• 한국정보통신학회논문지
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• 제23권9호
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• pp.1139-1145
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• 2019

한정된 위성통신망 자원을 효율적으로 사용하기 위해서는 통신망에 대한 성능과 사용량을 파악하는 것이 우선이다. 본 논문에서는 K-water 홍수예보 경보망으로 운영 중인 위성통신시스템에서 시스템의 운영 효율성과 안정성을 분석하기 위하여, 중심국과 관측국간에 다운로드 및 업로드의 속도를 측정하는 FTP 및 핑 시험과 네트워크 트래픽 분석 방법을 도입하였다. 도입한 시험방법에 의한 전송속도를 측정한 결과, TCP 가속기의 영향은 관측국에서 다운로드시 120% 속도 향상이 되었으며, 데이터의 크기에 따른 차이가 발생하였고, 트래픽 분석에서는 네트워크상에 접속되는 프로토콜 종류와 사용량을 파악하였다. 도입한 위성수문관측시스템의 성능 시험 및 트래픽 분석을 통하여 위성통신시스템의 환경보완 및 개선점을 도출하여 통신망의 운영 효율성과 안정성 향상을 기대할 수 있도록 하였다.

• 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.

• 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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• Journal of Astronomy and Space Sciences
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• 제36권3호
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• pp.169-180
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• 2019

In this study, a batch least square estimator that utilizes optical observation data is developed and utilized to determine geostationary orbits (GEO). Through numerical simulations, the effects of error sources, such as clock errors, measurement noise, and the a priori state error, are analyzed. The actual optical tracking data of a GEO satellite, the Communication, Ocean and Meteorological Satellite (COMS), provided by the optical wide-field patrol network (OWL-Net) is used with the developed batch filter for orbit determination. The accuracy of the determined orbit is evaluated by comparison with two-line elements (TLE) and confirmed as proper for the continuous monitoring of GEO objects. Also, the measurement residuals are converged to several arcseconds, corresponding to the OWL-Net performance. Based on these analyses, it is verified that the independent operation of electro-optic space surveillance systems is possible, and the ephemerides of space objects can be obtained.

• 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.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권7호
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• pp.2936-2951
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• 2016

An emerging satellite technology, Operationally Responsive Space (ORS) is expected to provide a fast and flexible solution for emergency response, such as target tracking, dense earth observation, communicate relaying and so on. To realize large distance transmission, we propose the use of available relay satellites as relay nodes. Accordingly, we apply software defined network (SDN) technology to ORS networks. We additionally propose a satellite network architecture refered to as the SDN-based ORS-Satellite (Sat) networking scheme (SDOS). To overcome the issures of node failures and dynamic topology changes of satellite networks, we combine centralized and distributed routing mechanisms and propose a fast recovery routing algorithm (FRA) for SDOS. In this routing method, we use centralized routing as the base mode.The distributed opportunistic routing starts when node failures or congestion occur. The performance of the proposed routing method was validated through extensive computer simulations.The results demonstrate that the method is effective in terms of resoving low end-to-end delay, jitter and packet drops.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.278-281
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• 2006

Korea Meteorological Administration(KMA) has issued the tropical storm(typhoon) warning or advisories when it was developed to tropical storm from tropical depression and a typhoon is expected to influence the Korean peninsula and adjacent seas. Typhoon information includes current typhoon position and intensity. KMA has used the Dvorak Technique to analyze the center of typhoon and it's intensity by using available geostationary satellites' images such as GMS, GOES-9 and MTSAT-1R since 2001. The Dvorak technique is so subjective that the analysis results could be variable according to analysts. To reduce the subjective errors, QuikSCAT seawind data have been used with various analysis data including sea surface temperature from geostationary meteorological satellites, polar orbit satellites, and other observation data. On the other hand, there is an advantage of using the Subjective Dvorak Technique(SDT). SDT can get information about intensity and center of typhoon by using only infrared images of geostationary meteorology satellites. However, there has been a limitation to use the SDT on operational purpose because of lack of observation and information from polar orbit satellites such as SSM/I. Therefore, KMA has established Advanced Objective Dvorak Technique(AODT) system developed by UW/CIMSS(University of Wisconsin-Madison/Cooperative Institude for Meteorological Satellite Studies) to improve current typhoon analysis technique, and the performance has been tested since 2005. We have developed statistical relationships to correct AODT CI numbers according to the SDT CI numbers that have been presumed as truths of typhoons occurred in northwestern pacific ocean by using linear, nonlinear regressions, and neural network principal component analysis. In conclusion, the neural network nonlinear principal component analysis has fitted best to the SDT, and shown Root Mean Square Error(RMSE) 0.42 and coefficient of determination($R^2$) 0.91 by using MTSAT-1R satellite images of 2005. KMA has operated typhoon intensity analysis using SDT and AODT since 2006 and keep trying to correct CI numbers.

• Journal of Astronomy and Space Sciences
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• 제33권2호
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• pp.137-146
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• 2016

The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.