• Journal of Ecology and Environment
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• v.47 no.4
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• pp.228-240
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• 2023

Growing complexity in ecosystem structure and functions, under impacts of climate and land-use changes, requires interdisciplinary understandings of processes and the whole-system, and accurate estimates of the changing functions. In the last three decades, observation networks for biodiversity, ecosystems, and ecosystem functions under climate change, have been developed by interested scientists, research institutions and universities. In this paper we will review (1) the development and on-going activities of those observation networks, (2) some outcomes from forest carbon cycle studies at our super-site "Takayama site" in Japan, and (3) a few ideas how we connect in-situ and satellite observations as well as fill observation gaps in the Asia-Oceania region. There have been many intensive research and networking efforts to promote investigations for ecosystem change and functions (e.g., Long-Term Ecological Research Network), measurements of greenhouse gas, heat, and water fluxes (flux network), and biodiversity from genetic to ecosystem level (Biodiversity Observation Network). Combining those in-situ field research data with modeling analysis and satellite remote sensing allows the research communities to up-scale spatially from local to global, and temporally from the past to future. These observation networks oftern use different methodologies and target different scientific disciplines. However growing needs for comprehensive observations to understand the response of biodiversity and ecosystem functions to climate and societal changes at local, national, regional, and global scales are providing opportunities and expectations to network these networks. Among the challenges to produce and share integrated knowledge on climate, ecosystem functions and biodiversity, filling scale-gaps in space and time among the phenomena is crucial. To showcase such efforts, interdisciplinary research at 'Takayama super-site' was reviewed by focusing on studies on forest carbon cycle and phenology. A key approach to respond to multidisciplinary questions is to integrate in-situ field research, ecosystem modeling, and satellite remote sensing by developing cross-scale methodologies at long-term observation field sites called "super-sites". The research approach at 'Takayama site' in Japan showcases this response to the needs of multidisciplinary questions and further development of terrestrial ecosystem research to address environmental change issues from local to national, regional and global scales.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.417-421
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• 2006

A comparative study of wind speed spectrum based on the in-situ observation at the SeoHae bridge site is conducted. Wind speed and directions of the SeoHae bridge site is measured and analyzed. Mean wind speed and turbulence intensity are estimated. The power spectral density function of the fluctuating component of the wind velocity is estimated. Several wind spectrum models of gust wind turbulence are compared and discussed based on the estimated wind spectrum.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.195.1-195.1
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• 2012

Korea Aerospace Research Institute has developed an earth observation satellite whose primary mission objective is to provide high resolution electro optical earth images for Geographical Information Systems (GIS) establishment and the applications for environmental, agriculture and ocean monitoring. It was successfully launched into its mission orbit by using a commercial launch vehicle on 18th of May, 2012. This paper describes a series of launch activity at the launch site including its transportation to the launch site. Before conducting the launch site operation, satellite operation plane was prepared. Combining the satellite operation plan and launch vehicle activities, an integrated launch site operation plan and schedule have been drawn up. After arrival of the spacecraft at the launch site, post-ship check out has been conducted. And then it was fuel loaded and integrated with launch vehicle hardware. After completion of final electrical check out, count down procedure was executed. on 18th of May, it was launched into the space and was separated from the launch vehicle as planned. About 3 months of early operation and calibration/validation, now the satellite is conducting its normal mission.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.109-116
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• 2017

In this paper, we propose an Internet of Things (IoT) platform for ocean observation buoys. The proposed system consists of various sensor modules, a gateway, and a remote monitoring site. In order to integrate sensor modules with various communications interfaces, we propose a controller area network (CAN)-based sensor data packet and a protocol for the gateway. The proposed scheme supports the registration and management of sensor modules so as to make it easier for the buoy system to manage various sensor modules. Also, in order to extend communication coverage between ocean observation buoys and the monitoring site, we implement a multi-hop relay network based on a mesh network that can provide greater communication coverage than conventional buoy systems. In addition, we verify the operation of the implemented multi-hop relay network by measuring the received signal strength indication between buoy nodes and by observing the collected data from the deployed buoy systems via our monitoring site.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.615-621
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• 2020

In this paper, we propose a multi-site based earthquake event classification method using graph convolution networks. In the traditional earthquake event classification methods using deep learning, they used single-site observation to estimate seismic event class. However, to achieve robust and accurate earthquake event classification on the seismic observation network, the method using the information from the multi-site observations is needed, instead of using only single-site data. Firstly, our proposed model employs convolution neural networks to extract informative embedding features from the single-site observation. Secondly, graph convolution networks are used to integrate the features from several stations. To evaluate our model, we explore the model structure and the number of stations for ablation study. Finally, our multi-site based model outperforms up to 10 % accuracy and event recall rate compared to single-site based model.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.427-430
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• 2003

Yi-dong experimental site is operated for research on the rural basin characteristics and accumulation of a long term data by hydrological observation equipments. This basin area is 9,300ha, length 14.4km and slope 0.67%. Hydrological observation network has 3 rainfall meter3, 3 reservoir storage levels and 2 river water levels.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.179-185
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• 2020

Recently, in order to improve the performance of the Earthquake Early Warning System (EEWS) and to supplement the effects of earthquake disaster prevention in epicenters or near epicenters, development of on-site EEWS has been attempted. Unlike the national EEWS, which is used for earthquake disaster prevention by using seismic observation networks for earthquake research and observation, on-site EEWS aims at earthquake disaster prevention and therefore requires efficient design and evaluation in terms of performance and cost. At present, Korea lacks the necessary core technologies and operational know-how, including the use of existing EEWS design criteria and evaluation methods for the development of On-Site EEWS as well as EEWS. This study proposes hardware and software design directions and performance evaluation items and methods for seismic data collection, data processing, and analysis for localization of On-Site EEWS based on the seismic accelerometer requirements of the Seismic and Volcanic Disaster Response Act.

• Publications of The Korean Astronomical Society
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• v.19 no.1
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• pp.55-63
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• 2004

Observation environment of the Bohyunsan Optical Astronomy Observatory(BOAO) has been examined using various statistical data including real observation times versus allocated times and seeing statistics. The data have been collected from the observation logs of the 1.8m telescope in the period 1998 - 2004. New criteria have been set up to calculate a more realistic observation efficiency of the observatory. The new statistical analysis based on the new criteria gives the overall observation efficiency of BOAO as $38.6\%$, that is equivalent to 115.8 observable nights out of 300 allocatable nights. The seeing statistics shows that the mean seeing measured at the focal images is 2".3. The present study of the observation environment of BOAO suggests that differential photometry and spectroscopy should be preferred modes of observation to maximize the productivity of BOAO.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.208-209
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• 2019

• Journal of the Korean Society of Marine Environment & Safety
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• v.5 no.1
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• pp.9-18
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• 1999

To predict the oil spill dispersion phenomena in the ocean, the oil spill response model, which can be used for strategic purpose on the oil spill site, based on Lagrangian particle-tracking method was formulated and applied to the neighboring area with Pusan port where the oil spill incident occurred when the tanker ship No.1 Youil struck on a small rock near the Namhyungjeto on September 21, 1995. The real-time tidal currents to be required as input data of the oil spill model were obtained by the two-dimensional hydrodynamic model and the tide prediction model. Evaluation of tidal currents using observation data was successful. For wind data, other input data of oil spill model, observed data on the spot were used. To verify the oil spill model, the oil spill modelling results were compared with the field data obtained from the spill site. Compared the modelling results with the observation data, there exist some discrepancies but the general pattern of modelling results was similar to that of field observation. The modelling results on 7 days after spill occurred showed that the 40% of spilled oil is in floating, 36% in evaporated, 23% at shore, and 1% in out of boundary, respectively. According to the evaluation of weighting curves of effective components to the dispersion of oil, the winds make a 37% of contribution to the dispersion of oil, turbulent diffusion 39.5%, and tidal currents 23.5%, respectively. Provided the more accurate wind data are supported, more favorable results might be obtained.