• Atmosphere
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• v.28 no.2
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• pp.113-121
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• 2018

In order to monitor greenhouse gases including $CO_2$, various types of surface-, aircraft-, and satellite-based measurement projects have been conducted. These data help understand the variations of greenhouse gases and are used in atmospheric inverse modeling systems to simulate surface fluxes for greenhouse gases. CarbonTracker is a system for estimating surface $CO_2$ flux, using an atmospheric inverse modeling method, based on only surface observation data. Because of the insufficient surface observation data available for accurate estimation of the surface $CO_2$ flux, additional observations would be required. In this study, a system that assimilates aircraft $CO_2$ measurement data in CarbonTracker (CT2013B) is developed, and the estimated results from this data assimilation system are evaluated. The aircraft $CO_2$ measurement data used are obtained from the Comprehensive Observation Network for Trace gases by the Airliner (CONTRAIL) project. The developed system includes the preprocessor of the raw observation data, the observation operator, and the ensemble Kalman filter (EnKF) data assimilation process. After preprocessing the raw data, the modeled value corresponding spatially and temporally to each observation is calculated using the observation operator. These modeled values and observations are then averaged in space and time, and used in the EnKF data assimilation process. The modeled values are much closer to the observations and show smaller biases and root-mean-square errors, after the assimilation of the aircraft $CO_2$ measurement data. This system could also be used to assimilate other aircraft $CO_2$ measurement data in CarbonTracker.

• Atmosphere
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• v.29 no.5
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• pp.511-523
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• 2019

A new Korean Meteorological Administration (KMA) airborne measurement platform has been established for regular observations for scientific purpose over South Korea since late 2017. CRDS G-2401m analyzer mounted on the King Air 350HW was used to continuous measurement of CO₂, CH₄ and CO mole fraction. The total uncertainty of measurements was estimated to be 0.07 ppm for CO₂, 0.5 ppb for CH₄, and 4.2 ppb for CO by combination of instrument precision, repeatability test simulated in-flight condition and water vapor correction uncertainty. The airborne vertical profile measurements were performed at a regional Global Atmosphere Watch (GAW) Anmyeon-do (AMY) station that belongs to the Total Carbon Column Observing Network (TCCON) and provides concurrent observations to the Greenhouse Gases Observing Satellite (GOSAT) overpasses. The vertical profile of CO₂ shows clear altitude gradient, while the CH₄ shows non-homogenous pattern in the free troposphere over Anmyeon-do. Vertically averaged CO₂ at the altitude between 1.5 and 8.0km are lower than AMY surface background value about 7 ppm but higher than that observed in free troposphere of western pacific region about 4 ppm, respectively. CH₄ shows lower level than those from ground GAW stations, comparable with flask airborne data that was taken in the western pacific region. Furthermore, this study shows that the combination of CH₄ distribution in free troposphere and trajectory analysis, taking account of convective mixing, is a useful tool in investigating CH₄ transport processes from tropical region to Korean region in winter season.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1503-1517
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• 2018

Mt. Baekdu is a stratovolcano located at the border between China and North Korea and is known to have formed through its differentiation stage after the Oligocene epoch in the Cenozoic era. There has been a growing interest in the magma re-activity of Mt. Baekdu volcano since 2010. Several research projects have been conducted by government such as Korea Meteorological Administration and Korea Institute of Geoscience and Mineral Resources. Because, however, the Mt. Baekdu volcano is located far from South Korea, it is quite difficult to collect in-situ observations by terrestrial equipment. Remote sensing is a science to analyze and interpret information without direct physical contact with a target object. Various types of platform such as automobile, unmanned aerial vehicle, aircraft and satellite can be used for carrying a payload. In the past several decades, numerous volcanic studies have been conducted by remotely sensed observations using wide spectrum of wavelength channels in electromagnetic waves. In particular, radar remote sensing has been widely used for volcano monitoring in that microwave channel can gather surface's information without less limitation like day and night or weather condition. Radar interferometric technique which utilized phase information of radar signal enables to estimate surface displacement such as volcano, earthquake, ground subsidence or glacial movement, etc. In 2018, long-term research project for collaborative observation for Mt. Baekdu volcano between Korea and China were selected by Korea government. A volcanic specialized research center has been established by the selected project. The purpose of this paper is to introduce about remote sensing techniques for volcano monitoring and to review selected studies with remote sensing techniques to monitor Mt. Baekdu volcano. The acquisition status of the archived observations of six synthetic aperture radar satellites which are in orbit now was investigated for application of radar interferometry to monitor Mt. Baekdu volcano. We will conduct a time-series analysis using collected synthetic aperture radar images.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.17-27
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• 2023

Weeds are one of the factors that reduce crop yield through nutrient and photosynthetic competition. Quantification of weed density are an important part of making accurate decisions for precision weeding. In this study, we tried to quantify the density of weeds in images of maize fields taken by unmanned aerial vehicle (UAV). UAV image data collection took place in maize fields from May 17 to June 4, 2021, when maize was in its early growth stage. UAV images were labeled with pixels from maize and those without and the cropped to be used as the input data of the semantic segmentation network for the maize detection model. We trained a model to separate maize from background using the deep learning segmentation networks DeepLabV3+, U-Net, Linknet, and FPN. All four models showed pixel accuracy of 0.97, and the mIOU score was 0.76 and 0.74 in DeepLabV3+ and U-Net, higher than 0.69 for Linknet and FPN. Weed density was calculated as the difference between the green area classified as ExGR (Excess green-Excess red) and the maize area predicted by the model. Each image evaluated for weed density was recombined to quantify and visualize the distribution and density of weeds in a wide range of maize fields. We propose a method to quantify weed density for accurate weeding by effectively separating weeds, maize, and background from UAV images of maize fields.

• Journal of Practical Agriculture & Fisheries Research
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• v.10 no.1
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• pp.43-58
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• 2008

This research was conducted to determine the alternative tool of chemical spray for rice cultivation using the unmanned helicopter(Yamaha, R-Max Type 2G-remote controlled system) at farmer's field in Korea. The unmanned helicopter tested was introduced form Japan. In Korea the application of chemicals by machine sprayer for pest management in rice cultivation has been ordinarily used at the farmer's level. However, it involved a relatively high cost and laborious for the small scale of cultivation per farm household. Farm population has been highly decreased to 7.5% in 2002 and the population is expected to rapidly reduce by 3.5% in 2012. In Japan, pest control depending on unmanned helicopter has been increased by leaps and bounds. This was due in part to the materialization of the low-cost production technology under agricultural policy and demand environmentally friendly farm products. The practicability of the unmanned helicopter in terms of super efficiency and effectiveness has been proven, and the farmers have understood that the unmanned helicopter is indispensable in the future farming system that they visualized. Also, the unmanned helicopter has been applied to rice, wheat, soybean, vegetables, fruit trees, pine trees for spraying chemicals and/or fertilizers in Japan Effect of disease control by unmanned helicopter was partially approved against rice blast and sheath blight. However, the result was not satisfactory due to the weather conditions and cultural practices. The spray density was also determined in this experiment at 0, 15, 30, and 60cm height from the paddy soil surface and there was 968 spots at 0cm, 1,560 spots at 15cm, 1,923 spots at 30cm, and 2,999 spots at 60cm height. However, no significant difference was found among the treatments. At the same time, there was no phytotoxicity observed under the chemical stray using this unmanned helicopter, nor the rice plant itself was damaged by the wind during the operation.