• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1247-1255
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• 2013

In this paper, We proposes multipurpose function electronic measurement reference station prototype system based on LED and Gyro Sensor. This system have developed to possible with real time data collection and landscape illumination and surrounding diastrophism monitoring for that analyze problems of existing planted reference station. Hardware for the proposed system consists of a gyro sensor module to detect diastrophism, GPS module to process location information, environment sensor module to process surrounding environmental data and CDMA wireless data communication to send the collected data to server. In addition, this paper intends to enhance system management and future usability in a way that applies LED, QR-code, RFID and Solar cell module to outer side of electronic measurement reference station to improve usability of H/W for electronic measurement reference station. Lastly, this paper conducted current amount evaluation to supply stabilized electricity with its various functions in the proposed multipurpose function electronic measurement reference station and it's proved that this system can be stably operated with its electricity loss factor of 2.29% loss factor. And this paper conducted a qualitative comparison with existing electronic measurement reference station system in order to evaluate superiority of the proposed electronic measurement reference station.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.1
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• pp.9-15
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• 2000

The objective of this study is to evaluate the use of RADARSAT and Landsat TM data for the monitoring of rice growth. The relationships between backscatter coefficients($\sigma$$^{0}$ ) of RADARSAT data and digital numbers (DN) of Landsat TM and rice growth parameters were investigated. Radar backscatter coefficients were calculated by calibration process and then compared with rice growth parameters; plant height, leaf area index (LAI), and fresh and dry biomass. When radar backscatter coefficient ($\sigma$$^{0}$ ) of rice was expressed as a function of time, it is shown that the increasing trend ranged from -22--20dB to -9--8dB as growth advances. The temporal variation of backscatter coefficient was significant to interpret rice growth. According to the relationship between leaf area index and backscatter coefficient, backscatter coefficient underestimated leaf area index at the beginning of life history and overestimated, at the reproductive stage. The same increasing trend between biomass and backscatter coefficient was shown. From these results, RADARSAT data appear positive to the monitoring of rice growth. Each band of time-series Landsat TM data had a significant trend as a rice crop grows during its life cycle. Spectral indices, NDVI[(TM4-TM3)/(TM4+TM3)] and RVI(TM4/TM2), derived from Landsat TM equivalent bands had the same trend as leaf area index.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1951-1963
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• 2021

Remote sensing data using earth observation satellites in agricultural environment monitoring has many advantages over other methods in terms of time, space, and efficiency. Since the sensor mounted on the satellite measures the energy that sunlight is reflected back to the ground, noise is generated in the process of being scattered, absorbed, and reflected by the Earth's atmosphere. Therefore, in order to accurately measure the energy reflected on the ground (radiance), atmospheric correction, which must remove noise caused by the effect of the atmosphere, should be preceded. In this study, atmospheric correction sensitivity analysis, inter-satellite cross-analysis, and comparative analysis with ground observation data were performed to evaluate the application of KOMPSAT-3 satellite's atmospheric correction for agricultural application. As a result, in all cases, the surface reflectance after atmospheric correction showed a higher mutual agreement than the TOA reflectance before atmospheric correction, and it is possible to produce the time series vegetation index of the same standard. However, additional research is needed for quantitative analysis of the sensitivity of atmospheric input parameters and the tilt angle.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.95-102
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• 2022

It is a study for the evaluation of the stability of the distribution automation system for the expansion of renewable energy. Through the Renewable Energy 3020 Implementation Plan, the government plans to expand new renewable energy and convert it to participatory energy that improves the quality of life of the people by 2030. The government has set a target of 20% of domestic supply energy for renewable energy generation by 2030. It is planning to establish more than 95 percent of its new facilities with clean energy such as solar power and wind power. By expanding the supply of renewable energy, new energy businesses and distributed power industry were fostered, and short-distance, low-voltage, and small-scale power generation were rapidly expanded rather than large-scale power development in the past. Due to this demand, the importance of power distribution facility operation has emerged and the need for distribution automation system is increasing. This paper discusses the development of a power distribution simulator for the performance and function evaluation of power distribution automation systems and presents the results of an interlocking test with the power distribution automation system. In order to introduce an advanced system into the power distribution system, it is necessary to take advantage of the transmission and distribution system. The DNP3.0 protocol is used in the distribution system and the IEC61850 protocol is used in the transmission and distribution system. It was concluded that the functions and performance of operations were satisfied when these two protocols are mixed and used in the distribution automation system.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.1
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• pp.9-17
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• 2022

Rural spaces are increasingly valuable as areas for introducing renewable energy infrastructure to achieve carbon neutrality. Rural areas are the living grounds of rural residents, and the balance of conservation and development for rural areas is important for the introduction of reasonable facilities. In order to maintain a balance between development and preservation and to introduce reasonable renewable energy facilities, it is necessary to develop a current status survey and an effective survey method to utilize a space capable of introducing renewable energy facilities such as idle land and vacant houses. Therefore, this study was conducted to verify the readability using an unmanned aerial vehicle, and the main results are as follows. The detection of photovoltaic power generation facilities using unmanned aerial vehicles was effective in analyzing the location and area of photovoltaic panels located on the roofs of buildings, and it was possible to calculate the expected power generation by region through the area calculation of photovoltaic panels. The vacant house detection can be used to select an investigation target for an vacant house condition survey as it can identify damage to buildings that are expected to be empty houses, management status, and electricity supply facilities through aerial photos. It is judged that the unmanned aerial vehicle detection capability can be utilized as a method to improve the efficiency of investigation and supplement the data related to solar power generation facilities and vacant houses provided by public institutions. Although this study detected the status of solar power generation facilities and vacant houses through high-resolution aerial image analysis, as a follow-up study, automatic measurement methods using the temperature difference of solar power generation facilities and general characteristics of vacant houses that can be read from the air were investigated. If the deriving research is carried out, it is judged that it will be possible to contribute to the improvement of the accuracy of the detection result using the unmanned aerial vehicle and the expansion of the application range.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.4
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• pp.86-93
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• 2023

A bridge health monitoring technology is under development for the safety management of aged bridges. The bridge health monitoring technology has been developed mainly for single bridge management at a large scale, so it uses wire-based systems for power supply and data transfer. However, the wire-based systems need to be improved for the sporadically distributed small-sized bridges on local roads. This study proposed a wireless structural health monitoring system for small-sized bridges. The proposed monitoring system overcomes the limitations of wired systems by providing wireless power through solar power and utilizing LTE technology to transmit measurement data. In addition, a remote control system and power management plan were proposed to ensure the stability of the bridge measurement system. The proposed measurement system was installed on 32 bridges on fields and verified the operability by collecting 80.6% of measurement data for one year. The proposed system can support the health monitoring of aged bridges on local roads.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.316-328
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• 2021

In this study, the leaf Na content prediction model for spring potato was established using 400-1000 nm hyperspectral sensor to develop the multispectral sensor for the salinity monitoring in reclaimed land. The irrigation conditions were standard, drought, and salinity (2, 4, 8 dS/m), and the irrigation amount was calculated based on the amount of evaporation. The leaves' Na contents were measured 1st and 2nd weeks after starting irrigation in the vegetative, tuber formative, and tuber growing periods, respectively. The reflectance of the leaves was converted from 5 nm to 10 nm, 25 nm, and 50 nm of FWHM (full width at half maximum) based on the 10 nm wavelength intervals. Using the variance importance in projections of partial least square regression(PLSR-VIP), ten band ratios were selected as the variables to predict salinity damage levels with Na content of spring potato leaves. The MLR(Multiple linear regression) models were estimated by removing the band ratios one by one in the order of the lowest weight among the ten band ratios. The performance of models was compared by not only R2, MAPE but also the number of band ratios, optimal FWHM to develop the compact multispectral sensor. It was an advantage to use 25 nm of FWHM to predict the amount of Na in leaves for spring potatoes during the 1st and 2nd weeks vegetative and tuber formative periods and 2 weeks tuber growing periods. The selected bandpass filters were 15 bands and mainly in red and red-edge regions such as 430/440, 490/500, 500/510, 550/560, 570/580, 590/600, 640/650, 650/660, 670/680, 680/690, 690/700, 700/710, 710/720, 720/730, 730/740 nm.

• Korean Journal of Ecology and Environment
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• v.52 no.4
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• pp.293-305
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• 2019

In this study we investigated the effect of a floating photovoltaic (FPV) system in Cheongpung Lake on water quality. The FPV with a tilt angle of 33° covered ca. 0.04% of surface area (97 ㎢) of Chungju Lake. The water qualities of the whole lake before and after installation of FPV were first compared. DO, BOD, TOC, and Chl-a of the whole lake were increased, while conductivity decreased after installation period at the significance level of 0.05. This change was probably due to the increased influx of nutrients by 40% resulting from increased precipitation during the same period. We also measured water quality parameters on May and Nov. 2017 at the FPV center (FPVC) and nearby control sites, and compared water quality. The result showed that the FPVC and nearby sites were not significantly different (p>0.05), demonstrating that the FPV does not cause a decline of water quality. The water temperature, light intensity, and phytoplankton community were also measured. The water temperature was not different between the sites, while the light intensity decreased to 27~50%. Despite reduced light intensity at FPVC, the phytoplankton standing crops and the number of species were not significantly different (p>0.05). However, in the early November samples, standing crops was significantly higher in FPVC than control with periphytic diatoms belonging to Aulacoseira genus being dominant. This may be due to the temporal water body behavior or local retention of current by FPV system. This study may provide a measure of future installation of a FPV system.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.193-205
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• 2023

A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.436-445
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• 2023

Methane (CH₄) emissions from rice paddies are mainly observed using the closed chamber method or the eddy covariance method. In this study, a new observation technique combining a portable gas analyzer (Model LI-7810, LI-COR, Inc., USA) and an automatic opening/closing chamber (Model Smart Chamber, LI-COR, Inc., USA) was introduced based on the strengths and weaknesses of the existing measurement methods. A cylindrical collar was manufactured according to the maximum growth height of rice and used as an auxiliary measurement tool. All types of measured data can be monitored in real time, and CH₄ flux is also calculated simultaneously during the measurement. After the measurement is completed, all the related data can be checked using the software called 'SoilFluxPro'. The biggest advantage of the new observation technique is that time-series changes in greenhouse gas concentrations can be immediately confirmed in the field. It can also be applied to small areas with various treatment conditions, and it is simpler to use and requires less effort for installation and maintenance than the eddy covariance system. However, there are also disadvantages in that the observation system is still expensive, requires specialized knowledge to operate, and requires a lot of manpower to install multiple collars in various observation areas and travel around them to take measurements. It is expected that the new observation technique can make a significant contribution to understanding the CH₄ emission pathways from rice paddies and quantifying the emissions from those pathways.