods are limited in spatial and temporal coverage, and existing satellite imagery does not provide sufficient resolution to study micro-sedimentary structures. To overcome these limitations, high-resolution images of the Hwangdo tidal flats in Chungcheongnam-do were acquired using UAVs. This area has experienced significant changes in its sedimentary environment due to coastal development projects such as sea wall construction. From May 17 to 18, 2022, sediment samples were collected from 91 points during field surveys and 25 in-situ points were intensively analyzed. UAV data with a spatial resolution of approximately 0.9 mm allowed identifying and extracting parameters related to micro-sedimentary structures. For mud cracks, the length of the major axis of the polygons was extracted, and the wavelength and ripple symmetry index were extracted for ripple marks. The results of the study showed that in areas with mud content above 80%, mud cracks formed at an average major axis length of 37.3 cm. In regions with sand content above 60%, ripples with an average wavelength of 8 cm and a ripple symmetry index of 2.0 were formed. This study demonstrated that micro-sedimentary structures of tidal flats can be effectively analyzed using ultra-high resolution UAV data without field surveys. This highlights the potential of UAV technology as an important tool in environmental monitoring and coastal management and shows its usefulness in the study of sedimentary structures. In addition, the results of this study are expected to serve as baseline data for more accurate sedimentary facies classification.

• Korean Journal of Ecology and Environment
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• v.47 no.3
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• pp.135-145
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• 2014

The mountain forest vegetation of Gyebangsan (1,577 m) in Odaesan National Park is classified into deciduous broad-leaved forest, mountain valley forest, coniferous forest, subalpine coniferous forest, subalpine deciduous forest, plantation forest, and other vegetation which includes Actinidia argute community and agricultural land. As for the number of communities distributed in the each forest vegetation which were categorized by the physiognomy classification, deciduous broad-leaved forest had 33 communities, mountain valley forest 41 communities, coniferous forest 8 communities, subalpine coniferous forest 4 communities, subalpine deciduous forest 2 communities, plantation forest 6 communities and other vegetation 4 communities. Regarding the distribution rate of communities in the vegetation, in the deciduous broad-leaved forest. Quercus mongolica community accounted for 80.226% with $30,909,942.967m^2$, followed by Quercus variabilis community of 2.771% with $1,067,479.335m^2$. 55.463% of deciduous broad-leaved forest in the Gyebangsan had Quercus mongolica as a dominant or second dominant species. In the mountain valley forest, Fraxinus rhynchophylla - Juglans mandshurica community accounted for 10.955%. And there were ten mixed communities having Fraxinus rhynchophylla and upper layer at a similar level of coverage, taking up 32.776%. In the coniferous forest, Pinus densiflora and the community living with Pinus densiflora accounted for 100%, showing that the coniferous forest has the community with Pinus densiflora as a dominant species at upper layer. For other vegetation, subalpine coniferous forest had a total of four communities including Abies holophylla - Quercus mongolica community, and accounted for 4.980% of vegetation area of Odaesan National Park. Two communities including Betula ermani - Cornus controversa community were found in the subalpine deciduous forest, taking up 0.006% of total vegetation area of Odaesan National Park. Regarding plantation forest, Larix leptolepis was planted the most with 51.652%, followed by Betula platyphylla var. japonica with 38.975%, and Pinus koraiensis with 7.969%. These three species combined accounted for 98.565%. In conclusion, the forest vegetation found in the Gyebangsan of Odaesan National Park has Quercus mongolica as a dominant species at the top layer. A lot of other communities related with this species are expected to be quickly replaced due to vegetation succession and climatic causes. Therefore, Quercus mongolica is expected to become the main species in the deciduous broad-leaved forest, Fraxinus rhynchophylla, Juglans mandshurica and Fraxinus mandshurica in the mountain valley forest. Around the border line between deciduous broad-leaved forest and mountain valley forest, highly humid valley area is expected to be quickly taken up by Cornus controversa and Fraxinus mandshurica, and the slope area by Quercus mongolica. However, in the subalpine coniferous forest, the distribution rate of deciduous broad-leaved trees is expected to increase due to climate warming.