• International Journal of Aeronautical and Space Sciences
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• v.10 no.1
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• pp.75-82
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• 2009

In this parer, we propose a new way of improving DGNSS service using combination of multiple SBAS information. Because SBAS uses Geostationary Earth Orbit (GEO) satellites, it has very large coverage but it can be unavailable in urban canyon because of visibility problem. R. Chen solved this problem by creating Virtual Reference Stations (VRS) using the SBAS signal [1]. VRS converts SBAS signal to RTCM signals corresponding its location, and broadcast the converted RTCM signals over the wireless internet. This method can solve the visibility problem cost effectively. Furthermore it can solve DGNSS coverage problem by creating just a transmitter instead of a reference station. Developing above method, this paper proposes the methods that integrate two or more SEAS signals into one RTCM signal and broadcast it. In Korea, MSAS signal is available even though it is not officially certified for Korean users. As a Korean own SBAS-like system, there is the internet-based KWTB (Korean WADGPS Test Bed) which we developed and released at ION GNSS 2006. As a result, virtually two different SBAS corrections are available in Korea. In this paper, we propose the integration methods for these two independent SBAS corrections and present the test results using the actual measurements from the two systems. We present the detailed algorithm for these two methods and analyze the features and performances of them. To verify the proposed methods, we conduct the experiment using the logged SBAS corrections from the two systems and the RINEX data logged at Dokdo monitoring station in Korea. The preliminary test results showed the improved performance compared to the results from two independent systems, which shows the potential of our proposed methods. In the future, the newly developed SBASs will be available and the places which can access the multiple SBAS signals will increase. At that time, the integration or combination methods of two or more SBASs will become more important. Our proposed methods can be one of the useful solutions for that. As an additional research, we need to extend this research to the system level integration such as the concept of the decentralized W ADGPS.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.3
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• pp.154-167
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• 2014

The results of this study conducted to identify the substance, regional characteristics or landscaping of Namwon Yonghogugok, which is the only valley of Jiri Mountain, based on Kim Samun's 'Yonghokugok-Gyeongseungannae(龍湖九曲景勝案內)', 'Yongseongji(龍城誌)' and position, meaning of letters carved and projection technique by ArcGIS10.0 on the rocks are as below. The feature landscapes of the canyon of Yonghogugok, which is an incised meander and one of the Eight beautiful scenery of Namwon, ponds, cliffs and rocks generated with metamorphic rocks and granites weathered by rapids torrents. As a result of measuring the GPS coordinates of the letters carved on the rocks, excluding the 3 Gok Hakseoam and the distances based on the origin and destination of the letters carved on the rocks using the API(Application Programming Interface) function of Daum map, the total distance of Yonghogugok was 3.5km and the average distance between the each Gok was 436.5m. It is assumed that Yonghogugok was designated by Sarim(士林) of the Kiho School(畿湖學派) related to Wondong Hyangyak(元洞鄕約) which is the main agent of Yonghojeongsa(龍湖精舍), the forerunner of Yonghoseowon(龍湖書院), between the late Joseon Dynasty and the early Japanese colonial era, in 1927. Its grounds are the existence of Yonghoyeongdang mentioned on 'Yonghojeongsilgi'(龍湖亭實記), records of 'Haeunyugo(荷隱遺稿)', 'Yonghopumje(龍湖品題)' of Bulshindang(佛神堂), 'Yonghojeongsadonggu Gapjachun(龍湖精舍洞口 甲子春)' letters carved on the rocks and 'Yonghogugok-Shipyeong(龍湖九曲十詠)' posted on Mokgandang of Yonghoseowon. Comprehensively considering the numerous poetry society lists carved on the stone wall of Punghodae(風乎臺), the Sixth Gok Yuseondae, its stone mortar, 'Bangjangjeildongcheon(方丈第一洞天)' of Bulshindang and Gyoryongdam(交龍潭), the Yonghoseokmun(龍湖石門) letters carved on the rocks, Yeogungseok adjacent to the First Gok and Fengshui facilities, centered on Yonghoseowon and Yonghojeong, Yonghogugok can be understood as a unique valley culture formed with the thoughts of Confucianism, Buddhism, Taoism and Fengshui. 'Yonghogugok-Gyeongseungannae' provides very useful information to understand the place name, called by locals and landscaping aspects of Yonghogugok in the late Joseon Dynasty. In addition, the meaning of "Nine dragons" and even though 12 chu(湫: pond) of Yonghogugok Yongchudong including Bulyeongchu, Guryongchu, Isuchu, Goieumchu and Daeyachu are mentioned on Yongseongji, a part of them cannot be confirmed now. Various place names and facilities relevant to Guryong adjacent to Yonghogugok are the core of the place identity. In addition, the accurate location identification and the delivery of the landscaping significance of the 12 ponds is expected to provide landscaping attractiveness of Yonghogugok and become very useful contents for landscaping storytelling and a keyword of storyboard.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1653-1667
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• 2020

In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.