• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.93-102
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• 2019

In this study, in order to analyze the possibility of observing a typhoon track based on the Global Navigation Satellite System(GNSS), Typhoon NARI, the 11th typhoon of 2007, was analyzed in terms of the typhoon track as well as the local variation of perceptible water over time. The perceptible water was estimated using data obtained from observatories located on the typhoon track from Jeju to the southern coast of Korea for a total of 18 days from September 7(DOY 250) to September 24(DOY 267), 2007, including the period when the observatories were affected by the typhoon at full-scale, as well as one previous week and one following week. The results show that the trend of the variation of perceptible water was similar between the observatories near the typhoon track. Variation of perceptible water over time depending on the development and landing of the typhoon was distinctively observed. Several hours after the daily maximum of perceptible water was found at the JEJU Observatory, the first struck by the typhoon on the typhoon track, the maximum value was found at other observatories located on the southern coast. In the observation period, the time point at which the maximum perceptible water was recorded in each location was almost the same as the time point at which the typhoon landed at the location. To analyze the accuracy of the GNSS-based perceptible water measurement, the data were compared with radiosonde-based perceptible water data. The mean error was 0.0cm, and the root mean square error and the standard deviation were both 0.3cm, indicating that the GNSS-based perceptible water data were highly accurate and precise. The results of the this study show that the GNSS-based perceptible water data may be used as highly accurate information for the analysis of typhoon tracks over time.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.1
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• pp.1-7
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• 2019

In this study, we estimated the tropospheric delay of GNSS (Global Navigation Satellite System) signals during passing through the atmosphere in relation to weather and seasonal factors. For this purpose, we chose four CORS (Continuously Operating Reference Station) stations from inland (CCHJ and PYCH) and on the coast (GEOM and CHJU). A total of 48 days for each station (one set of data for each week) were downloaded from the NGII (National Geographic Information Institute) and processed it using the scientific GNSS software. The average tropospheric delays in winter are less than 2,400 mm, which is about 200 mm less than those in summer. The estimated tropospheric delay shows a similar pattern from all stations except the absolute bias in magnitude, while a large delay was observed for the station located on the coast. In addition, the delay during the day was relatively stable in winter, and the average tropospheric delay was strongly related to the orthometric height. The inland stations have tropospheric delays by the precipitation rather than humidity due to dry weather and difference in temperature. On the contrary, it was primarily caused by the humidity on the sea. The correlation between temperature and water vapor pressure is 0.9 or larger for all stations, and the tropospheric delay showed a high linear relationship with temperature. It is necessary to analyze the GNSS data with higher temporal resolution (e.g. all RINEX data of the year) to improve the stability and reliability of the correlation results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.663-670
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• 2020

In the present study, we assessed the accuracy of aerial triangulation using a UAV (Unmanned Aerial Vehicle) capable of network RTK (Real-Time Kinematic) survey in a disaster situation that may occur in a semi-urban area mixed with buildings. For a reliable survey of check points, they were installed on the roofs of buildings, and static GNSS (Global Navigation Satellite System) survey was conducted for more than four hours. For objective accuracy assessment, coded aerial targets were installed on the check points to be automatically recognized by software. At the instance of image acquisition, the 3D coordinates of the UAV camera were measured using VRS (Virtual Reference Station) method, as a kind of network RTK survey, and the 3-axial angles were achieved using IMU (Inertial Measurement Unit) and gimbal rotation measurement. As a result of estimation and update of the interior and exterior orientation parameters using Agisoft Metashape, the 3D RMSE (Root Mean Square Error) of aerial triangulation ranged from 0.153 m to 0.102 m according to the combination of the image overlap and the angle of the image acquisition. To get higher aerial triangulation accuracy, it was proved to be effective to incorporate oblique images, though it is common to increase the overlap of vertical images. Therefore, to conduct a UAV mapping in an urgent disaster site, it is necessary to acquire oblique images together rather than improving image overlap.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.47-54
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• 2021

Calculation of quantity at construction sites is a factor that has a great influence on construction costs, and it is important to calculate accurate values. In this study, topographic model was created by using drone photogrammetry and drone LiDAR to estimate earthwork volume. ortho image and DSM (Digital Surface Model) were constructed for the study area by drone photogrammetry, and DEM (Digital Elevation Model) of the target area was established using drone LiDAR. And through accuracy evaluation, accuracy of each method are 0.034m, 0.35m in horizontal direction, 0.054m, 0.25m in vertical direction. Through the research, the usability of drone photogrammetry and drone LiDAR for constructing geospatial information was presented. As a result of calculating the volume of the study site, the UAV photogrammetry showed a difference of 1528.1㎥ from the GNSS (Global Navigation Satellite System) survey performance, and the 3D Laser Scanner showed difference of 160.28㎥. The difference in the volume of earthwork is due to the difference in the topographic model, and the efficiency of volume calculation by drone LiDAR could be suggested. In the future, if additional research is conducted using GNSS surveying and drone LiDAR to establish topographic model in the forest area and evaluate its usability, the efficiency of terrain model construction using drone LiDAR can be suggested.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.291-298
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• 2022

Recently developed drones are inexpensive and very convenient to operate. As a result, the production and utilization of spatial information using drones are increasing. However, most drones acquire images with a low-cost global navigation satellite system (GNSS) and an inertial measurement unit (IMU). Accordingly, the accuracy of the initial location and rotation angle elements of the image is low. In addition, because these drones are small and light, they can be greatly affected by wind, making it difficult to maintain a certain overlap, which degrades the positioning accuracy. Therefore, in this study, images are taken at different times in order to analyze the positioning accuracy according to changes in certain exterior orientation parameters. To do this, image processing was performed with Pix4D Mapper and the accuracy of the results was analyzed. In order to analyze the variation of the accuracy according to the exterior orientation parameters in detail, the exterior orientation parameters of the first processing result were used as meta-data for the second processing. Subsequently, the amount of change in the exterior orientation parameters was analyzed by in a strip-by-strip manner. As a result, it was proved that the changes of the Omega and Phi values among the rotation elements were related to a decrease in the height accuracy, while changes in Kappa were linked to the horizontal accuracy.

• Journal of Cadastre & Land InformatiX
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• v.46 no.1
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• pp.133-148
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• 2016

Voices demanding a revision of the aviation law on the operating drones are continuously rising high with the increase of their applicability in various industry fields. According to the current regulations, drones are permitted to fly under very strict conditions, which include limited places and the line-of-sight visibility from pilots. Because of the strict regulations, it is almost impossible for drones to be used in many industries such as parcel delivery services. To improve the business value of drones, we have to improve the accuracy of drones' positions and provide the proper protection levels in order to detect and avoid any risks including the collisions with the other drones. SBAS(Satellite Based Augmentation System) can support the aviation requirements with the accuracy and integrity so as to reduce the position errors and to calculate the protection levels of drones. In this paper, we assign the flight heights of drones according to the decision heights as per LAAS(Local Area Augmentation System) landing categories and conduct a simulation to predict the SBAS available time of the day.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.737-745
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• 2010

This paper describes the operation results of the GPS receiver system for KSLV (Korea Space Launch Vehicle)-I on the launch site at Naro Space Center that is the first spaceport of South Korea located at Goheung. All equipments of KSLV-I including the GPS receiver system should be monitored and controlled through hard-wired interface during KSLV-I is on standby at the launch pad. The GPS receiver for KSLV-I is connected to triple almost omni-directional patch antennas mounted on the cylindrical surface of KSLV-I that should be erected vertically on the launch pad until lift-off. Signal interference and multipath effects observed in the GPS receiver on the launch site are analyzed in this paper based on the GPS signals received from each GPS antenna.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.197-200
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• 2008

A GNSS augmentation system provides precise position information using corrected GNSS pseudorange measurements. Common bias errors are corrected by PRC (Pseudorange Correction) between reference stations and a rover. However non-common errors (Ionospheric and Tropospheric noise error) are not corrected. Using position error variance this paper analyzes non-common errors (noise errors) of ionosphere and troposphere wet vapor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1045-1050
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• 2008

A GNSS augmentation system provides precision information using corrected GNSS pseudorange measurements. Common bias errors are corrected by PRC (Pseudorange Correction) between reference stations and a rover. However non-common errors (ionospheric and tropospheric noise error) are not corrected. Using position error variance this paper analyzes non-common error (noise errors) of ionosphere and troposphere wet vapor.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.331-341
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• 2019

With the popularity of sensor-rich environments, smartphones have become one of the major platforms for obtaining and sharing information. Since it is difficult to utilize GNSS (Global Navigation Satellite System) inside the area with many buildings, the localization of smartphone in this case is considered as a challenging task. To resolve problem of localization using smartphone a four step image-based localization method and procedure is proposed. To improve the localization accuracy of smartphone datasets, MMS (Mobile Mapping System) and Google Street View were utilized. In our approach first, the searching for candidate matching image is performed by the query image of smartphone's using GNSS observation. Second, the SURF (Speed-Up Robust Features) image matching between the smartphone image and reference dataset is done and the wrong matching points are eliminated. Third, the geometric transformation is performed using the matching points with 2D affine transformation. Finally, the smartphone location and attitude estimation are done by PnP (Perspective-n-Point) algorithm. The location of smartphone GNSS observation is improved from the original 10.204m to a mean error of 3.575m. The attitude estimation is lower than 25 degrees from the 92.4% of the adjsuted images with an average of 5.1973 degrees.