• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.282-285
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• 2007

Satellite observed brightness temperature simulation using a radiative transfer model (here after, RTM) is useful for various fields, for example sensor design and channel selection by using theoretically calculated radiance data, development of satellite data processing algorithm and algorithm parameter determination before launch. This study is focused on elaborating the simulation procedure, and analyzing of difference between observed and modelled clear sky brightness temperatures. For the CMDPS (COMS Meteorological Data Processing System) development, the simulated clear sky brightness temperatures are used to determine whether the corresponding pixels are cloud-contaminated in cloud mask algorithm as a reference data. Also it provides important information for calibrating satellite observed radiances. Meanwhile, simulated brightness temperatures of COMS channels plan to be used for assessing the CMDPS performance test. For these applications, the RTM requires fast calculation and high accuracy. The simulated clear sky brightness temperatures are compared with those of MTSAT-1R observation to assess the model performance and the quality of the observation. The results show that there is good agreement in the ocean mostly, while in the land disagreement is partially found due to surface characteristics such as land surface temperature, surface vegetation, terrain effect, and so on.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.88-91
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• 2008

The COMS IMPS (Communication Ocean and Meteorological Satellite IMage Pre-processing Subsystem) is developed for image pre-processing of COMS. For a test of the COMS IMPS, 7 support software are developed in KARI GS using simulated MI/GOCI WB (Wide-Band) data; COMS Fill Adder, MI (Meteorological Imager) CADU generator, GOCI (Geostationary Ocean Colour Imager) CADU generator, COMS CADU combiner, MI SD (Sensor Data) analyzer, GOCI SD analyzer, and COMS DM (Decomposition Module) test harness. This paper explains functions of developed support software and the COMS IMPS test using those software.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.6
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• pp.1327-1332
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• 2011

In the mobile meteorological information services, an existing sensor system should be expanded to serve precise information. This is because of large cost problem to add the existing sensors. This thesis proposes a system architecture to construct scalable mobile meteorological information services and suggests mobile phone, sensor network, and public traffic vehicle as expended sensors. The proposed scalable sensors are compared each other and analysed the results to evaluated their strength and weakness. In this system, based on the characteristics of the sense data collected at server, a data processing methods are proposed to support efficient query processing. The proposing data processing methods have several benefits. They compress some data volume sensed by various sources on some area at some time to a logical unit. Still it could preserve same services quality.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.371-382
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• 2005

We present a processing system for the Atmospheric Infrared Sounder (AIRS) sounding suite onboard Aqua satellite. With its unprecedented 2378 channels in IR bands, AIRS aims at achieving the sounding accuracy of radiosonde (1 K in 1-km layer for temperature and $10\%$ in 2-km layer for humidity). The core of the processor is the International MODIS/AIRS Processing Package (IMAPP) that performs the geometric and radiometric correction for generation of Level 1 brightness temperature and Level 2 geophysical parameters retrieval. The processor can produce automatically from received raw data to Level 2 geophysical parameters. As we process the direct-broadcast data almost for the first time among the AIRS direct-broadcast community, a special attention is paid to understand and verify the Level 2 products. This processor includes sub-systems, that is, the near real time validation system which made the comparison results with in-situ measurement data, and standard digital information system which carry out the data format conversion into GRIdded Binary II (GRIB II) standard format to promote active data communication between meteorological societies. This processing system is planned to encourage the application of geophysical parameters observed by AIRS to research the aqua cycle in the Korean peninsula.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.457-460
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• 2011

For the mobile meteorological services, sensed data should be gathered at a server from various clients like as Ubiquitous Sensor Network, mobile phone or public traffic vehicle by wireless network. The gathered data at server have huge volume and increase continuously. Therefore, a special query method and data structure should be considered. This paper studies on all possible query type on the data and processing steps for the mobile meteorological services. Some query spaces will be discussed. After that, this paper proposes effective data structure for the sensed data to support the query types.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.79-93
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• 2012

This paper suggests a system architecture for the advanced meteorological satellite image processing system that is developing by NMSC(National Meteorological Satellite Center). The meteorology satellite image processing system has basically the image acquisition, the image processing, the data management, and the data dissemination functionalities. However, the existing system has some problems with respect to system integration as well as maintenance to accommodate new satellites and/or the new image processing systems for them which will be developed in the near future. To cope with these problems we propose a new system architecture for the advanced meteorology satellite image processing system. To do this we select as the architectural drivers the quality attributes such as modifiability, inter-operability, extendability, reusability, and platform independency and design the architecture to achieve such quality attributes. We expect that the new approach will solve current issues such as system integration, system dependency, or data management problems and will provide easy ways to incorporate new systems and to maintain them.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.526-533
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• 2014

In this study, we introduce design methodology to develop a guidance for issuing heavy rainfall warning by using both RBFNNs(Radial basis function neural networks) and SVR(Support vector regression) model, and then carry out the comparative studies between two pattern classifiers. Individual classifiers are designed as architecture realized with the aid of optimization and pre-processing algorithm. Because the predictive performance of the existing heavy rainfall forecast system is commonly affected from diverse processing techniques of meteorological data, under-sampling method as the pre-processing method of input data is used, and also data discretization and feature extraction method for SVR and FCM clustering and PSO method for RBFNNs are exploited respectively. The observed data, AWS(Automatic weather wtation), supplied from KMA(korea meteorological administration), is used for training and testing of the proposed classifiers. The proposed classifiers offer the related information to issue a heavy rain warning in advance before 1 to 3 hours by using the selected meteorological data and the cumulated precipitation amount accumulated for 1 to 12 hours from AWS data. For performance evaluation of each classifier, ETS(Equitable Threat Score) method is used as standard verification method for predictive ability. Through the comparative studies of two classifiers, neuro-fuzzy method is effectively used for improved performance and to show stable predictive result of guidance to issue heavy rainfall warning.

• Korean Journal of Remote Sensing
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• v.9 no.1
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• pp.37-49
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• 1993

In this research, the WEF AX and APT(Automatic Picture Transmission) data receiving and image processing software using PC/AT called WADIPS(WEFAX and APT Data Integrated Processing System) Software has been developed. The main functions of WADIPS software are follow : 1) Real time receiving and saving to hard disk of WEFAX and APT data 2) B/W(Black and White) and false color display 3) Image enhancement using histogram stretch and color control 4) 2-4 times zooming 5) Hard copy of data using dithering and patterning 6) Animation 7) File management 8) On line help. WADIPS can be used in the offices or persons need real time meteorological information and education offices to teach the image processing technique and general characteristics of meteorological satellites.

• Proceedings of the KSRS Conference
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• v.1
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• pp.159-162
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• 2006

This paper describes the ground system for COMS (Communication, Ocean, and Meteorological Satellite), the first Korean multi-purposed geostationary satellite, at MSC (Meteorological Satellite Center) in Korea. The overview of COMS MI (Meteorological Imager) will be introduced as well. KMA would implement mission planning for COMS MI operation and receive, process, interpret, disseminate, and archive MI data operationally for domestic and foreign user groups. Major missions of COMS MI are mitigation of natural hazard such as typhoon, dust storm, and heavy rain, and short-term warning of severe weather to protect human health and commerce. Moreover, research of climate variability and long-term changes will be supported. In accordance with those missions, the concept and design of COMPASS (COMS operation and meteorological products application service system), the ground system for COMS MI in MSC, have been setting up since 2004. Currently, COMPASS design is being progressed and will have finished the end of 2006. The development of COMPASS has three phases: first phase is development of fundamental COMPASS components in 2007, second phase is to integrate and test all of the COMPASS components in 2008, and the last phase is to operate COMPASS after COMS In-Orbit Tests in 2009.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.473-478
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• 2013

In this paper, we develop the Heavy Rain Advisory Decision Model based on intelligent neuro-fuzzy algorithm RBFNNs by using KLAPS(Korea Local Analysis and Prediction System) Reanalysis data. the prediction ability of existing heavy rainfall forecasting systems is usually affected by the processing techniques of meteorological data. In this study, we introduce the heavy rain forecast method using the pre-processing techniques of meteorological data are in order to improve these drawbacks of conventional system. The pre-processing techniques of meteorological data are designed by using point conversion, cumulative precipitation generation, time series data processing and heavy rain warning extraction methods based on KLAPS data. Finally, the proposed system forecasts cumulative rainfall for six hours after future t(t=1,2,3) hours and offers information to determine heavy rain advisory. The essential parameters of the proposed model such as polynomial order, the number of rules, and fuzzification coefficient are optimized by means of Differential Evolution.