• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.175-185
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• 2020

Three-dimensional registration is a process of matching data with or without a coordinate system to a reference coordinate system, which is used in various fields such as the absolute orientation of photogrammetry and data combining for producing precise road maps. Three-dimensional registration is divided into a method using points and a method using linear features. In the case of using points, it is difficult to find the same conjugate point when having different spatial resolutions. On the other hand, the use of linear feature has the advantage that the three-dimensional registration is possible by using not only the case where the spatial resolution is different but also the conjugate linear feature that is not the same starting point and ending point in point cloud type data. In this study, we proposed a method to determine the scale and the three-dimensional translation after determining the three-dimensional rotation angle between two data using quaternion to perform three-dimensional registration using linear features. For the verification of the proposed method, three-dimensional registration was performed using the linear features constructed an indoor and the linear features acquired through the terrestrial mobile mapping system in an outdoor environment. The experimental results showed that the mean square root error was 0.001054m and 0.000936m, respectively, when the scale was fixed and if not fixed, using indoor data. The results of the three-dimensional transformation in the 500m section using outdoor data showed that the mean square root error was 0.09412m when the six linear features were used, and the accuracy for producing precision maps was satisfied. In addition, in the experiment where the number of linear features was changed, it was found that nine linear features were sufficient for high-precision 3D transformation through almost no change in the root mean square error even when nine linear features or more linear features were used.

• Ocean Systems Engineering
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• v.10 no.1
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• pp.111-129
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• 2020

A simplified algorithm is proposed for fast estimation of the material quantities required for the construction of rubble-mound breakwaters. The proposed algorithm is able to employ only the data available at feasibility study phase such as the maximum draught of the design ship selected to transport the cargos to the harbor despite, because at the feasibility phase, information for the planned harbor is likely to be very limited. A linear-constant waterdepth model together with a proposed section configuration for the breakwaters, which is customary for harbors, is considered to calculate the quantity of materials. The numerical simulation of the wave characteristics has been verified using the recorded wave data collected by a buoy installed near the Neka harbor in Caspian Sea waters. A case study has been also applied to four harbors to validate the proposed algorithm. The estimated weights using the proposed linear-constant and multi-linear waterdepth models were compared using the bathymetry maps and layouts of these harbors. A computer program, written in QBasic language, has been developed to simulate the wave characteristics and to estimate the material quantities needed to construct a rubble-mound breakwater. The obtained results show that taking into account the acceptable accuracies normally applied to the feasibility study and conceptual design phases, the proposed algorithm is sufficiently accurate and highly effective for the conceptual estimation of materials' quantities of breakwaters in the feasibility study phase of harbor projects.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.509-518
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• 2018

Weather is the most influential factor for crop cultivation. Weather information for cultivated areas is necessary for growth and production forecasting of agricultural crops. However, there are limitations in the meteorological observations in cultivated areas because weather equipment is not installed. This study tested methods of predicting the daily mean temperature in onion fields using geostatistical models. Three models were considered: inverse distance weight method, generalized additive model, and Bayesian spatial linear model. Data were collected from the AWS (automatic weather system), ASOS (automated synoptic observing system), and an agricultural weather station between 2013 and 2016. To evaluate the prediction performance, data from AWS and ASOS were used as the modeling data, and data from the agricultural weather station were used as the validation data. It was found that the Bayesian spatial linear regression performed better than other models. Consequently, high-resolution maps of the daily mean temperature of Jeonnam were generated using all observed weather information.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.267-274
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• 2023

LiDAR, one of the most important sensing methods used in mobile robots and cars with assistive/autonomous driving functions, is used to locate surrounding obstacles or to build maps. For real-time path generation, the detection of potholes or puddles on the driving surface is crucial. To achieve this, we used the coordinates of the reflection points provided by LiDAR as well as the intensity information to classify water areas, which was achieved by applying a linear regression method to the intensity distribution. The rationale for using the LiDAR index as an input variable for linear regression is presented, and we demonstrated that it is not affected by errors in the distance measurement value. Because of LiDAR vertical scanning, if the reflective surface is not uniform, it is divided into different groups according to the intensity distribution, and a mathematical basis for this is presented. Through experiments in an outdoor driving area, we could distinguish between flat ground, potholes, and puddles, and kinematic analysis was performed to calculate the maximum width that could be crossed for a given vehicle body size and wheel radius.

• Journal of Astronomy and Space Sciences
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• v.27 no.2
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• pp.117-122
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• 2010

An ionospheric error simulation is needed for creating precise Global Positioning System (GPS) signal using GPS simulator. In this paper we developed Klobuchar coefficients n ${\alpha}_n$ and ${\beta}_n$ (n = 1, 2, 3, 4) generation algorithms for simulator and verified accuracy of the algorithm. The algorithm extract those Klobuchar coefficients from broadcast (BRDC) messages provided by International GNSS Service during three years from 2006 through 2008 and curve-fit them with sinusoidal and linear functions or constant. The generated coefficients from our developed algorithms are referred to as MODL coefficients, while those coefficients from BRDC messages are named as BRDC coefficients. The maximum correlation coefficient between MODL and BRDC coefficients was found for ${\alpha}_2$ and the value was 0.94. On the other hand, the minimum correlation was 0.64 for the case of ${\alpha}_1$. We estimated vertical total electron content using the Klobuchar model with MODL coefficients, and compared the result with those from the BRDC model and global ionosphere maps. As a result, the maximum RMS was 3.92 and 7.90 TECU, respectively.

• Coupled systems mechanics
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• v.9 no.6
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• pp.539-562
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• 2020

In this paper the linear elastic coupling between a 2 degree of freedom shear-type frame system and a rigid block is analytically and experimentally investigated. As demonstrated by some of the authors in previous papers, it is possible to choose a coupling system able to guarantee advantages, whatever the mechanical characteristics of the frame. The main purpose of the investigation is to validate the analytical model. The nonlinear equations of motion of the coupled system are obtained by a Lagrangian approach and successively numerically integrated under harmonic and seismic excitation. The results, in terms of gain graphs, maps and spectra, represent the ratio between the maximum displacements or drifts of the coupled and uncoupled systems as a function of the system's parameters. Numerical investigations show the effectiveness of the nonlinear coupling for a large set of parameters. Thus experimental tests are carried out to verify the analytical results. An electro-dynamic long-stroke shaker sinusoidally and seismically forces a shear-type 2 d.o.f frame coupled with a rigid aluminium block. The experimental investigations confirm the effectiveness of the coupling as predicted by the analytical model.

• Journal of Korean Tunnelling and Underground Space Association
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• v.4 no.3
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• pp.217-227
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• 2002

Geostatistical methods were used for the groundwater flow analysis on the ${\bigcirc}{\bigcirc}$ tunnel area. Linear regression analysis shows that the topographic elevation and ground water level of this area have very high correlation. Groundwater-level contour maps produced by ordinary kriging and cokriging have little differences in mountain areas. But, comparing two maps on the basis of an elevation contour map, a groundwater-level contour map using cokring is more accurate. Analyzing the groundwater flow on two groundwater-level contour maps, the groundwater of study area flows from the north-west mountain areas to near valleys, and from the peak of the mountain to outside areas. In the design steps, the groundwater-level distribution is reasonably considered in the tunnel construction area by cokriging approach. And, geostatistics will provide quantitative information in the unknown groundwatrer-level area.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.845-854
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• 2006

Establishment of snowmelt factors is necessary to simulate stream flow using snowmelt models during snowmelt periods. The few observed data related snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. The objective of this study was to extract snowmelt factors using RS, GIS technique and meteorological data. Snow cover maps were derived from NOAA/AVHRR images for the winter seasons from 1997 to 2003. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation station. Depletion curves of snowmelt area were described from the linear regression equations of each year between the average temperature and snow cover area in Soyanggang-dam and chungju-dam watershed.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.1 s.9
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• pp.71-80
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• 1997

This paper suggests a Map Accuracy Standards by analyzing U.S. National Map Accuracy Standards, by considering korean terrain feature and statistical error theory for paper and digital maps on the scale of 1:50,000. Map accuracy standards require horizontal accuracy to be reported as a circular error with 90% confidence level through Linear Error Probable(LEP) theory and Circular Error Probable(CEP) theory. In order to verify the proposed methodology for positioning accuracy testing, several kinds of test point were selected and tested. These test points were extracted at the centers of roads and bridges, the comers of the independent building, the edges of geographical botany, and the tops of mountains. The positioning accuracy assessment was peformed by comparing the positions of test points in digital maps generated three different sources with those acquired by high accurate GPS surveying. The digital maps were produced from aerial photographs and SPOT satellite image using analytical plotter and 1:50,000 paper map.

• Geomechanics and Engineering
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• v.34 no.3
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.