• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.5
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• pp.445-458
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• 2012

The objective of GPS control surveying is ultimately to determine coordinate sets of control points within targeted accuracy through a series of observations and network adjustments. To this end, it is of equivalent importance for the accuracy of these coordinates to be realistically represented by using an appropriate method. The accuracy representation can be quantitively made by the variance-covariance matrices of the estimates, of which features are sensitive to the mathematical models used in the adjustment. This paper deals with impact of functional and stochastic modeling techniques into the accuracy representation of the GPS control surveying with a view of gaining background for its standardization. In order to achieve this goal, mathematical theory and procedure of the single-baseline based multi-session adjustment has been rigorously reviewed together with numerical analysis through processing real world data. Based on this study, it was possible to draw a conclusion that weighted-constrained adjustment with the empirical stochastic model was among the best scheme to more realistically describe both of the absolute and relative accuracies of the GPS surveying results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.675-686
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• 2021

This study investigated the ground displacement occurring in a slope below a waste-rock dumping site and estimated the likelihood of a disaster due to a landslide. To start with, photogrammetry was conducted by unmanned aerial vehicles (UAVs) to investigate the size and extent of the ground displacement. From April 2019 to July 2020, the average error rate of the five UAV surveys was 0.011-0.034 m, and an elevation change of 2.97 m occurred due to the movement of the soil layer. Only some areas of the slope showedelevation change, and this was believed to be due to thegroundwater generated during rainfall rather than the effect of the waste-rock load at the top. Sensitivity analysis for LS-RAPID simulation was performed, and the simulation results were compared and analyzed by applying a digital elevation model (DEM) and a digital surface model (DSM)as terrain data with 10 m, 5 m, and 4 m grids. When data with high spatial resolution were used, the extent of the sedimentation of landslide material tended to be excessively expanded in the DEM. In contrast, in the result of applying a DSM, which reflects the topography in detail, the diffusion range was not significantly affected even when the spatial resolution was changed, and the sedimentation behavior according to the river shape could be accurately expressed. As a result, it was concluded that applying a DSM rather than a DEM does not significantly expand the sedimentation range, and results that reflect the site situation well can be obtained.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.163-171
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• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

• Korean Journal of Remote Sensing
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• v.18 no.4
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• pp.209-220
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• 2002

We carried out studies on SAR image intensity and interferometric phase over oyster sea farms. Strong backscattering was observed in amplitude images, and that was considered as a radar signal double bouncing from horizontal bars. These sea farming structures are not visible in satellite optical images except IKONOS image, so that it demonstrates the value of radar remote sensing as an effective tool in support of sea farm detection. The intensity of the image is sensitive to system parameters including wavelength, polarization, and look direction, but does not correlate to tide height. We found that the strongest backscattering can be obtained by L-band HH-polarization with a look direction perpendicular to the horizontal bar. We also succeeded in generating 21 coherent JERS-1 SAR interferometric pairs over the oyster farms. The general trend of the fringe rate of the interferometric phases appeared to be governed by altitude of ambiguity. The general trend was modeled by an inverse function and removed to have a residual phase. The residual phase showed a linear relation with the tide height. The results demonstrate for the first time that SAR can possibly be used to estimate sea level. However, the r.m.s. error of a regression line is 11.7 cm, and that is so far too large to make reliable assessments of sea level in practical applications. Further studies is required to improve the accuracy specifically using multi-polarization SAR data.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1559-1572
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• 2021

The response of vegetation under the crop stress condition was evaluated using structural, biochemical, and physiological vegetation indices based on unmanned aerial vehicle (UAV) images and field-spectrometer data. A high concentration of herbicide was sprayed at the different growth stages of garlic to process crop stress, the above ground dry matter of garlic at experimental area (EA) decreased about 46.2~84.5% compared to that at control area. The structural vegetation indices clearly responded to these crop damages. Spectral reflectance at near-infrared wavelength consistently decreased at EA. Most biochemical vegetation indices reflected the crop stress conditions, but the meaning of physiological vegetation indices is not clear due to the effect of vinyl mulching. The difference of the decreasing ratio of vegetation indices after the herbicide spray was 2.3% averagely in the case of structural vegetation indices and 1.3~4.1% in the case of normalization-based vegetation indices. These results meant that appropriate vegetation indices should be utilized depending on the types of crop stress and the cultivation environment and the normalization-based vegetation indices measured from the different spatial scale has the minimized difference.