• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_1
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• pp.503-509
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• 2013

The KOMPSAT-3 (Korea Multi-Purpose Satellite-3), was launched on May 18, 2012, is an optical high-resolution observation mission of the Korea Aerospace Research Institute and provides RPC(Rational Polynomial Coefficient) for ground coordinate determination. It is however need to adjust because RPC absorbs effects of interior-exterior orientation errors. In this study, to obtain the suitable adjustment parameters of the vendor-provided RPC of the KOMPSAT-3 images, six types of adjustment models were implemented. As results, the errors of two and six adjustment parameters differed approximately 0.1m. We thus propose the two parameters model, the number of control points are required the least, to adjust the KOMPSAT-3 R PC. According to the increasing the number of control points, RPC adjustment was performed. The proposed model with a control point particularly did not exceed a maximum error 3m. As demonstrated in this paper, the two parameters model can be applied in RPC adjustment of KOMPSAT-3 stereo image.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.5 no.2
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• pp.109-120
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• 1985

This thesis is a study on multiple close range photogrammetry, and the purpose of this study is to develop the most accurate adjustment method of three dimensional object coordinates. This was achieved by comparing the standard errors of actual data to the computed values from 2 photos and multiple photos. The conventional methods for multiple photos have been analyzed by using geometric model formation. But in this study, the equation of collinearity condition which has been applied to aerial photogrammetry was derived to be a basic principle of close range photogrammetry, and the algorithm for analyzing multiple photos was developed using simultaneous bundle adjustment. The method used in this study, showed more homogeneous accuracy in coordinate and more consistent variance of error than those of conventional methods. It was found that the cases using 3, 4, and 5 photos were more accurate than using 2 photos; the accuracies were improved to 15%, 35%, and 50%, for each case. Thus this study is expected to be useful in measuring the geometry of historic monuments and other structures requiring high accuracy. Also the combined case of multiple photos is considered to be effective for the precise analysis of the objects which are difficult to measure for obstacles.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.97-105
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• 2020

Recently, Artificial Neural Network receives attention as a data prediction method. Among these, a Long Shot-term Memory (LSTM) model specialized for time-series data prediction was utilized as a prediction method of hydrological time series data. In this study, the LSTM model was constructed utilizing deep running open source library TensorFlow which provided by Google, to predict inflows of multipurpose dams. We predicted the inflow of the Yongdam Multipurpose Dam which is located in the upper stream of the Geumgang. The hourly flow data of Yongdam Dam from 2006 to 2018 provided by WAMIS was used as the analysis data. Predictive analysis was performed under various of variable condition in order to compare and analyze the prediction accuracy according to four learning parameters of the LSTM model. Root mean square error (RMSE), Mean absolute error (MAE) and Volume error (VE) were calculated and evaluated its accuracy through comparing the predicted and observed inflows. We found that all the models had lower accuracy at high inflow rate and hourly precipitation data (2006~2018) of Yongdam Dam utilized as additional input variables to solve this problem. When the data of rainfall and inflow were utilized together, it was found that the accuracy of the prediction for the high flow rate is improved.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.101-111
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• 2017

This study propose a method to predict the bus arrival time by considering the signal delay time which is an element which can not be considered in the current bus arrival prediction information generation algorithm. In order to consider the signal delay time, travel time is divided into three components: service time, cruising travel time, and signal delay time. Signal delay time was estimated using intersection arrival time and TOD. The results show that most of the errors that occurred in predicting the arrival time are within about 30 seconds. Some of the estimates have large errors due to the nature of this methodology that uses the estimated value of the intersection arrival time rather than the observation value. It is also difficult to predict the arrival time of the express buses using this method. Future studies such as improving this through real-time location information will greatly improve the accuracy of the methodology.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.4
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• pp.43-48
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• 2015

We studied on pseudo-range correction(PRC) modeling in order to improve differential GNSS(DGNSS) accuracy. The PRC is the range correction information that provides improved location accuracy using DGNSS technique. The digital correction signal is typically broadcast over ground-based transmitters. Sometimes the degradation of the positioning accuracy caused by the loss of PRC signals, radio interference, etc. To prevent the degradation, in this paper, we have designed a PRC model through polynomial curve fitting and evaluated this model. We compared two quantities, estimations of PRC using model parameters and observations from the reference station. In the case of GPS, the average is 0.1m and RMSE is 1.3m. Most of GPS satellites have a bias error of less than ${\pm}1.0m$ and a RMSE within 3.0m. In the case of GLONASS, the average and the RMSE are 0.2m and 2.6m, respectively. Most of satellites have less than ${\pm}2.0m$ for a bias error and less than 3.0m for RMSE. These results show that the estimated value calculated by the model can be used effectively to maintain the accuracy of the user's location. However;it is needed for further work relating to the big difference between the two values at low elevation.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.251-262
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• 2010

In order to provide quantitative control of the standard products of Geostationary Ocean Color Imager (GOCI), on-board radiometric correction, atmospheric correction, and bio-optical algorithm are obtained continuously by comprehensive and consistent calibration and validation procedures. The calibration/validation for radiometric, atmospheric, and bio-optical data of GOCI uses temperature, salinity, ocean optics, fluorescence, and turbidity data sets from buoy and platform systems, and periodic oceanic environmental data. For calibration and validation of GOCI, we compared radiometric data between in-situ measurement and HyperSAS data installed in the Ieodo ocean research station, and between HyperSAS and SeaWiFS radiance. HyperSAS data were slightly different in in-situ radiance and irradiance, but they did not have spectral shift in absorption bands. Although all radiance bands measured between HyperSAS and SeaWiFS had an average 25% error, the 11% absolute error was relatively lower when atmospheric correction bands were omitted. This error is related to the SeaWiFS standard atmospheric correction process. We have to consider and improve this error rate for calibration and validation of GOCI. A reference target site around Dokdo Island was used for studying calibration and validation of GOCI. In-situ ocean- and bio-optical data were collected during August and October, 2009. Reflectance spectra around Dokdo Island showed optical characteristic of Case-1 Water. Absorption spectra of chlorophyll, suspended matter, and dissolved organic matter also showed their spectral characteristics. MODIS Aqua-derived chlorophyll-a concentration was well correlated with in-situ fluorometer value, which installed in Dokdo buoy. As we strive to solv the problems of radiometric, atmospheric, and bio-optical correction, it is important to be able to progress and improve the future quality of calibration and validation of GOCI.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.1
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• pp.16-25
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• 2012

To calculate the total mass flux that change in dry and flood season in the Yeomha Channel of Gyeonggi Bay, the 13 hour bottom tracking observation was performed from the southern extremity. The value of the total mass flux(Lagrange flux) was calculated as the sum of the Eulerian flux value and stroke drift value and the tidal residual flow was harmonically analyzed through the least-squares method. Moreover, the average during the tidal cycle is essential to calculate the mass flux and the tidal residual flow and there is the need to equate the grid of repeatedly observed data. Nevertheless, due to the great differences in the studied region, the number of vertical grid tends to change according to time and since the horizontal grid differs according to the transport speed of the ship as a characteristic of the bottom tracking observation, differences occur in the horizontal and vertical grid for each hour. Hence, the present study has vertically and horizontally normalized(sigma coordinate) to equate the grid per each hour. When compared to the z-level coordinate system, the Sigma coordinate system was evaluated to have no irrationalities in data analysis with 5% of error. As a result of the analysis, the tidal residual flow displayed the flow pattern of sagging in the both ends in the main waterway direction of dry season. During flood season, it was confirmed that the tidal residual flow was vertical 2-layer flow. As a result of the total mass flux, the ebb properties of 359 cm/s and 261 cm/s were observed during dry and flood season, respectively. The total mass flux was moving the intertidal region between Youngjong-do and Ganghwa-do.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.231-242
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• 2016

As of late, air quality information has been actively gathered and investigated in order to find possible environmental risk factors that may affect the onset of cardiovascular disease. Nevertheless, existing studies are limited in the detailed analysis because they take advantage of the air quality information of the macro statistics divided into administrative districts. This paper proposes the construction of distance-based air quality dataset using a domestic hospital’s geographical location information as a reliable data gathering step for a more detailed analysis of environmental risk factors. For the construction of the dataset, air quality information was obtained by utilizing the geographical location of a hospital—in which a patient with cardiovascular disease had been admitted—and then matching the hospital with a meteorological and air pollution station in its vicinity. An air quality acquisition system based on GMap.net was devised for the purpose of data gathering and visualization. The reliability of the experiment was confirmed by evaluating the matching rate and error of air quality values between the acquired dataset with existing area-based air quality datasets from matched distances. Therefore, this dataset, which considers geographical information, can be utilized in multidisciplinary research for the discovery of environmental risk factors that can affect not only cardiovascular diseases but also potentially other epidemic diseases.

• Journal of the Korean Geosynthetics Society
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• v.16 no.1
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• pp.1-8
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• 2017

Displacement of dams by various instrumentations has been monitored for its safety management and analyzing the behavior after a dam collapse accident. However, unknown displacement of dam has frequently been occurred and it's difficult to analyze behavior of dams more accurately. In this study, improvement of reliabilities for displacement of dams measured by a total station was suggested by calibrating the monitoring system. The position of total station was initially measured through 2-3 given points and the coordinate of the total station was considered as an absolute value. Also, base horizontal and vertical angles had not been considered even if they are important factors when displacement was estimated. In this study, location of the total station and variations of base horizontal and vertical angles were investigated during measuring displacements of targeting points. From the results of this study, they are important factors which are affecting measurements of dam displacements. Before the calibrating, the displacement at 50 m from total station was ${\pm}20mm$. After the calibrating, the displacement was decreased by ${\pm}5mm$.

• Journal of Soil and Groundwater Environment
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• v.7 no.4
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• pp.59-67
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• 2002

As a parameter for hydrodynamic modeling to define the range of seawater intrusion, dispersivities are frequently determined from pre-experiments or theoretical studies because field experiments need a lot of time and expenses. If the dispersivities are inadequate for an aquifer, the numerical results may have some errors. We examined the validity of longitudinal dispersivities by comparing the ranges of seawater intrusion with numerical modeling, field data and apparent resistivity sections. In the numerical modeling the TDS distributions simulated by the Xu's longitudinal dispersivity are more similar to the values of TDS measured at monitoring wet]s and boreholes than those by the Neuman's longitudinal dispersivity. The ranges of seawater intrusion by numerical simulations using Xu's longitudinal dispersivity show that the contour line of 1000 ㎎/L. as TDS is located at 480 m from the coast in May, while at 390 m in July. The difference is originated from the shift of the interface between seawater and fresh water. It moved toward the coast in July because of the seasonal increase of hydraulic gradient according to rainfall. A contour line of 15 ohm-m was used to define the range of seawater intrusion in apparent resistivity sections. From this criterion on the interface between seawater and fresh water, the range of seawater intrusion is located at 450 m from the coast. This result is similar to the range of seawater intrusion simulated by the numerical modeling using Xu's dispersivity. Therefore the range of seawater intrusion shows the difference due to the dispersivities used for the hydrodynamic modeling and the dispersivity generated by the Xu's equation is considered more effective to decide the range of seawater intrusion in this study area.