• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1407-1422
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• 2022

This study was conducted to classify tree species and assess the classification accuracy, using SE-Inception, a classification-based deep learning model. The input images of the dataset used Worldview-3 and GeoEye-1 images, and the size of the input images was divided into 10 × 10 m, 30 × 30 m, and 50 × 50 m to compare and evaluate the accuracy of classification of tree species. The label data was divided into five tree species (Pinus densiflora, Pinus koraiensis, Larix kaempferi, Abies holophylla Maxim. and Quercus) by visually interpreting the divided image, and then labeling was performed manually. The dataset constructed a total of 2,429 images, of which about 85% was used as learning data and about 15% as verification data. As a result of classification using the deep learning model, the overall accuracy of up to 78% was achieved when using the Worldview-3 image, the accuracy of up to 84% when using the GeoEye-1 image, and the classification accuracy was high performance. In particular, Quercus showed high accuracy of more than 85% in F₁ regardless of the input image size, but trees with similar spectral characteristics such as Pinus densiflora and Pinus koraiensis had many errors. Therefore, there may be limitations in extracting feature amount only with spectral information of satellite images, and classification accuracy may be improved by using images containing various pattern information such as vegetation index and Gray-Level Co-occurrence Matrix (GLCM).

• Journal of Korean Society of Forest Science
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• v.113 no.2
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• pp.187-197
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• 2024

In this study, we aimed to identify the factors influencing post-fire mortality in Korean red pine (Pinus densiflora) using Cox's proportional hazards model and analyze the impact of these factors. We monitored the mortality rate of fire-damaged pine trees for seven years after a forest fire. Our survival analysis revealed that the risk of mortality increased with higher values of the delta normalized difference vegetation index (dNDVI), delat normalized burn ratio (dNBR), bark scorch index (BSI), bark scorch height (BSH) and slope. Conversely, the risk of mortality decreased with higher elevation, greater diameter at breast height (DBH), and higher value of delta moisture stress index (dMSI) (p < 0.01). Verification of the proportional hazards assumption for each variable showed that all factors, except slope aspect, were suitable for the model and significantly influenced fire occurrence. Among the variables, BSI caused the greatest change in the survival curves (p < 0.0001). The environmental change factors determined through remote sensing also significantly influenced the survival rates (p < 0.0001). These results will be useful in establishing restoration plans considering the potential mortality risk of Korean red pine after a forest fire.

• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.397-407
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• 2017

This research aims to analyze and compare the drought resistance of 7 species of landscape trees commonly grown in Korea. The 7 species are: Camellia japonica, Rhaphiolepis indica, Quercus glauca, Machilus thunbergii, Daphniphyllum macropodum, Dendropanax morbifera and Cinnamomum camphora. In order to analyze their drought resistance, the samples were left without irrigation for 30 days (05/09/2016 ~ 05/10/2016), during which period their respective drought resistor, relative water content, electrolyte elution figures and proline content were measured. As the non-irrigation proceeded, C. camphora was the first to wither, followed by D. morbifera, then D. macropodum, then M. thunbergii, then Q. glauca, then R. indica then finally C. japonica. Of the 7 species, Q. glauca, C. japonica and R. indica can be considered highly drought resistant, since they survived for longer than 3 weeks without irrigation. Relative water content (RWC) plummeted dramatically after the first 15 days of non-irrigation. Whereas RWC readings of C. camphora, D. morbifera, D. macropodum and M. tunbergii dropped by 40% or more, the other 4 species reported a relatively low rate of decrease at 20% or lower. The Camellia japonica, the R. indica and Q. glauca, which were the species with relatively high drought resistance, showed low proline content and electrolyte elution figures, whereas those of C. camphora, D. macropodum, D. morbifera and M. tunbergii were higher. Analysis through the nonlinear regression analysis logistic model showed that non-irrigation proved fatal for the 7 sample species in a range of 22.7 to 37.6 days. The C. japonica, R. indica, Q. glauca and M. tunbergii demonstrated a high drought resistance of 30 days or longer, whereas C. camphora, D. morbifera and D. macropodum had a low resistance of 25 days or less to drought from lack of water. In conclusion, out of the 7 species of broad-leaved evergreen trees tested, C. japonica, R. indica and Q. glauca seem to be suitable for use as landscape trees, owing to their high drought resistance.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.5
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• pp.64-72
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• 2014

This study quantified the storage and annual uptake of carbon by apple trees in orchards as a production-type greenspace, and computed the annual carbon emissions from apple cultivation. Tree individuals in the study orchards were sampled to include the range of stem diameter sizes. The study measured biomass for each part including the roots of sample trees through a direct harvesting method to compute total carbon storage per tree. Annual carbon uptake per tree was quantified by analyzing the radial growth rates of stem samples at ground level. Annual carbon emissions from management practices such as pruning, mowing, irrigation, fertilization, and use of pesticides and fungicides were estimated based on maintenance data, interviews with managers, and actual measurements. Regression models were developed using stem diameter at ground level (D) as an independent variable to easily estimate storage and annual uptake of the carbon. Storage and annual uptake of carbon per tree increased as D sizes got larger. Apple trees with D sizes of 10 and 15 cm stored 9.1 and 21.0 kg of carbon and annually sequestered 1.0 and 1.6 kg, respectively. Storage and annual uptake of carbon per unit area in study orchards were 3.81 t/ha and 0.42 t/ha/yr, respectively, and annual carbon emissions were 1.30 t/ha/yr. Thus, the carbon emissions were about 3 times greater than the annual carbon uptake. The study identified management practices to reduce the carbon footprint of production-type greenspace, including efficient uses of water, pesticides, fungicides, and fertilizers. It breaks new ground by including measured biomass of roots and a detailed inventory of carbon emissions.

• Korean Journal of Environment and Ecology
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• v.33 no.4
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• pp.472-480
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• 2019

Selection of the plant material for planting to reduce fine dust should comprehensively consider the visual characteristics, such as the shape and texture of the plant leaves and form of bark, which affect the adsorption function of the plant. However, previous studies on reduction of fine dust through plants have focused on the absorption function rather than the adsorption function of plants and on foliage plants, which are indoor plants, rather than the outdoor plants. In particular, the criterion for selection of fine dust reduction species is not specific, so research on the selection criteria for plant materials for fine dust reduction in urban areas is needed. The purpose of this study is to identify the priorities of eight indicators that affect the fine dust reduction by using the fuzzy multi-criteria decision-making model (MCDM) and establish the tree selection criteria for the urban planting to reduce fine dust. For the purpose, we conducted a questionnaire survey of those who majored in fine dust-related academic fields and those with experience of researching fine dust. A result of the survey showed that the area of leaf and the tree species received the highest score as the factors that affect the fine dust reduction. They were followed by the surface roughness of leaves, tree height, growth rate, complexity of leaves, edge shape of leaves, and bark feature in that order. When selecting the species that have leaves with the coarse surface, it is better to select the trees with wooly, glossy, and waxy layers on the leaves. When considering the shape of the leaves, it is better to select the two-type or three-type leaves and palm-shaped leaves than the single-type leaves and to select the serrated leaves than the smooth edged leaves to increase the surface area for adsorbing fine dust in the air on the surface of the leaves. When considering the characteristics of the bark, it is better to select trees that have cork layers or show or are likely to show the bark loosening or cracks than to select those with lenticel or patterned barks. This study is significant in that it presents the priorities of the selection criteria of plant material based on the visual characteristics that affect the adsorption of fine dust for the planning of planting to reduce fine dust in the urban area. The results of this study can be used as basic data for the selection of trees for plantation planning in the urban area.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.417-425
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• 2023

The aim of this study was to derive stem taper equations for Quercus acuta, one of main evergreen broad-leaved tree species found in warm temperate regions, and to prepare a stem volume table using those stem taper equations. A total of 688 individual trees were used in the analysis, which were collected from Jeonnam-do, Gyeongnam-do, and Jeju-do. The stem taper models applied to derive the stem curve pattern were the Max and Burkhart, Kozak, and Lee models. Among the three stem taper models, the best explanation of the stem curve shape of Q. acuta was found to be given by the Kozak model, which showed a fitness index of 0.9583, bias of 0.0352, percentage of estimated standard error of 1.1439, and mean absolute deviation of 0.6751. Thus, the stem taper of Q. acuta was estimated using the Kozak model. Moreover,thestemvolumecalculationwasperforme d by applying the Smalian formula to the diameter and height of each stem interval. In addition, an analysis of variance (ANOVA) was conducted to compare the two existing Q. acuta stem volume tables (2007 and 2010) and the newly created stem volume table (2023). This analysis revealed that the stem volume table constructed in the Wando region in 2007 included about twice as much as the stem volume tables constructed in 2010 and 2023. The stem volume table (2023) developed in this study is not only based on the regional collection range and number of utilized trees but also on a sound scientific basis. Therefore, it can be used at the national level as an official stem volume table for Q. acuta.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.1-19
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• 2013

This study tries to review 'Sakuteiki(作庭記)', the Book of Garden Making, compiled at the end of the 11th Century during the Heian Period of Japan, from the East-Asian perspective. 'Sakuteiki' is a Garden Theory Book, the oldest in the world as well as in Asia, and it contains the traditional knowledge of Japanese ancient garden culture, which originated from the continent(Korea and China). Traditional knowledge related to East-Asian garden culture reviewed in this paper is "Fungsu Theory"(風水, Asian traditional ecology: Fengshui in Chinese; Fusui in Japanese), stemmed from the culture to seek sound and blessed places to live in. Viewed from modern landscape architecture, the Fungsu Theory corresponds to ecology(science). The Fungsu Theory was established around the Han Dynasty of China together with the Yinyangwuxing(陰陽五行) Theory and widely used for making human residences including gardens. It was transmitted to Japan via Korea as well as through direct transaction between Japan and China. This study reinterprets garden design principles represented in Sakuteiki, which were selected in 5 key words according to the Fungsu Theory. The 5 key words for the Fungsu Theory are "the place in harmony of four guardian gods(四神相應地)", "planting trees in the four cardinal directions", "flow of Chi(氣)", "curved line and asymmetry", and "mountain is the king, water is the people". Garden design principles of "the place in harmony of four guardian gods(四神相應地)" and "planting trees in the four cardinal directions" are corresponding to "Myeongdang-ron(明堂論, Theory of propitious site)". The place in harmony of four guardian gods mentioned in Sakuteiki is a landform surrounded by the flow of water to the east, the great path to the west, the pond to the south, and the hill to the north. And the Theory originated from Zhaijing(宅經, Classic of dwelling Sites) of China. According to this principle, the city was planned and as a miniature model, the residence of the aristocrat during the Heian period was made. At the residence the location of the garden surrounded by the four gods(the flow of water, the great path, the pond, and the hill) is the Myeongdang(明堂, the propitious site: Mingtang in Chinese; Meido in Japanese). Sakuteiki explains how to substitute for the four gods by planting trees in the four cardinal directions when they were not given by nature. This way of planting originated from Zhaijing(宅經) and also goes back to Qiminyaoshu (齊民要術), compiled in the 6th Century of China. In this way of planting, the number of trees suggested in Sakuteiki is related to Hetu(河圖) and Luoshu(洛書), which are iconography of Yi(易), the philosophy of change, in ancient China. Such way of planting corresponds to that of Yongdoseo(龍圖墅, the villa based on the principle of Hetu) presented in Sanrimgyeongje (山林經濟), an encyclopedia on agriculture and living in the 17th Century of Korea. And garden design principles of "the flow of Chi(氣)", "curved line and asymmetry" is connected to "Saenggi Theory(生氣論, Theory of vitality)". Sakuteiki explains the right flow of Chi(氣) through the proper flow and the reverse flow of the garden stream and also suggests the curved line of the garden stream, asymmetric arrangement of bridges and stones in the garden, and indented shape of pond edges, which are ways of accumulating Chi(氣) and therefore lead to "Saenggi Theory" of the Fungsu Theory. The last design principle, "mountain is the king, water is the people", is related to "Hyeongguk Theory(形局論, Theory of form)" of the Fungsu Theory. Sakuteiki explains the meaning of garden through a metaphor, which views mountain as king, water as the people, and stones as king's retainers. It compares the situation in which the king governs the people with the help of his retainers to the ecological phenomena in which mountain(earth) controls water with the help of stones. This principle befits "Hyeongguk Theory(形局論, Theory of form)" of the Fungsu Theory which explains landform on the analogy of social systems, people, animals and things. As above, major garden design principles represented in Sakuteiki can be interpreted in the context of the Fungsu Theory, the traditional knowledge system in East Asia. Therefore, we can find the significance of Sakuteiki in that the wisdom of ancient garden culture in East-Asia was integrated in it, although it described the knowhow of a specific garden style in a specific period of Japan.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

• Journal of the Korean Geographical Society
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• v.29 no.3
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• pp.233-252
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• 1994

One of major advantages of Lumped model is its ability to simulate extended flows. A further advantage is that it requires only conventional, readily available hydrological data (rainfall, evaporation and runoff). These two advantages commend the use of this type of model for the analysis of the hydrological effects of landuse change. Experimental Catchment(K11) of Kimakia site in Kenga experienced three phases of landuse change for sixteen and half years. The Institute of Hydrology offered the hydrological data from the catchment for this research. On basis of Blackie's(l972) 9-parameter model, a new model(R1131) was reorganized in consideration of the following aspects to reflect the hydrological characteristics of the catchment: 1) The evapotranspiration necessary for the landuse hydrology, 2) high permeable soils, 3) small catchment, 4) input option for initial soil moisture deficit, and 5) othel modules for water budget analysis. The new model is constructed as a 11-parameter, 3-storage, 1-input option model. Using a number of initial conditions, the model was optimized to the data of three landuse phases. The model efficiencies were 96.78%, 97.20%, 94.62% and the errors of total flow were -1.78%, -3.36%, -5.32%. The bias of the optimized models were tested by several techniques, The extended flows were simulated in the prediction mode using the optimized model and the data set of the whole series of experimental periods. They are used to analyse the change of daily high and low-flow caused by landuse change. The relative water use ratio of the clearing and seedling phase was 60.21%, but that of the next two phases were 81.23% and 83.78% respectively. The annual peak flows of second and third phase at a 1.5-year return period were decreased by 31.3% and 31.2% compared to that of the first phase. The annual peak flow at a 50-year return period in the second phase was an increase of only 4.8%, and that in the third phase was an increase of 12.9%. The annual minimum flow at a 1.5-year return period was decreased by 34.2% in the second phase, and 34.3% in the third phase. The changes in the annual minimum flows were decreased for the larger return periods; a 20.2% decrease in the second phase and 20.9% decrease in the third phase at a 50-year return period. From the results above, two aspects could be concluded. Firstly, the flow regime in Catchment K11 was changed due to the landuse conversion from the clearing and seedling phade to the intermediate stage of pine plantation. But, The flow regime was little affected after the pine trees reached a certain height. Secondly, the effects of the pine plantation on the daily high- and low-flow were reduced with the increase in flood size and the severity of drought.