• Korean Journal of Environment and Ecology
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• v.33 no.5
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• pp.539-551
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• 2019

The purpose of this study is to understand the vegetation structure and ecological characteristics of the coastal forest Pinus thunbergii community in Busan Metropolitan City (BMC) and to establish reference information for the management of the coastal forest in BMC in the future. We set up 97 plots with an area of $100m^2$ each for the analysis and investigation of the vegetation characteristics. The analysis using the TWINSPAN and DCA techniques found seven community groups: Pinus thunbergii-Quercus aliena community, Pinus thunbergii-Eurya japonica(1) community, Pinus thunbergii-Eurya japonica(2) community, Pinus thunbergii-Quercus serrata community, Pinus thunbergii-Camellia japonica(1) community, Pinus thunbergii-Camellia japonica(2) community, and Pinus thunbergii-Eurya japonica-Camellia japonica community. According to the analysis of vegetation structure, Pinus thunbergii was a main dominant species at the canopy layer in all sites while Eurya japonica and Camellia japonica were dominant species at the understory layer. Pinus thunbergii-Quercus serrata community is predicted in the forest succession because of the competition between Pinus thunbergii and Quercus serrata in the canopy layer and the understory layer. As such, it is necessary to observe changes by continually monitoring this community. Tree species with strong salinity tolerance, including Pinus thunbergii, have formed community groups because of the environmental characteristics of coastal forests, strong with salinity tolerance species are forming community groups. Therefore, all community groups except for the Pinus thunbergii-Quercus serrata community will maintain the current vegetation structure unless drastic environmental changes occur.

• Composites Research
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• v.34 no.5
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• pp.317-322
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• 2021

When a complex load such as torsion, low-speed impact, or fatigue load is applied, the properties in the thickness direction are weakened through microcracks inside the material due to the nature of the laminated composite material, and delamination occurs. To prevent the interlaminar delamination, various three-dimensional reinforcement methods such as Z-pinning and stitching, and structural health monitoring techniques that detect the microcrack of structures in real time have been continuously studied. In this paper, the single-lap joints with I-fiber stitching process were manufactured by a co-curing method and their strengths and failure detection capability were evaluated. AE and electric resistance method were used for detection of crack and failure signal and electric circuit for signal analysis was manufactured, and failure signal was analyzed during the tensile test of a single-lap joint. From the experiment, the strength of the single lap joint reinforced by I-fiber stitching process was improved by about 44.6% compared to the co-cured single lap joint without reinforcement. In addition, as the single-lap joint reinforced by I-fiber stitching process can detect failure in both the electrical resistance method and the AE method, it has been proven to be an effective structure for failure monitoring as well as strength improvement.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.223-233
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• 2021

Systematic and continuous monitoring and management of the energy consumption of buildings are important for estimating building energy efficiency, and ultimately aim to cope with climate change and establish effective policies for environment, and energy supply and demand policies. Globally, buildings consume 36% of total energy and account for 39% of carbon dioxide emissions. The purpose of this study is to generate three-dimensional thermo-spatial building models with photogrammetric technique using drone TIR (Thermal Infrared) images to measure the temperature emitted from a building, that is essential for the building energy rating system. The aerial triangulation was performed with both optical and TIR images taken from the sensor mounted on the drone, and the accuracy of the models was analyzed. In addition, the thermo-spatial models of temperature distribution of the buildings in three-dimension were visualized. Although shape of the objects 3D building modeling is relatively inaccurate as the spatial and radiometric resolution of the TIR images are lower than that of optical images, TIR imagery could be used effectively to measure the thermal energy of the buildings based on spatial information. This paper could be meaningful to present extension of photogrammetry to various application. The energy consumption could be quantitatively estimated using the temperature emitted from the individual buildings that eventually would be uses as essential information for building energy efficiency rating system.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.291-304
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• 2021

Updating a forest type map is essential for sustainable forest resource management and monitoring to cope with climate change and various environmental problems. According to the necessity of efficient and wide-area forestry remote sensing, CAS500-4 (Compact Advanced Satellite 500-4; The agriculture and forestry satellite) project has been confirmed and scheduled for launch in 2023. Before launching and utilizing CAS500-4, this study aimed to pre-evaluation the possibility of satellite-based tree species classification using RapidEye, which has similar specifications to the CAS500-4. In this study, the study area was the Chuncheon forest management complex, Gangwon-do. The spectral information was extracted from the growing season image. And the GLCM texture information was derived from the growing and non-growing seasons NIR bands. Both information were used to classification with random forest machine learning method. In this study, tree species were classified into nine classes to the coniferous tree (Korean red pine, Korean pine, Japanese larch), broad-leaved trees (Mongolian oak, Oriental cork oak, East Asian white birch, Korean Castanea, and other broad-leaved trees), and mixed forest. Finally, the classification accuracy was calculated by comparing the forest type map and classification results. As a result, the accuracy was 39.41% when only spectral information was used and 69.29% when both spectral information and texture information was used. For future study, the applicability of the CAS500-4 will be improved by substituting additional variables that more effectively reflect vegetation's ecological characteristics.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.595-603
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• 2018

This study was conducted to understand the growth of attached microbial community in small and medium streams of Gyeonggi-do and the removal efficiency of fluoride with changes in growth. The sites monitoring were carried out for 12 weeks at the P1 and P2(P1 is the point where the discharge water flows. P2 is the downstream point of about 2 km flow), and investigated the water quality and the biomass analysis of the attached microbial community. The growth of the attached microbial community increased up to the 7th investigation, and it was observed that detachment phenomenon occurred. Influencing factors about growth of the attached microbial community were flow rate, velocity, and organic material(T-N & T-P). Meanwhile, fluoride content of attached microbial community also tended to increase until the 7th investigation, and decrease from the 8th. It is assumed that fluoride content has also be reduced with the detachment phenomenon of the attached microbial community. It is expected that this will contribute to the evaluation and management of the use of attached microbial community as a means of stream management. The application of techniques using the attached microbial community should include basic investigation of factors that may affect the growth of the attached microbial community and replacement of the attachment plate according to the time of removal.

• Journal of Wetlands Research
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• v.24 no.4
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• pp.268-287
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• 2022

This study reports newly discovered seven forest wetlands in the western part of the Korean Demilitarized Zone-Civilian Control Zone ecoregion. The wetland assessment criteria proposed by National Arboretum were adopted to evaluate four fields: vegetation and landscape, biogeochemical cycle, hydraulics and hydrology, and social-cultural-historical landscape and disturbances. Among seven wetlands located in Gimpo and Paju, five were of the fallow field type and two were of the natural type. A total of 474 plant species were recorded, including nine rare plants, such as the Carex capricornis Meinsh. ex Maxim. Three forest wetlands were sorted into A-grade, three into B-grade, and one into C-grade. Monitoring forest wetlands scattered across the border area ruled by military regulations can be challenging; still, as forest wetlands with high conservation value turned out, further investigations through remote sensing and cooperation by the relevant agencies will be required.

• Journal of the Korean Geotechnical Society
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• v.37 no.8
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• pp.25-35
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• 2021

Recently, the ground anchor method is commonly applied with nail and rock bolt to secure the stability of slopes and structures in Korea. Among them, permanent anchor which is used for long-term stability should secure bearing capacity and durability during the period of use. However, according to recent studies, phenomenon such as deformation to slope and the reduction of residual tensile load over time have been reported along the long-term behavior of the anchors. These problems of reducing residual tensile load are expected to increase in the future, which will inevitably lead to problems such as increasing maintenance costs. In this study, we identified the factors that affect the tensile load of permanent anchor from a literature study on the domestic and foreign, and investigated the prior studies that analyzed previously conducted load cell monitoring data. Afterwards, using this as basic data, the load cell measurement data collected at the actual site were analyzed to identify the tensile load reduction status of anchors, and the long-term load reduction characteristics were analyzed. Finally, by aggregating the preceding results, proposed a technique to predict the long-term load reduction characteristics of permanent anchors through short-term data to around 100 days after installation.

• Journal of Korean Society of Disaster and Security
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• v.14 no.1
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• pp.9-21
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• 2021

Recently, the importance of eco-friendly power generation facility using renewable energy has newly appeared. Hydropower plant is a very important source of electricity generation and supply which is very important to secure safety because it is commonly connected with multi facility and operated on a large scale. In this study, a scenario-based analysis method was suggested to assess vulnerability of a penstock system caused by water hammer commonly occurred in the operation of hydropower plants. A hypothetical hydropower plant was used to demonstrate the applicability of a transient analysis model. In order to verify reliability of the model, the prediction of pressure behaviors were compared with the results of commercial model (SIMSEN) and measured data, then a real hydroelectric power plant was applied to develop all potential water hammer scenarios during the actual operation. The scenario-based simulation and vulnerability assessment for water hammer in the penstock system were performed with internal and external load conditions. The simulation results indicated that the vulnerability of a penstock system was varied with the operating conditions of hydropower facilities and significantly affected by load combination consisting of different load scenarios. The proposed numerical method could be an useful tool for the vulnerabilityty assessment of the hydropower plants due to water hammer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.257-266
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• 2021

Urban areas can often suffer flood damage because of the more frequent catastrophic rainfall events from climate change. Flood mitigation measures consist of (1) structural and (2) non-structural measures. In this study, the proposed method focused on operating an urban drainage system among non-structural measures. The combined inland-river operation technique estimates the inflow of pump stations based on the water level obtained from a preselected monitoring point, and the pump station expels the stored rainwater to the riverside based on those estimates. In this study, the proposed method was applied to the Mokgam drainage watershed, where catastrophic rainfall events occurred (i.e., 2010- and 2011-years), and severe flood damage was recorded in Seoul. Using the proposed method, the efficiency of flood reduction from the two rainfall events was reduced by 34.9 % and 54.4 %, respectively, compared to the current operation method. Thus, the proposed method can minimize the flood damage in the Mokgam drainage watershed by reserving the additional storage space of a reservoir. In addition, flooding from catastrophic rainfall can be prevented, and citizens' lives and property in urban areas can be protected.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.25-33
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• 2021

With the development of machine learning techniques, various types of data such as vibration, temperature, and flow rate can be used to detect and diagnose abnormalities in machine conditions. In particular, in the field of the state monitoring of rotating machines, the fault diagnosis of machines using vibration data has long been carried out, and the methods are also very diverse. In this study, an experiment was conducted to collect vibration data from normal and abnormal compressors by installing accelerometers directly on rotary compressors used in household air conditioners. Data segmentation was performed to solve the data shortage problem, and the main features for the fault classification model were extracted through the chi-square test after statistical and physical features were extracted from the vibration data in the time domain. The support vector machine (SVM) model was developed to classify the normal or abnormal conditions of compressors and improve the classification accuracy through the hyperparameter optimization of the SVM.