• Journal of Ecology and Environment
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• v.45 no.1
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• pp.1-9
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• 2021

Background: Abandoned coal piles after the closure of mines have a potential negative influence on the environment, such as soil acidification and heavy metal contamination. Therefore, revegetation by efficient species is required. For this, we wanted to identify the role of Silene acaulis in the succession of coal piles as a pioneer and a nurse plant. S. acaulis is a well-studied cushion plant living in the Arctic and alpine environments in the northern hemisphere. It has a highly compact cushion-like form and hosts more plant species under its canopy by ameliorating stressful microhabitats. In this research, we surveyed vegetation cover on open plots and co-occurring species within S. acaulis cushions in coal piles with different slope aspects and a control site where no coal was found. The plant cover and the similarity of communities among sites were compared. Also, the interaction effects of S. acaulis were assessed by rarefaction curves. Results: S. acaulis was a dominant species with the highest cover (6.7%) on the coal piles and occurred with other well-known pioneer species. Plant communities on the coal piles were significantly different from the control site. We found that the pioneer species S. acaulis showed facilitation, neutral, and competition effect in the north-east facing slope, the south-east facing slope, and the flat ground, respectively. This result was consistent with the stress gradient hypothesis because the facilitation only occurred on the north-east facing slope, which was the most stressed condition, although all the interactions observed were not statistically significant. Conclusions: S. acaulis was a dominant pioneer plant in the succession of coal piles. The interaction effect of S. acaulis on other species depended on the slope and its direction on the coal piles. Overall, it plays an important role in the succession of coal piles in the High Arctic, Svalbard.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1567-1577
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• 2020

Urban land cover classification is role in urban planning and management. So, it's important to improve classification accuracy on urban location. In this paper, machine learning model, Support Vector Machine (SVM) and Artificial Neural Network (ANN) are proposed for urban land cover classification based on high resolution satellite imagery (KOMPSAT-3A). Satellite image was trained based on 25 m rectangle grid to create training data, and training models used for classifying test area. During the validation process, we presented confusion matrix for each result with 250 Ground Truth Points (GTP). Of the four SVM kernels and the two activation functions ANN, the SVM Polynomial kernel model had the highest accuracy of 86%. In the process of comparing the SVM and ANN using GTP, the SVM model was more effective than the ANN model for KOMPSAT-3A classification. Among the four classes (building, road, vegetation, and bare-soil), building class showed the lowest classification accuracy due to the shadow caused by the high rise building.

• Journal of Wetlands Research
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• v.14 no.4
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• pp.699-713
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• 2012

Palustrine wetland is often used for development work and green area creation. However, the ecological characteristic of vegetation is not frequently considered in planning. Therefore, this study was conducted to investigate vegetation characteristic according to land-use of palustrine wetland and to provide basic materials in assessment of palustrine wetland and restoration and creation of wetland. Survey sites were caterogized into paddy, field, and mountain. Each category had two sites, so total 6 survey sites were investigated for vegetation. As a result, with a range of 61~92 species, total 216 taxa were confirmed, consisting of 71 families, 168 generic, 187 species, 2 variety 1 forma 1 subforma. Mountain received a high score in the evaluation score range of floristic regional indicator plants, and it was found that there were 10 families and 28 species of naturalized plant. Mountain showed low appearance, and fiddy and field showed relatively high appearance. Naturalized plants with slightly high vegetation cover ratio are Erigeron annuus, Amorpha fruticosa, Dactylis glomerata, Festuca arundinacea, Eragrostis curvula, Trifolium repens, Erigeron Canadensis, Ambrosia trifida, Oenothera odorata, Bidens frondosa, etc. Such naturalized plants should be removed to prevent terrestrialization of wetland and its harmful damages. Long-term monitoring and proper management of naturalized plants are expected to improve palustrine wetland into high quality biotope of rural area in the future.

• Ecology and Resilient Infrastructure
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• v.6 no.4
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• pp.304-313
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• 2019

Biopolymer based on microbial β-glucan and xanthan gum is effective for vegetation and has a function of enhancing soil strength, which can be used as soil reinforcement and stabilization materials in river embankment. The purpose of this study is to verify the vegetation effect of the surface of levee by biopolymer with seed spraying method. Mixed soils with biopolymer were used to cover the surface of embankments. The strength is higher in biopolymer-treated soil and xanthan gum based biopolymer has advantage for quality control in field scale. In addition, the vegetation of F. arundinacea and L. perenne showed various reactions with types of biopolymers. Biopolymer has a positive effect on the vegetation of them. In contrast, root growth tended to decrease in biopolymer-treated soils. The results indicate that root growth is slow down due to increasing ability to retain water in biopolymer-treated soil. In order to apply biopolymer to river embankment, it is necessary to examine the effects of biopolymers on a wide range of plant species in river embankment.

• The Korean Journal of Ecology
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• v.28 no.2
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• pp.99-103
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• 2005

Actual vegetation map drown with the scale 1 to 100 and Alnus japonica population in Ja-neup and Woong-neup of the Mujechi moor were described in order to monitor long-termly and preserve permanently, where is a very rare Molinietea moor and a legally protected area. A total of 3036 plots of 5m $\times$ 5m were surveyed during summer 1996. Thiessen polygons of 1491 alder trees were derived from the plot data. Actual vegetation map was illustrated by 6 cover types such as needle spike-rush type, moor-grass type, alder-moor type, eulalia type, oak forest type, and exposed site. Molinia grasses native to the moor and Miscanthus grasses alien to the moor are reciprocally dominant. The area of Molinia grasslands was rapidly in decline and alder population size was dramatically in increase in the moor, particularly in Woong-neup. In Molinietea moor preservation more attention should be focused on the regulation of a nutrient rich soil from forest road and fire.

• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.407-414
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• 2013

This study was conducted to classify forest cover types using the multivariate statistical analysis in the natural forest of western Mt. Jiri. On the basis of the vegetation data by point quarter sampling, the adopted analytical methods were species-area curve (SAC), hierarchical cluster analysis (HCA), indicator species analysis (ISA), and multiple discriminant analysis (MDA). SAC selected the outlier tree species which was likely to have no influence on the classification of forest cover types, excluded from all analytical process. Based on forest vegetative information, HCA classified the study area into 2 to 10 clusters and ISA indicated that the optimal number of clusters were seven. MDA was taken to test the clusters that classified with HCA and ISA. The seven clusters were classified appropriately as overall classification success were 91.3%. The classified forest cover types were named by the ratio of the dominant species in the upper layer of each cluster. They were (1) Quercus mongolica Pure forest, (2) Mixed mesophytic forest, (3) Q. mongolica - Q. serrata forest, (4) Abies koreana - Q. mongolica forest, (5) Fraxinus mandshurica forest, (6) Q. serrata forest, and (7) Carpinus laxiflora forest.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.215-219
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• 2001

Land surface parameterization schemes for atmospheric models as well as decision support tools for ecosystem management require a frequent updating of land cover classification data for regional to global scales. Rice paddies have not been treated independently from other agricultural land classes in many classification systems, despite their atmospheric and ecological significance. A simple but improved method over conventional land cover classification schemes for rice paddy is suggested. Normalized difference vegetation index (NDVI) was calculated for the land area of South Korea at a 1km by 1 km resolution from the visible and the near-infrared channel reflectances of NOAA-AVHRR (Advanced Very High Resolution Radiometer). Monthly composite images of daily maximum NDVI were prepared for May and August, and used to classify 4 major land cover classes : urban, farmland, forests and water body. Among the pixels classified as "forests" in August, those classified as "water body" in May were assigned a "rice paddy" class. The distribution pattern of "rice paddy" pixels was very similar to the reported rice acreage of 1,455 Myons, which is the smallest administrative land unit in Korea. The correlation coefficient between the estimated and the reported acreage of Myons was 0.7, while 0.5 was calculated from the USGS classification.calculated from the USGS classification.

• Journal of Korean Society of Forest Science
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• v.95 no.3
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• pp.334-341
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• 2006

This study was to investigate the growth of planted red pine (Pinus densiflora S. et. Z.) seedling, soil properties and understory vegetation structure after fertilizer treatments [unfertilized plot (control), CF plot (Combination Fertilizer), UF plot (Urea Formaldehyde Fertilizer)] in a Pinus densiflora stand planted after the forest fires in Gosung, Gangwon province. The height growth rates of seedlings in four years were 264% in unfertilized, 404% in CF, and 388% in UF plots, respectively. The root collar diameters were increased 340% in unfertilized, 454% in CF, and 427% in UF plots, respectively. No significant changes occurred in soil total nitrogen and potassium ion ($K^+$) with the fertilization. However, available $P_2O_5$, content in the soil surface (0-15 cm) increased with the fertilizer application. Soil organic matter increased significantly with fertilizer treatments, while gradual decrease occurred in unfertilized plots. Sodium ion ($Na^-$) decreased in all sites. Soil pH, CEC, calcium ion ($Ca^{2+}$) and magnesium ion ($Mg^{2+}$) contents were not significantly different among treatments. Although Shannon's species diversity index and species richness in understory vegetation did not change with fertilizer treatments, vegetation cover rates in forest floor increased significantly with the fertilization. These results suggest that the increase of pine seedling growth and vegetation cover rates with fertilization could enhance soil stabilization in forest tire areas.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.15-17
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• 2003

One of the most serious problems that the world is facing is the loss of biodiversity and habitats as a result of environmental degradation. There are several strategies to protect the habitats and biodiversity within a certain region such as establishing protected areas; monitoring the remaining forests and managing the landscape within limits have been employed. In this study, Predicted Habitat Distribution Model (simple spatial modeling) was developed using vegetation types, land use and land cover, DEM, slope, drainage, roads, human settlement areas and minimum habitat requirements of each species. Then, based on the checklist of presence and absence of each species, the final habitat maps for selected endangered species are generated. Integration of Remote Sensing (RS) and Geographical Information System (GIS) has proven a very effective tool to generate wildlife habitat maps at various levels. An effecting mapping could be performed based on satellite remote sensing and modeling biodiversity indicators in GIS.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1483-1485
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• 2003

Multitemporal approaches using sequential data acquired over multiple years are essential for satisfactory discrimination between many land cover classes whose signatures exhibit seasonal trends. At any particular time, the response of several classes may be indistinguishable. Using the estimates of periodogram which are obtained from sequential images, the periodicity of the process have been incorporates into multitemporal classification. The Normalized Difference Vegetation Index (NDVI) was computed for seven-day composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 - 2000 using a dynamic technique.