• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.140-153
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• 2019

Cloase-range image information from drones and ground-based camera has been frequently used in the field of disaster mitigation with 3D modeling and mapping. In addition, the utilization of virtual reality(VR) is being increased by implementing realistic 3D models with the VR technology simulating disaster circumstances in large scale. In this paper, we created a VR training program by extracting realistic 3D models from close-range images from unmanned aircraft and digital camera on hand and observed several issues occurring during the implementation and the effectiveness in the case of a VR application in training for disaster mitigation. First of all, we built up a scenario of disaster and created 3D models after image processing with the close-range imagery. The 3D models were imported into Unity, a software for creation of augmented/virtual reality, as a background for android-based mobile phones and VR environment was created with C#-based script language. The generated virtual reality includes a scenario in which the trainer moves to a safe place along the evacuation route in the event of a disaster, and it was considered that the successful training can be obtained with virtual reality. In addition, the training through the virtual reality has advantages relative to actual evacuation training in terms of cost, space and time efficiencies.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.6
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• pp.243-250
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• 2019

Because of a moving UAV has a lot of potential/kinetic energy, if the UAV falls to the ground, it may have a lot of impact. Because this can lead to human casualities, in this paper, the population density area on the UAV flight path is defined as a dangerous area. The conventional UAV path flight was a passive form in which a UAV moved in accordance with a path preset by a user before the flight. Some UAVs include safety features such as a obstacle avoidance system during flight. Still, it is difficult to respond to changes in the real-time flight environment. Using public Big Data for UAV path flight can improve response to real-time flight environment changes by enabling detection of dangerous areas and avoidance of the areas. Therefore, in this paper, we propose a method to detect and avoid dangerous areas for UAVs by utilizing the Big Data collected in real-time. If the routh is designated according to the destination by the proposed method, the dangerous area is determined in real-time and the flight is made to the optimal bypass path. In further research, we will study ways to increase the quality satisfaction of the images acquired by flying under the avoidance flight plan.

• Korean Journal of Heritage: History & Science
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• v.42 no.4
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• pp.4-19
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• 2009

Though admitting that, in light of the recent archaeological trend, the excavation on relics of Sam-gama (a sort of kiln steaming the hemp) is increasingly reported, little efforts by far have been made not only to restore its traditional structure design but also to research hardly the change of hemp-steaming technologies in ages. In this regard, this paper shows the exploration of structural method and design as well as operability with regard to Sam-gut, traditional hemp-processing equipment that was recently reconstructed in Jungsun, Kangwon Province. Samgut, generally positioned at the waterside area, is an traditional device for steaming hemp to get bast fibers from the raw material of hemp, principally consisting of HWA-JIP(fire-place) to obtain steams by feeding fire ad Mong-got(boiling chamber) to make the hemp steamed after stacking. More specifically, thick round-logs were piled at the bottom of Hwajip prior to stacking stones around its circumferential area. When the timber positioned below gets burned with high temperature to heat stones existing in the upper side, waters then poured onto it after laying a bundle of grass and soil up to the boiled stones. If so, there generates hot vapor, which is conveyed to Monggot to steam the hemp. Functionally, it is of outstanding importance that Samgut is capable of producing high-temperature water vapors instantaneously under the intensive manpower, thus being constructed achievable for those purposes. The Samgut made by digging the ground is an instant facility that is closed after use. The remains, which were used to generate higher thermal power for steaming hemp, make it hard to excavate the historic traits because there left little vestiges in the soil, which means keen attention must be paid to find out the trace of Smgama relics. Future research stall be focused on collection of broader data regarding Samgut including technological review in extracting bas fibers from the hemp.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.23-38
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• 2021

In this paper, we analyzed the possibility of utilizing LX-PPS GNSS permanent stations whose antennas are installed on the building rooftop for the purpose of high-precision GNSS positioning services. We picked 15 pairs of adjacent GNSS permanent stations operated by LX-PPS and NGII, and then produced 3-year-long time series using the high-precision data processing software called GIPSY. Patterns and trends of position estimates were compared and analyzed. Horizontal and vertical deviations including the linear velocities coincide with the well-known crustal deformation rates of the Korean peninsula. We also observed almost the same annual or seasonal patterns from those nearby sites. After detrending the linear velocity, the amplitude and phase of annual signals almost perfectly match each other within the baseline length of 2 km. By subtracting seasonal signals, the RMS and standard deviations in LX-PPS PPGR with respect to NGII KANR are about 1, 2, and 5 mm in the north-south, east-west, and vertical directions, respectively. From this analysis it can be concluded that the rooftop-installed LX-PPS sites show similar level of stability and positioning performance comparable to those ground-mounted NGII stations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.977-985
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• 2020

KOMPSAT-3A launched in 2015 provides Middle InfraRed(MIR) images with 3.3~5.2㎛. Though the satellite provide high resolution images for estimating bright temperature of ground objects, it is different from existing satellites developed for natural science purposes. An atmospheric compensation process is essential in order to estimate the surface brightness temperature from a single channel MIR image of KOMPSAT-3A. However, even after the atmospheric compensation process, there is a brightness temperature error due to various factors. In this paper, we analyzed the cause of the brightness temperature estimation error by tracking signal flow from camera physical characteristics to image processing. Also, we study on possibility of improvement of MIR brightness temperature bias error of KOMPSAT-3A using GEOKOMPSAT-2A. After bias compensation of a real nighttime image with a large bias error, it was confirmed that the surface brightness temperature of KOMPSAT-3A and GEOKOMPSAT-2A have correlation. We expect that the GEOKOMPSAT-2A images will be helpful to improve MIR brightness temperature bias error of KOMPSAT-3A.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1219-1230
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• 2022

Multi-spectral drones in agricultural observation require quantitative and reliable data based on physical quantities such as radiance or reflectance in crop yield analysis. In the case of remote sensing data for crop monitoring, images taken in the same area over time-series are required. In particular, biophysical data such as leaf area index or chlorophyll are analyzed through time-series data under the same reference, it can be directly analyzed. So, comparable reflectance data are required. Orthoimagery using drone images, the entire image pixel values are distorted or there is a difference in pixel values at the junction boundary, which limits accurate physical quantity estimation. In this study, reflectance and vegetation index based on drone images were calculated according to the correction method of drone images for time-series crop monitoring. comparing the drone reflectance and ground measured data for spectral characteristics analysis.

• Journal of the Korean Geotechnical Society
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• v.38 no.12
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• pp.91-101
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• 2022

The 1995 Kobe earthquake caused a massive damage to the Port of Kobe. Therefore, it was pointed out that it was impossible to design port structures for Level II (Mw 6.5) earthquakes with quasi-static analysis and Allowable Stress Design methods. In Japan and the United States, where earthquakes are frequent, the most advanced design standards for port facilities are introduced and applied, and the existing seismic design standards have been converted to performance-based design. Since 1999, the Korean Port Seismic Design Act has established a definition of necessary facilities and seismic grades through research on facilities that require seismic design and their seismic grades. It has also established a performance-based seismic design method based on experimental verification. In the performance-based seismic design method of the breakwater proposed in this study, the acceleration time history on the surface of the original ground was subjected to a fast Fourier transform, followed by a filter processing that corrected the frequency characteristics corresponding to the maximum allowable displacement with respect to performance level of the breakwater and the filtered spectrum. The horizontal seismic coefficient for the equivalent static analysis considering the displacement was calculated by inversely transforming (i.e., subjected to an inverse fast Fourier transform) into the acceleration time history and obtaining the maximum acceleration value. In addition, experiments and numerical analysis were performed to verify the performance-based seismic design method of breakwaters suitable for domestic earthquake levels.

• Smart Structures and Systems
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• v.29 no.1
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• pp.1-16
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• 2022

Despite recent breakthroughs in deep learning and computer vision fields, the pixel-wise identification of tiny objects in high-resolution images with complex disturbances remains challenging. This study proposes a modified U-net for tiny crack segmentation in real-world steel-box-girder bridges. The modified U-net adopts the common U-net framework and a novel Self-Attention-Self-Adaption (SASA) neuron as the fundamental computing element. The Self-Attention module applies softmax and gate operations to obtain the attention vector. It enables the neuron to focus on the most significant receptive fields when processing large-scale feature maps. The Self-Adaption module consists of a multiplayer perceptron subnet and achieves deeper feature extraction inside a single neuron. For data augmentation, a grid-based crack random elastic deformation (CRED) algorithm is designed to enrich the diversities and irregular shapes of distributed cracks. Grid-based uniform control nodes are first set on both input images and binary labels, random offsets are then employed on these control nodes, and bilinear interpolation is performed for the rest pixels. The proposed SASA neuron and CRED algorithm are simultaneously deployed to train the modified U-net. 200 raw images with a high resolution of 4928 × 3264 are collected, 160 for training and the rest 40 for the test. 512 × 512 patches are generated from the original images by a sliding window with an overlap of 256 as inputs. Results show that the average IoU between the recognized and ground-truth cracks reaches 0.409, which is 29.8% higher than the regular U-net. A five-fold cross-validation study is performed to verify that the proposed method is robust to different training and test images. Ablation experiments further demonstrate the effectiveness of the proposed SASA neuron and CRED algorithm. Promotions of the average IoU individually utilizing the SASA and CRED module add up to the final promotion of the full model, indicating that the SASA and CRED modules contribute to the different stages of model and data in the training process.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.1-8
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• 2023

Modeling of artificial targets in Synthetic Aperture radar (SAR) mainly simulates radar signals reflected from the faces and edges of the 3D Computer Aided Design (CAD) model with a ray-tracing method, and modeling of the clutter on the Earth's surface uses a method of distinguishing types with similar distribution characteristics through statistical analysis of the SAR image itself. In this paper, man-made targets on the surface and background clutter on the terrain are integrated and made into a three-dimensional (3D) point cloud scatterer model, and SAR image were created through computational signal processing. The results of the SAR Stripmap image generation of the actual automobile based SAR radar system and the results analyzed using EM modeling or statistical distribution models are compared with this 3D point cloud scatterer model. The modeling target is selected as an bridge because it has the characteristic of having both water surface and ground terrain around the bridge and is also a target of great interest in both military and civilian use.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1C
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• pp.11-20
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• 2009

A new alternative method based on HWAW method to detect underground anomaly was introduced. The location of underground anomaly can be estimated by using 2-dimensional image of phase velocity image with position and wavelength based on distortion phenomena of surface wave due to underground anomaly. Overall procedure of proposed method such as field testing, signal processing and interpretation of the result was introduced. Numerical verification study was performed by using various ground models containing underground anomaly. According to the condition of anomaly, the propagation and reflection characteristics of surface wave were different and this could be more easily shown in the image of phase velocity. Some rules of distortion phenomena were found and these become clues for estimating underground anomaly in interpreting real field data. Field verification tests were performed with conventional geophysical methods such as DC resistivity method and GPR. Though field condition is not homogeneous like numerical models, similar distortion phenomena were found in the testing results and estimated location of underground anomaly was agreed well with the results of another geophysical methods.