• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.729-734
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• 2006

This paper aimed to suggest decision-making method for forest management planning using integer programming. Thus, the study examined 85 stands consisting of Korean pine, Japanese larch and oak stands-all of which were at the most suitable time for tending, selection thinning, commercial thinning and final cutting-in the experimental forest of Kangwon National University. The forest management model comprised one objective function, maximizing harvest volume in each stand according to tree species and the kinds of practices, and seven constraints: frequency and stands of practices, minimum and maximum yields, even yields, maximum production, and decision-making varialbes. Besides, the entire period intended by the study was 10 years, divided into 5 management periods. In conclusion, the forest management planning model using integer programming proved that among 85 stands, forest practices were conducted over 68 stands (202.8 ha), producing the total harveted volume of $20,000m^3$, while the rest was reserved. This case study could help make decisions on whether and when the forest practices and harvests could be done in a specific condition.

• Journal of Korean Society of Forest Science
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• v.80 no.2
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• pp.202-209
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• 1991

This study was carried out to examine seed germination, seedling growth, and biomass production of Eucommia ulmoides. The results were summarized as follows ; 1. Cold moist stratification at a refrigerator showed 60.3% of seed germination, which is the most effective among pretreatment methods. 2. In case of 1-0 seedlings, sixty seedlings per $1m^2$ was the most appropriate density, and the growth quality of seedlings differed significantly among densities. 3. Height growth showed continuous growth pattern and the maximum growth was shown during the period 21 June to 20 July, which corresponds 32.7% of total annual growth. 4. As tree age and DBH increased, the production of bark and leaf increased, however, its increment rate remarkably dropped down after ten years. 5. When tree age was ten years, the rate of bark volume showed the maximum value, 12.42%. 6. Dry weight of barks and leaves and bark volume were positively related to the growth of DBH and height. 7. As tree age increased, leaf area decreased, but the number of leaves increased.

• Journal of Korean Society of Forest Science
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• v.106 no.1
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• pp.40-53
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• 2017

The purpose of this study was to evaluate the effects of container types on physiological characteristics of Zelkova serrata, Fraxinus rhynchophylla and Quercus serrata in the container nursery stage. We used 16 container types [4 growing densities (100, 144, 196 and $256\;seedlings/m^2$)${\times}4$ cavity volumes (460, 380, 300 and $220cm^3/cavity$)] and performed two-way ANOVA to test the differences in photosynthesis, photochemical efficiency and chlorophyll content among container types. Also, multiple regression analysis was conducted to correlate container dimensions with photosynthetic rate. Container types had a strong influence on photosynthesis of three species seedlings. Growing densities and cavity volumes had a significant interaction effect on photosynthetic rate, water use efficiency, stomatal conductance and chlorophyll contents except stomatal conductance of Q. serrata. In all three species, however, interactions between the two factors of container type were not found with regard to photochemical efficiency. Growing density was negatively correlated with photosynthetic rate of F rhynchophylla and Q. serrata, while cavity volumes positively affected on those of three species seedlings. The range of optimal container types was determined by multiple regression analysis based on photosynthetic rate. Consequently, optimal growing density and cavity volume of container by each tree species were found to be approximately $160{\sim}210\;seedlings/m^2$ and $430{\sim}460cm^3/cavity$ for Z. serrata, $130{\sim}150\;seedlings/m^2$ and $390{\sim}440cm^3/cavity$ for F. rhynchophylla and $130{\sim}170\;seedlings/m2$ and $420{\sim}460cm^3/cavity$ for Q. serrata, respectively. Application of adequate container will induce higher quality seedling production in nursery stage, which will also increase seedling growth in plantation stage.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.1-11
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• 2021

The purpose of this study is to find out the main factors affecting air quality in urban physical space factors, and provide clues for environmental improvement. Nine monitoring stations in China's industrial city, Changchun, collected AQI concentration data from January 1, 2018 to December 31, 2019. This paper analyzes the types and distribution characteristics of urban physical facilities within a radius of 300m with the detection station as the center. The monitoring station is divided into three groups, and the difference in floating dust concentration among the three groups in different seasons is analyzed. The results show that AQI concentration is the highest in spring and winter, followed by summer, and the lowest in autumn. The place with the highest concentrations of AQI in spring are F (93.00), D (91.10), I (89.20), in summer are D (69.05), A (67.89), B (84.44), in autumn are I (62.80), G (60.84), D (53.27), D (53.27), in winter are I (95.82), H (95.60), f (94.04). Through SPSS analysis, it shows that the air index in a space with a diameter of 600 meters is related to forest land, grassland, bare land, water space, tree height, building area (average value), and building volume (average value). According to the statistical analysis results of spring and winter with the most serious pollution, forest land area (43,637m², 15.44%) and water surface area (18,736m², 6.63%) accounted for the majority, and group 1 (A, B, C) with the least average building area (448m², 0.17%) and average building volume (10,201m²) had the lowest pollution concentration. On the contrary, group 2 (D, E, F) had the highest AQI concentration, with less or no woodland (1,917m², 0.68%) and water surface area (0m², 0%), and the highest average building area (1,056m², 0.37%) and average building volume (17,470m³). It is confirmed that the characteristics of the area with the highest AQI concentration are that the more the site ratio of tree height above 12m, the smaller the site ratio of bare land, and the lower the pollution degree. On the contrary, the larger the area of bare land, the higher the pollution degree. By analyzing the characteristics of nine monitoring stations in Changchun, it can be seen that the air quality brought by the physical characteristics of urban space is closely related to the above factors.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Korean Society of Forest Science
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• v.87 no.4
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• pp.631-641
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• 1998

The objectives of this study were 1) to classify the types of Quercus mongolica stands at Mt. Joongwang and compare their quality, and 2) to determine the proper future tree number of Q. mongolica per ha and the appropriate distance between the future trees. The results from this study were as follows : Q. mongolica stands at Mt. Joongwang was classified into four types, pure Q. mongolica stand as stand type I, Q. mongolica - hardwood stand as stand type II, Q. mongolica - Pines densiflora stand as stand type III, Hardwood - Q. mongolica stand as stand type IV, according to mixture rate in stand volume. Stand type IV showed the best quality stem of Q. mongolica among the stand types, and the stem quality of Q. mongolica in Q. mongolica stand mixed with hardwood as stand types II and IV was better than those in pure Q. mongolica stand as stand type I and in Q. mongolica - P. densiflora stand as stand type III. If the management goal for Q. mongolica stand is to produce its high quality-timber, it is desirable to sustain proper mixture rate of Q. mongolica with another hardwoods. The proper number of future trees in pure Q. mongolica stand as stand type I was 122trees/ha and reasonable distance between the future trees was 9.15m. The distance between future trees in other stand types was 7.2m to 9.3m for stand types II and IV, while 8.0m for stand type III. Thus, the classification of Q. mongolica stand type based on stand character and maturity, and proper stem number of future tree and optimum distance between future trees would be a useful forest tending work.

• Korean Journal of Heritage: History & Science
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• v.43 no.1
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• pp.190-211
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• 2010

The purpose of this paper is to provide the preliminary data for maintenance of old trees of natural monuments and establishing protection projects. Accordingly, growth conditions, location circumstances, environment and protection management were analyzed for old trees at 34 sites in Gyeongsangbuk-do. Tree forms, crown, trunk and trees' health, leaves volume were analyzed in survey sites. As the results, the growth of Picrasma quassioides in Songsadong, Andong-si and Catalpa ovata in Hongwon-ri, Cheongsong-gun were not in good condition, along with other old trees of 6 cities (Quercus variabilis in Susan-ri, Uljin-gun, Juniperus chinensis in Hujeong-ri, Uljin-gun, Pyrus ussuriensis in Ssangjeon-ri, Uljin-gun, Salix glandulosa var. pilosa in Deokchon-ri, Cheongdo-gun, Pinus densiflora for. multicaulis in Hwasan-ri, Mungyeong-si, Pinus densiflora in Daeha-ri, Mungyeong-si). Accoding to these results, protection project and consistent monitoring are necessary. The analysis results of growth conditions per location circumstances showed that the old trees in the small spaces with large traffic of people were in bad condition. Therefore, it is necessary to secure sufficient space and soil improvement for such trees. The analysis results of growth conditions per species showed that Zelkova serrata, Quercus spp., Pinus densiflora are in good condition while Salix koreensis and others, i.e. a singular tree, are in poor condition. Thus, relatively smaller individuals and separately situated trees need careful management in their protection. The analysis results of trunk's growth ratio showed that Pinus densiflora, Ginkgo biloba, Zelkova serrata are in good condition whereas Juniperus chinensis, Quercus variabilis, Salix koreensis are not. It is a recent trend that tree surgeries are gradually decreasing; there are a number of damaged trees with no maintenance/management, and several sites requiring mend trunks management and cabling, bracing in protection and management projects. Hence, in the future, local government and management organizations should plan for systematic management and establish a protection plan for the natural monument trees. Also, 12 sites were found to be in need to purchase lands in order to secure the growth spaces, and since most of these areas are available for purchase, it is needed to promote a budget and purchase those areas through persuasion of the owner. These areas seems crucial in order to maximize the effect of conservation efforts and budgets for the preservation and restoration of the old trees.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.71-79
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• 2016

Evaluation of the walkability of the urban pedestrian network requires construction of a pedestrian network model that reflects Space Syntax Theory. Space Syntax Theory deduces an integration value through which materials for evaluation of the pedestrian network's connectivity can be produced; and can aid in illustrating the ease of walkability through the model's calculation of pedestrian indices such as movability, comfort, and safety. But the representation of space syntax theory in the pedestrian network requires that turn delay be added by means of a network-type construction method. While tree-based Dial Algorithm proposed for the logit-based probability walkability distribution model may be effective for link-based pedestrian volume distribution, it requires further network expansion to reflect turn delays. In this research, Vine-based Dial Algorithm is executed in order to obtain a measure reflecting the integration value for Space Syntax Theory. The Vine-based Dial Algorithm of two adjacent links, which forms the minimum unit of the Vine network, has the advantage of encompassing turn delay, and thus eliminates the need for network expansion. Usage of the model to evaluation of complicated pedestrian spheres such as urban roads is left to further research. Especially the progression of the proposed method is deduced through case study.

• Journal of Korean Society of Forest Science
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• v.105 no.1
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• pp.132-138
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• 2016

The objectives of this study were to infer the parameters of forest stand growth functions of STEMS for Cryptomeria japonica stands of Jeju Hannam Experimental Forest, Korea Forest Research Institute, and to investigate the effects of thinning regimes on the patterns of stand growth and carbon absorption. The forest stand growth functions for the potential diameter growth, modifier, crown ratio and mortality are the major ones composing the independent-tree/distance-free forest stand growth simulator, STEMS. The parameters were inferred using the sets of growth data obtained from stem analyses of 39 trees, chosen from 13 sample plots of the forest stands. The effects of thinning regimes on the patterns of stand growth and carbon absorption were investigated by simulating the stand growth patterns of the case study stand with 3 different thinning regimes: no-thinning, early thinning with low intensity and late thinning with high intensity using the simulator. According to the results of the analyses, the different thinning regimes cause significant effects on the growth patterns of average DBH, average height, diameter distribution and stand volume as well as the amount of carbon absorptions.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.25-36
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• 2014

Multispectral image classification of individual tree species is often difficult because of the spectral similarity among species. In this study, we attempted to analyze the suitability of hyperspectral image to classify coniferous tree species. Several image sets and classification methods were applied and the classification results were compared with the ones from multispectral image. Two airborne hyperspectral images (AISA, CASI) were obtained over the study area in the Gwangneung National Forest. For the comparison, ETM+ multispectral image was simulated using hyperspectral images as to have lower spectral resolution. We also used the transformed hyperspectral data to reduce the data volume for the classification. Three supervised classification schemes (SAM, SVM, MLC) were applied to thirteen image sets. In overall, hyperspectral image provides higher accuracies than multispectral image to discriminate coniferous species. AISA-dual image, which include additional SWIR spectral bands, shows the best result as compared with other hyperspectral images that include only visible and NIR bands. Furthermore, MNF transformed hyperspectral image provided higher classification accuracies than the full-band and other band reduced data. Among three classifiers, MLC showed higher classification accuracy than SAM and SVM classifiers.