• Korean Journal of Remote Sensing
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• v.9 no.1
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• pp.21-35
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• 1993

In this study, an integrated GMS(Geostationary Meteorological Satellite) receiving ground system, which includes the real-time reception and image processing of WEFAX data, has been developed. The demodulator, PC demodulator, PC interface and application softwares of the system were made and integrated with the commercially available antenna and receiver. Hardwars of the system were described in this part. This system operates at IBM PC/AT or above. It can be used for students at school and for application research in the fields of meteorology, oceanography, hydrology and astronomy.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.12
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• pp.1292-1299
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• 2014

Weather radar systems can provide weather information of the ground, sea, and air in extensive spatial coverage in near real time. However, it becomes problematic when ground clutter signal exists around precipitation because strong signals of ground can cause a false precipitation report. A large percentage of land coverage of Korea consists of mountainous regions where ground clutter needs to be mitigated for more accurate prediction. Thus, it is considered necessary to introduce a new suitable ground clutter removal technique specifically adequate for Korea. In this paper, the C-Map(Clutter Map) method using raw radar signals is proposed for removing ground clutter using a terrain-adaptive clutter map. A clutter map is generated using raw radar signals(I/Q) of clear days, then it is subtracted from received radar signals in frequency domain. The proposed method is applied to the radar data acquired from Sobaeksan rain radar and the result shows that the clutter rejection ratio is about 91.17 %.

• Journal of Korea Water Resources Association
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• v.49 no.7
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• pp.625-634
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• 2016

Three leading agencies under different ministries - Korea Meteorological Administration (KMA) in the ministry of Environment, Han river control office in the Ministry of Land, Infrastructure and Transport (MOLIT) and Weather Group of ROK Air Force in the Ministry of National Defense (MND) - have been operated radars in the purpose of observing weather, hydrology and military operational weather in Korea. Eight S-band dual-pol. radars have been newly installed or replaced by these ministries over different places by 2015. However each ministry has different aims of operating radars, observation strategies, data processing algorithms, etc. Due to the differences, there is a wide level of accuracy on observed radar data as well as the composite images made of the cross governmental radar measurement. Gaining fairly high level of accuracy on radar data obtained by different agencies has been shared as a great concern by the ministries. Thus, "an agreement of harmonizing weather and hydrological radar products" was made by the three ministries in 2010. Particularly, this is very important to produce better rainfall estimation using the cross governmental radar measurement. Weather Radar Center(WRC) in KMA has been developed an empirical method using measurements observed by Yongin testbed radar. This study is aiming to examine the efficiency of the empirical method to improve the accuracies of radar rainfalls estimated from cross governmental dual-pol. radar measurements. As a result, the radar rainfalls of three radars (Baengnyeongdo, Biseulsan, and, Sobaeksan Radar) were shown improvement in accuracy (1-NE) up to 70% using data from May to October in 2015. Also, the range of the accuracies in radar rainfall estimation, which were from 30% to 60% before adjusting polarimetric variables, were decreased from 65% to 70% after adjusting polarimetric variables.

• Journal of the Korean Geophysical Society
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• v.3 no.4
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• pp.235-244
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• 2000

We studied basic ideas of a network based Gravity/Magnetic data processing server/client system which provides functions of data processing, forward modeling, inversion and data process on Data Base. This Java technology was used to provide facilities, socket communication and JDBC(Java Database Connectivity) technology to produce an effective and practical client application. The server computers are linked by network to process the MPI parallelized computing. This can provide useful devices of the geophysical process and modeling that usually require massive computing performance and time. Since this system can be accessed by lots of users, it can provides the consistent and confident results through the verified processing programs. This system also makes it possible to get results and outputs through internet when their local machines are connected to the network. It can help many users who want to omit the jobs of system administration and to process data during their field works.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• Atmosphere
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• v.17 no.4
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• pp.339-348
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• 2007

Global Environment Laboratory at Yonsei University in Seoul ($37.57^{\circ}N$, $126.95^{\circ}E$) has carried out the ozone layer monitoring program in the framework of the Global Ozone Observing System of the World Meteorlogical Organization (WMO/GAW/GO3OS Station No. 252) since May of 1984. The daily measurements of total ozone and the vertical distribution of ozone amount have been made with the Dobson Spectrophotometer (No.124) on the roof of the Science Building on Yonsei campus. From 2004 through 2006, major parts of the manual operations are automated in measuring total ozone amount and vertical ozone profile through Umkehr method, and calibrating instrument by standard lamp tests with new hardware and software including step motor, rotary encoder, controller, and visual display. This system takes full advantage of Windows interface and information technology to realize adaptability to the latest Windows PC and flexible data processing system. This automatic system also utilizes card slot of desktop personal computer to control various types of boards in the driving unit for operating Dobson spectrophotometer and testing devices. Thus, by automating most of the manual work both in instrument operation and in data processing, subjective human errors and individual differences are eliminated. It is therefore found that the ozone data quality has been distinctly upgraded after automation of the Dobson instrument.

• Proceedings of the KSRS Conference
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• v.1
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• pp.90-93
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• 2006

The first Geostationary Ocean Color Imager (GOCI) onboard its Communication Ocean and Meteorological Satellite (COMS) is scheduled for launch in 2008. GOCI includes the eight visible-to-near-infrared (NIR) bands, 0.5km pixel resolution, and a coverage region of 2500 ${\times}$ 2500km centered at 36N and 130E. GOCI has had the scope of its objectives broadened to understand the role of the oceans and ocean productivity in the climate system, biogeochemical variables, geological and biological response to physical dynamics and to detect and monitor toxic algal blooms of notable extension through observations of ocean color. The special feature with GOCI is that like MODIS, MERIS and GLI, it will include the band triplets 660-680-745 for the measurements of sun-induced chlorophyll-a fluorescence signal from the ocean. The GOCI will provide SeaWiFS quality observations with frequencies of image acquisition 8 times during daytime and 2 times during nighttime. With all the above features, GOCI is considered to be a remote sensing tool with great potential to contribute to better understanding of coastal oceanic ecosystem dynamics and processes by addressing environmental features in a multidisciplinary way. To achieve the objectives of the GOCI mission, we develop the GOCI Data Processing System (GDPS) which integrates all necessary basic and advanced techniques to process the GOCI data and deliver the desired biological and geophysical products to its user community. Several useful ocean parameters estimated by in-water and other optical algorithms included in the GDPS will be used for monitoring the ocean environment of Korea and neighbouring countries and input into the models for climate change prediction.

• Journal of Positioning, Navigation, and Timing
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• v.5 no.2
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• pp.75-85
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• 2016

The performance of up-to-date mapping functions and various mean temperature equations were analyzed to derive optimal mapping function and mean temperature equation when GNSS precipitable water vapor (PWV) was investigated in the Korean Peninsula. Bernese GNSS Software 5.2, which can perform high precision GNSS data processing, was used for accurate analysis, and zenith total delay (ZTD) required to calculate PWV was estimated via the Precise Point Positioning (PPP) method. GNSS, radiosonde, and meteorological data from 2009 to 2014 were acquired from Sokcho Observatory and used. ZTDs estimated by applying the global mapping function (GMF) and Vienna mapping function 1 (VMF1) were compared with each other in order to evaluate the performance of the mapping functions. To assess the performance of mean temperature equations, GNSS PWV was calculated by using six mean temperature equations and a difference with radiosonde PWV was investigated. Conclusively, accuracy of data processing was improved more when using VMF1 than using GMF. A mean temperature equation proposed by Wu (2003) had the smallest difference with that in the radiosonde in the analysis including all seasons. In summer, a mean temperature equation proposed by Song & Grejner-Brzezinska (2009) had the closest results with that of radiosonde. In winter, a mean temperature equation proposed by Song (2009) showed the closest results with that of radiosonde.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.347-357
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• 2019

The usefulness of processing and analysis systems of GIS-based agricultural climate data is affected by the reliability and availability of computing infrastructures such as cloud, on-premises, and hybrid. Cloud technology has grown in popularity. However, various reference cases accumulated over the years of operational experiences point out important features that make on-premises technology compatible with cloud technology. Both cloud and on-premises technologies have their advantages and disadvantages in terms of operational time and cost, reliability, and security depending on cases of applications. In this study, we have described characteristics of four general computing platforms including cloud, on-premises with hardware-level virtualization, on-premises with operating system-level virtualization and hybrid environments, and compared them in terms of advantages and disadvantages when a huge amount of GIS-based agricultural climate data were stored and processed to provide public services of agro-meteorological and climate information at high spatial and temporal resolutions. It was found that migrating high-resolution agricultural climate data to public cloud would not be reasonable due to high cost for storing a large amount data that may be of no use in the future. Therefore, we recommended hybrid systems that the on-premises and the cloud environments are combined for data storage and backup systems that incur a major cost, and data analysis, processing and presentation that need operational flexibility, respectively.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.319-327
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• 2013

The objective of this research was to develop a relational database management system(RDBMS) to collect, manage and analyze data on agricultural non-point source(NPS) pollution. The system consists of the relational database for agricultural NPS data and data process modules. The data process modules were composed of four sub-modules for data input, management, analysis, and output. The data collected from the watershed of the upper Cheongmi stream and Geunsam-Ri were used in this study. The database was constructed using Apache Derby with meteorological, hydrological, water quality, and soil characteristics. Agricultural NPS-Data Management System(ANPS-DMS) was developed using Oracle Java. The system developed in this study can deal with a variety of agricultural NPS data and is expected to provide an appropriate data management tool for agricultural NPS studies.