• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.309-314
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• 2013

The concentration of terpene (18 species) was measured from spring to fall in ambient air and essential oil at three different forests located in Jeollanamdo province. Sampling was conducted at 4-hour-interval a day of each season. In the ambient air, ${\alpha}$-pinene, ${\beta}$-pinene and 2-carene were the most abundant compounds throughout the sampling periods and areas. The highest three-season average concentration of total terpene was 2,597 pptv at Jeamsan(Mt.) in Boseong which was predominantly populated by Pinaceae. The seasonal averages were observed to peak during spring with their max at Palyeongsan(Mt.) in Goheung and Jeamsan(Mt.) in Boseong, and during fall at Woodland in Jangheung. Most of terpenes had diurnal variations with higher concentrations during the daytime, and lower during the nighttime. However in essential oil, the highest annual average concentration of total terpene was $798{\mu}g/dry-g$ at Goheung which was predominantly populated by Chamaecyparis obtusa. Also, the component proportion ratio showed different distribution between ambient air and essential oil. From the results of this study, we suggest that Chamaecyparis obtusa species is more useful, and younger tree is more economical than older one, and spring is the best season for lumbering in order to use essential oil.

• Korean journal of applied entomology
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• v.57 no.3
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• pp.209-220
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• 2018

Mating disruption (MD) has been widely used to effectively control Grapholita molesta in apple orchards. A simultaneous mating disruption (SMD) techniques have been developed to control both G. molesta and G. dimorpha. This study was performed to determine the practical parameters to apply the SMD technique to field conditions. To determine the application amount of SMD lures, a dispenser containing 10 mg pheromone was placed at different numbers of trees in an orchard. Application at every other tree (= one dispenser per two trees) was relatively safe to expect effective MD efficiency in both wax and polyethylene (PE) formulations. One time application at the end of March was enough to maintain a year round MD efficacy against both species. A fence treatment using food trap was applied to prevent any immigratory mated females from nearby untreated regions. To enhance the food trap by adding host-derived secondary compounds, terpinyl acetate (TA) was screened to be effective to attract females of Grapholita molesta among six compounds contained in apple fruit extracts. Among different TA concentrations, 0.05% TA treatment was the most effective to attract the adults. A mixture of TA and sugar was effective to attract and kill females and called FAKT (female attract-to-kill techniques). FAKT was treated at approximately 6 m interval at the edge of the apple orchards. The females trapped by the FAKT included mated females possessing vitellogenic oocytes. SMD supplemented with FAKT maintained the high MD efficacy and significantly suppressed leaf damage induced by the two insect pests compared to control or single SMD treatment.

• Korean Journal of Environment and Ecology
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• v.36 no.2
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• pp.118-138
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• 2022

This study was conducted to identify the vegetation structure of major vegetation by region and elevation in the subalpine zone of Seoraksan National Park and prepare an inventory of flora. We reviewed the results of the previous subalpine studies and, through a preliminary survey, determined that the first appearance point of subalpine vegetation was about 800 m based on the south. Then we conducted a site survey by installing a total of 77 plots, including 12 plots on the northern Baekdamsa-Madeungnyeong trail (BD), 13 plots on the west Hangyeryeong-Kkeutcheong trail (HG), 13 plots on the east side of Sinheungsa-Socheongbong trail (SA), and 39 plots in the southern Osaek-Kkeutcheong, Osaek-Daecheongbong trail (OS), in an interval of 50 m above sea level. The analysis classified 7 communities, including Qercus mongolica-Abies holophylla-Acer pseudosieboldianumcommunity, Q. mongolica-Tilia amurensiscommunity, Q. mongolica-Pinus koraiensiscommunity, Q. mongolica-A. pseudosieboldianumcommunity, Betula ermanii-A. nephrolepiscommunity, P. koraiensis-A. nephrolepiscommunity, and mixed deciduous broad-leaf tree community according to the species composition based on the appearance of the major subalpine plants such as Quercus mongolica, Betula ermanii, and Abies nephrolepis, region, and elevation. 10.68±2.98 species appeared per plot (100 m²), and 110.87±63.89 individuals were identified. The species diversity analysis showed that the subalpine vegetation community of Seoraksan National Park was a mixed forest in which various species appeared as important species. Although there was a difference in the initial elevation for the appearance of major subalpine plants by region, they were distributed intensively in the elevation range of 1,100 to 1,300 m. In the Seoraksan National Park, 322 taxa, 83 families, 193 genera, 196 species, 1 subspecies, 26 varieties, and 4 forms of vascular plants were identified. One taxon of Trientalis europaeavar.arcticawas identified as the protected species. The endemic plants were 19 taxa, and 58 taxa were identified as subalpine plants.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.1-14
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• 2022

To alleviate the urban heat island phenomenon, this study aims to quantitatively analyze the effects of neighborhood green spaces on the improvement of the thermal environment based on detailed scenarios of five types of green spaces, including parks, pocket parks, parking lot greening, roadside planting, and rooftop-wall greening. The ENVI-met 4.4.6v model, a microclimate simulation program, was used to analyze the effects of green spaces. As a result, it was found that the air temperature decreased as the planting density of the park increased, but the thermal comfort index PET, which is the degree of heat sensation felt by humans, was not directly proportional to temperature. The establishment of a pocket park reduced air temperature up to a radius of 56m, while the range of temperature reduction increased by about 12.5% when three additional pocket parks were established at 250m intervals. Unlike the air temperature, PET was only affected in the vicinity of the planted area, so there was no significant difference in the thermal comfort of the surrounding environment due to the construction of pocket parks. Changing the surface pavement from asphalt to lawn blocks and implementing rooftop or wall greening did not directly act as solar shading but positively affected air temperature reduction; PET showed no significant difference. Roadside planting showed a higher air temperature reduction effect as the planting interval was narrower, but PET was not directly proportional to tree density. In the case of shrub planting under trees, it did not significantly affect the air temperature reduction but positively affected the improvement of thermal comfort. This study can outline strategies for constructing neighborhood green spaces to solve the urban heat island phenomena and establish detailed strategies for efficient thermal environment improvements.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1779-1790
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• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.1-9
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• 2006

Regardless of the recent observed warmer winters in Korea, more freeze injuries and associated economic losses are reported in fruit industry than ever before. Existing freeze-frost forecasting systems employ only daily minimum temperature for judging the potential damage on dormant flowering buds but cannot accommodate potential biological responses such as short-term acclimation of plants to severe weather episodes as well as annual variation in climate. We introduce 'dormancy depth', in addition to daily minimum temperature, as a complementary criterion for judging the potential damage of freezing temperatures on dormant flowering buds of grape vines. Dormancy depth can be estimated by a phonology model driven by daily maximum and minimum temperature and is expected to make a reasonable proxy for physiological tolerance of buds to low temperature. Dormancy depth at a selected site was estimated for a climatological normal year by this model, and we found a close similarity in time course change pattern between the estimated dormancy depth and the known cold tolerance of fruit trees. Inter-annual and spatial variation in dormancy depth were identified by this method, showing the feasibility of using dormancy depth as a proxy indicator for tolerance to low temperature during the winter season. The model was applied to 10 vineyards which were recently damaged by a cold spell, and a temperature-dormancy depth-freeze injury relationship was formulated into an exponential-saturation model which can be used for judging freeze risk under a given set of temperature and dormancy depth. Based on this model and the expected lowest temperature with a 10-year recurrence interval, a freeze risk probability map was produced for Hwaseong County, Korea. The results seemed to explain why the vineyards in the warmer part of Hwaseong County have been hit by more freeBe damage than those in the cooler part of the county. A dormancy depth-minimum temperature dual engine freeze warning system was designed for vineyards in major production counties in Korea by combining the site-specific dormancy depth and minimum temperature forecasts with the freeze risk model. In this system, daily accumulation of thermal time since last fall leads to the dormancy state (depth) for today. The regional minimum temperature forecast for tomorrow by the Korea Meteorological Administration is converted to the site specific forecast at a 30m resolution. These data are input to the freeze risk model and the percent damage probability is calculated for each grid cell and mapped for the entire county. Similar approaches may be used to develop freeze warning systems for other deciduous fruit trees.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.