• Korean Journal of Ecology and Environment
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• v.48 no.2
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• pp.129-138
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• 2015

Forest vegetation of Geumsusan (1,016.0 m) and Doraksan (964.4 m) in Woraksan National Park is classified into mountain forest vegetation. Mountain forest vegetation is subdivided into deciduous broad-leaved forest, mountain valley forest, coniferous forest, riparian forest, afforestation and other vegetation. Including 77 communities of mountain forest vegetation and 5 communities of other vegetation, the total of 82 communities were researched; mountain forest vegetation classified by physiognomy classification are 37 communities deciduous broad-leaved forest, 16 communities of mountain valley forest, 8 communities of coniferous forests, 1 community of riparian forest, 15 afforestation and 5 other vegetation. As for the distribution rate for surveyed main communities, Quercus variabilis and Quercus mongolica communities account for 33.031 percent of deciduous broadleaved forest, Cornus controversa community takes up 29.142 percent of mountain valley forest, Pinus densiflora community holds 64.477 percent of mountain coniferous forest holds. In conclusion, minority species consisting of Quercus variabilis, Quercus mongolica, Pinus densiflora, Quercus serrata and Cornus controversa are distributed as dominant species of the uppermost part in a forest vegetation region in Woraksan National Park. In addition, because of vegetation succession and climate factors, numerous colonies formed by the two species are expected to be replaced by Quercus variabilis, Quercus mongolica, Cornus controversa and Fraxinus mandshurica which are climax species in the area.

• Korean Journal of Ecology and Environment
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• v.49 no.4
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• pp.296-307
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• 2016

Ecological restoration is an eco-technology, which heals the nature damaged by human activity by imitating organization and function of the integrate nature and thereby provide an inhabitable space for diverse organisms. Such an ecological restoration has to be carried out by applying restoration plan prepared based on the results of diagnostic evaluation discussed in the diversified respects. This study aims to prepare an ecological restoration plan of the damaged forest ecosystem in Mt. Moodeung National Park. To arrive at the goal, first of all, we diagnosed quality of forest landscape established in Mt. Moodeung National Park based on natural (topography, climate, and distribution of vegetation) and artificial (land use, linear landscape element) factors. In addition, we evaluated the integrity of each zone divided by linear landscape element quantitatively based on geometric property and land use intensity. As the result of analysis, topography of Mt. Moodeung National Park tended to be depended on weathering property of parent rock and vegetation zones were divided to three vegetation zones. Based on land use pattern, deciduous broad-leaved forest, evergreen needle-leaved forest, and mixed forest occupied about 90% of Mt. Moodeung National Park. Mean score of forest landscape quality was shown in $69.86{\pm}11.41$. As a result, forest landscape elements in Mt. Moodeung National Park were influenced greatly by human activity and the degree was depended on topographic condition. This study suggested the synthetic restoration plan to improve ecological quality of Mt. Moodeung National Park based on the results of diagnostic evaluation.

• Korean Journal of Environment and Ecology
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• v.36 no.4
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• pp.390-401
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• 2022

This study investigated the characteristics of fish communities and inhabiting status of endangered species in the Bukcheon (Stream) of Seoraksan National Park, Korea from April to September 2020. A total of 4,356 fish of 7 families and 22 species were collected from 17 survey stations during the survey period. The dominant species was Zacco koreanus (relative abundance, 41.8%), and subdominant species was Rhynchocypris kumgangensis (relative abundance, 15.1%), followed by Pungtungia herzi (10.1%), Pseudopungtungia tenuicorpa (5.0%), Coreoleuciscus splendidus (4.1%), Zacco platypus (3.8%), Microphysogobio longidorsalis (3.5%), and Hemibarbus mylodon (2.2%). Among the fish species collected, 14 species (63.6%) were identified as Korean endemic species. There was one natural monument species (Hemibarbus mylodon), and four species of class II endangered wildlife that were designated by the Ministry of Environment (Acheilognathus signifer, Pseudopungtungi tenuicorpa, Gobiobotia brevibarba, and Brachymystax lenok tsinlingensis). Among the four species of class II endangered wildlife, B. lenok tsinlingensis inhabited in the upper stream, and A. signifer, P. tenuicorpa and G. brevibarba inhabited mainly in the middle-lower stream. Also, P. tenuicorpa, H. mylodon, and B. lenok tsinlingensis were inhabited in large numbers. Additionally, two cold-water fish species (R. kumgangensis and B. lenok tsinlingensis) and one landlocked species (B. lenok tsinlingensis) were collected. According to the results of cluster analysis, the dominance index decreased from upstream to downstream, but the diversity, evenness, and richness index increased; the cluster structure was divided into the uppermost, upstream, midstream, and downstream. The water quality of Bukcheon was evaluated as good overall since the river health (index of biological integrity) evaluated using fish was evaluated as very good (11 stations), good (2 stations), and normal (4 stations). However, river repair work was being carried out in some areas and some wastewater was flowing in from the midstream, therefore, supplementary measures to preserve fish habitats are required.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.