• 대기
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• 제30권2호
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• pp.169-181
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• 2020

We conducted a study on the impact of observation station density; this was done in order to enable the accurate estimation of spatial meteorological variables. The purpose of this study is to help operate an efficient observation network by examining distributions of temperature, relative humidity, and wind speed in a test area of a three-dimensional meteorological observation project in the Yeongdong region in 2019. For our analysis, we grouped the observation stations as follows: 41 stations (for Step 4), 34 stations (for Step 3), 17 stations (for Step 2), and 10 stations (for Step 1). Grid values were interpolated using the kriging method. We compared the spatial accuracy of the estimated meteorological grid by using station density. The effect of increased observation network density varied and was dependent on meteorological variables and weather conditions. The temperature is sufficient for the current weather observation network (featuring an average distance about 9.30 km between stations), and the relative humidity is sufficient when the average distance between stations is about 5.04 km. However, it is recommended that all observation networks, with an average distance of approximately 4.59 km between stations, be utilized for monitoring wind speed. In addition, this also enables the operation of an effective observation network through the classification of outliers.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2011년도 학술발표회
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• pp.15-15
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• 2011

The radar observation system in Japan is operated by two governmental groups: Japan Meteorological Agency (JMA) and the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan. The JMA radar observation network is comprised of 20 C-band radars (with a wavelength of 5.6 cm), which cover most of the Japan Islands and observe rainfall intensity and distribution. And the MLIT's radar observation system is composed of 26 C-band radars throughout Japan. The observed radar echo from each radar unit is first modified, and then sent to the National Bureau of Synthesis Process within the MLIT. Through several steps for homogenizing observation accuracy, including distance and elevation correction, synthesized rainfall intensity maps for the entire nation of Japan are generated every 5 minutes. The MLIT has recently launched a new radar observation network system designed for flash flood observation and forecasting in small river basins within urban areas. It is called the X-band multi parameter radar network, and is distinguished by its dual polarimetric wave pulses of short length (3cm). Attenuation problems resulting from the short wave length of radar echo are strengthened by polarimetric wavelengths and very dense radar networks. Currently, the network is established within four areas. Each area is observed using 3-4 X-band radars with very fine resolution in spatial (250 m) and temporal (1 minute intervals). This study provides a series of utilization procedures for the new input data into a real-time forecasting system. First of all, the accuracy of the X-band radar observation was determined by comparing its results with the rainfall intensities as observed by ground gauge stations. It was also compared with conventional C-band radar observation. The rainfall information from the new radar network was then provided to a distributed hydrologic model to simulate river discharges. The simulated river discharges were evaluated again using the observed river discharge to estimate the applicability of the new observation network in the context of operations regarding flood forecasting. It was able to determine that the newly equipped X-band polarimetric radar network shows somewhat improved observation accuracy compared to conventional C-band radar observation. However, it has a tendency to underestimate the rainfall, and the accuracy is not always superior to that of the C-band radar. The accuracy evaluation of the X-band radar observation in this study was conducted using only limited rainfall events, and more cases should be examined for developing a broader understanding of the general behavior of the X-band radar and for improving observation accuracy.

• 천문학회보
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• 제46권2호
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• pp.77.2-77.2
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• 2021

Starting with the observation of sunspots in 1987, Korea Astronomy and Space Science Institute (KASI) has developed and installed various ground-based instruments for space weather research in Korea. Recently, SNIPE and CODEX are also being developed as space-based instruments. Expansion of the observation area and simultaneous observation have become important in the study of space weather. We have started Next-Generation Space Weather Observation Network Project this year. In order to establish a solar observation network, we planned to develop the Next Solar Telescope (NxST) which is a solar imaging spectrograph, and to install three NxST in the northern hemisphere. And we also planned to develop the Thermosphere-Ionosphere-Mesosphere Observation System (TIMOS), Global Navigation Satellite System (GNSS), and Geomagnetic packages, and install them in about ten sites over the world, for the purpose of establishing a global observation network for the near-earth space weather. We can take simultaneously observed space weather data in the global area, and are expecting it will play an important role in the international community for space weather research. We also have a strategy to secure observational technologies necessary for big space missions in the future, through this project.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.592-597
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• 2003

In this paper, some differential geometric conditions for the observer using a recurrent neural network are provided in terms of a stochastic nonlinear system control. In the stochastic nonlinear system, it is necessary to make an additional condition for observation of stochastic nonlinear system, called perfect filtering condition. In addition, we provide a observer using a recurrent neural network for the observation of a stochastic nonlinear system with the proposed observation conditions. Computer simulation shows that the control performance of the stochastic nonlinear system with a observer using a recurrent neural network satisfying the proposed conditions is more efficient than the conventional observer as Kalman filter

• 천문학회보
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• 제44권2호
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• pp.60.2-60.2
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• 2019

Based on our experience on exoplanet transit observation, we propose the exoplanet science cases with Small Telescope Network. One is the follow-up observation for validation of exoplanet candidates. TESS(Transiting Exoplanet Survey Satellite) is pouring out exoplanet candidates in bright stars(V<15) on all the sky. Since Small Telescope Network will consist of 0.5-1m telescopes, we will expect to produce promising outcomes from the follow-up observation of bright candidates. Next is the transit time observation. By spectroscopy of space and large telescopes during transit event, it can be possible to find the bio signatures in exoplanet atmosphere. So, in terms of cost, it is critical to determine the exact time of transit event. In addition, detecting the variation of transit time can reveal another exoplanet and exomoon in the system. In order to determine the transit time and its variation, the accumulation of transit event data is more important than the quality of photometric data. We expect that it can be a challenging project of Small Telescope Network.

• IEIE Transactions on Smart Processing and Computing
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• 제6권2호
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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.

• Journal of Ecology and Environment
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• 제47권4호
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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.

• 한국환경과학회지
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• 제31권4호
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• pp.357-363
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• 2022

In this study, we installed a weather observation tower tailored to the intertidal zone and established an intertidal weather observation system capable of real-time monitoring through a wireless network. This provided weather observation data representing the meteorological characteristics of the intertidal zone. To optimize this system in the future, we present practical directions for the development of observation equipment and for the data management and sharing, and we contribute to establishing the infrastructure.

• 한국농공학회논문집
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• 제61권2호
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• pp.63-74
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• 2019

The objective of this study was to evaluate the influence of rainfall observation network on daily dam inflow using artificial neural networks(ANNs). Chungju Dam and Soyangriver Dam were selected for the study watershed. Rainfall and dam inflow data were collected as input data for construction of ANNs models. Five ANNs models, represented by Model 1 (In watershed, point rainfall), Model 2 (All in the Thiessen network, point rainfall), Model 3 (Out of watershed in the Thiessen network, point rainfall), Model 1-T (In watershed, area mean rainfall), Model 2-T (All in the Thiessen network, area mean rainfall), were adopted to evaluate the influence of rainfall observation network. As a result of the study, the models that used all station in the Thiessen network performed better than the models that used station only in the watershed or out of the watershed. The models that used point rainfall data performed better than the models that used area mean rainfall. Model 2 achieved the highest level of performance. The model performance for the ANNs model 2 in Chungju dam resulted in the $R^2$ value of 0.94, NSE of 0.94 $NSE_{ln}$ of 0.88 and PBIAS of -0.04 respectively. The model-2 predictions of Soyangriver Dam with the $R^2$ and NSE values greater than 0.94 were reasonably well agreed with the observations. The results of this study are expected to be used as a reference for rainfall data utilization in forecasting dam inflow using artificial neural networks.

• 한국지리정보학회지
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• 제25권4호
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• pp.200-209
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• 2022

실시간 위치 정보를 제공하는 것이 국가산업의 주요한 목표로 부상하고 있는 실정이다. 이러한 실시간 위치 정보(3차원 공간 정보)를 제공하기 위해서는 위성 측위 방법의 기술 발달이 필수적이다. 그래서 국가에서는 Network RTK GNSS방식을 도입하여, 수요자의 요구에 만족도를 증가시키는 노력을 지속적으로 하고 있다. 본 연구에서는 국토지리정보원에서 제공하고 있는 Network RKT GNSS(Global Navigation Satellite System) 방식 중 VRS(Virtual Reference Station)과 FKP(Flachen-Korrektur Parameter)을 이용하여 통합기준점에서 연속 관측과 단독 관측을 측량하여 정확도 평가를 하였다. 또한 현장에서 급속하게 증가하고 있는 Network RTK GNSS 방법에 대하여 정확도를 제시하여 효율성을 극대화하고자 한다.