• Journal of Korean Society for Atmospheric Environment
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• v.24 no.3
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• pp.300-309
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• 2008

Variations in PM10 concentration between 2000 and 2005 from 84 urban air monitoring stations operated by the government were analyzed. The K-means cluster analysis was attempted using annual average and the 99th percentile of daily averages as parameters. The results obtained by excluding Asian dust episode days were compared with those obtained by using all available data. In any cases, the cluster with the highest mean concentration was mostly composed of stations in Seoul and Gyeonggi. Annual average of the cluster with the highest mean concentration showed a distinct decreasing trend, but that excluding Asian dust episode days did not show such a trend. Without Asian dust episode days high concentrations of monthly averages in March and April were also not observed. The effect of Asian dust was more pronounced in the 99th percentile of daily averages. The 99th percentile of daily averages of the cluster with the highest mean concentration was the highest in June following downs in April and May.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.269-277
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• 2022

In this paper, we overview the system development status of the national maritime precise point positioning-real-time kinematic (PPP-RTK) service in Korea, also known as the Precise POsitioning and INTegrity monitoring (POINT) system. The development of the POINT service began in 2020, and the open service is scheduled to start in 2025. The architecture of the POINT system is composed of three provider-side facilities-a reference station, monitoring station, and central control station-and one user-side receiver platform. Here, we propose the detailed functionality of each component considering unidirectional broadcasting of augmentation data. To meet the centimeter-level user positioning accuracy in maritime coverage, new reference stations were installed. Each reference station operates with a dual receiver and dual antenna to reduce the risk of malfunctioning, which can deteriorate the availability of the POINT service. The initial experimental results of a testbed from corrections generated from the testbed network, including newly installed reference stations, are presented. The results show that the horizontal and vertical accuracies satisfy 2.63 cm and 5.77 cm, respectively. For the purpose of (near) real-time broadcasting of POINT correction data, we designed a correction message format including satellite orbit, satellite clock, satellite signal bias, ionospheric delay, tropospheric delay, and coordinate transformation parameters. The (near) real-time experimental setup utilizing (near) real-time processing of testbed network data and the designed message format are proposed for future testing and verification of the system.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.253-256
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• 2002

A hydrologic gauging network include a real-time measuring equipment was established within the Balhan watershed. Rainfall, stream water level, flow velocities were monitored at the six gauging stations. For stream flow gauging stations, the stage-discharge relationships were developed. The flow rate of the Balan watershed was 83.60% in 2001 and 48.79% in 2002.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2569-2575
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• 2015

Network RTK generally uses a linear interpolation method by using the corrections from reference stations. This minimizes the spatial decorrelation error caused by the increase of distance between the reference station's baseline and user's baseline. However, tropospheric delay, a function of the meteorological data can cause a spatial decorrelation characteristic among reference stations within a network by local meteorological difference. A non-linear characteristic of tropospheric delay can deteriorate Network RTK performance. In this paper, the modeling of tropospheric delay irregularity is made from the data when the typhoon is occurred. By using this modeling, analyzing the effect of meteorological difference between reference stations on correction is performed. Finally, we analyze an effect of non-linear characteristics of tropospheric delay among reference stations to Network RTK user.

• Journal of Soil and Groundwater Environment
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• v.19 no.3
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• pp.123-133
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• 2014

It is important to predict the groundwater level fluctuation for effective management of groundwater monitoring system and groundwater resources. In the present study, three different time series models for the prediction of groundwater level in response to rainfall were built, those are transfer function noise model (TFNM), artificial neural network (ANN), and adaptive neuro fuzzy interference system (ANFIS). The models were applied to time series data of Boen, Cheolsan, and Hongcheon stations in National Groundwater Monitoring Network. The result shows that the model performance of ANN and ANFIS was higher than that of TFNM for the present case study. As lead time increased, prediction accuracy decreased with underestimation of peak values. The performance of the three models at Boen station was worst especially for TFNM, where the correlation between rainfall and groundwater data was lowest and the groundwater extraction is expected on account of agricultural activities. The sensitivity analysis for the input structure showed that ANFIS was most sensitive to input data combinations. It is expected that the time series model approach and results of the present study are meaningful and useful for the effective management of monitoring stations and groundwater resources.

• Journal of Soil and Groundwater Environment
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• v.21 no.4
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• pp.30-41
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• 2016

The amount of groundwater related data is drastically increasing domestically from various sources since 2000. To justify the more expansive continuation of the data acquisition and to derive valuable implications from the data, continued employments of sophisticated and state-of-the-arts statistical tools in the analyses and predictions are important issue. In the present study, we employed a well established machine learning technique of Gaussian Process Regression (GPR) model in the trend analyses of groundwater level for the long-term change. The major benefit of GPR model is that the model provide not only the future predictions but also the associated uncertainty. In the study, the long-term predictions of groundwater level from the stations of National Groundwater Monitoring Network located within Han River Basin were exemplified as prediction cases based on the GPR model. In addition, a few types of groundwater change patterns were delineated (i.e., increasing, decreasing, and no trend) on the basis of the statistics acquired from GPR analyses. From the study, it was found that the majority of the monitoring stations has decreasing trend while small portion shows increasing or no trend. To further analyze the causes of the trend, the corresponding precipitation data were jointly analyzed by the same method (i.e., GPR). Based on the analyses, the major cause of decreasing trend of groundwater level is attributed to reduction of precipitation rate whereas a few of the stations show weak relationship between the pattern of groundwater level changes and precipitation.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1756-1760
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• 2008

In this study, it was suggested how to monitor the air quality with use of intelligent wireless sensor network in the subway station. When Zigbee-based ubiquitous sensor network was used, smaller budget was required in configuring the system compared to existing air-quality monitoring method and this system may easily be configured due to easy installation of communication cables. The study will be continued to supplement the network systems currently installed in subway stations and the completion of development of this system is expected to make a large contribution in improvement of indoor air quality.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.5
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• pp.583-591
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• 2004

In this study, methodologies for the rational organization of air pollution monitoring network were examined by understanding the characteristics of temporal and spatial distribution of secondary air pollution, whose significance would increase hereafter. The data on $O_3$ and $NO_2$ concentrations during high ozone period in 1998~1999 recorded at the nine air pollution monitoring station in Busan were analysed using principal component analysis (PCA) and cumulative semivariogram. It was found that the ozone concentration was deeply associated with the daily emission characteristics or the $O_3$ precusors, and nitrogen dioxide concentration largely depends on the emission strength of regional sources. According to the spatial distribution analysis of ozone and nitrogen dioxide in Busan using cumulative semivariograms, the number of monitoring stations for the secondary air pollution can be reduced in east-west direction, but reinforced in north-south direction to explain the spacial variability. More scientific and rational relocation of air pollution monitoring network in Busan would be needed to investigate pollution status accurately and to plan and implement the pollution reduction policies effectively.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.175-184
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• 2017

Recently, PM10 is becoming a main issue in Korea because it causes a variety of diseases, such as respiratory and ophthalmologic diseases. This research studied to spatial information application cases for evaluating the feasibility of the location for PM10 observation stations utilizing Geogrphic Information System(GIS) spatial analysis. The spatial Information application cases for optimal location assessment were investigated to properly manage PM10 observation stations which are closely related with public spatial data and health care. There are 31 PM10 observation stations in Seoul city and the observed PM10 data at these stations were utilized to understand the overall assessment of PM10 stations to properly manage using interpolation methods. The estimated PM10 using Inverse Distance Weighted(IDW) and Kriging techniques and the map of PM10 concentrations of monitoring stations in Seoul city were compared with public spatial data such as precipitation, floating population, elementary school location. On the basis of yearly, seasonal and daily PM10 concentrations were used to evaluate the feasibility analysis and the location of current PM10 monitoring stations. The estimated PM10 concentrations were compared with floating population and calculated 2015 PM10 distribution data using zonal statistical methods. The national spatial data could be used to analyze the PM10 pollution distribution and additional determination of PM10 monitoring sites. It is further suggested that the spatial evaluation of national spatial data can be used to determine new location of PM10 monitoring stations.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.479-484
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• 2015

Network RTK is a precise positioning technique using carrier phase correction data from reference stations within the network, and is constantly being researched for improved performance. However, the study for the system accuracy has been performed but system integrity research has not been done as much as system accuracy, because network RTK has been mainly used on surveying for static or kinematic positioning. In this paper, adequate monitoring system for network RTK is designed as basis research for integrity monitoring on network RTK. To this, fault tree on network RTK is analyzed, and a countermeasure is prepared to detect and identify the each fault items. Based these algorithms, monitoring system to use on central processing facility is designed for network RTK service.