• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.1
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• pp.93-106
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• 2016

This study aimed to estimate and evaluate the thermal mitigation of the urban tree canopy on the summer outdoor environment by quantitative use of mean radiant temperature. This study applied the SOLWEIG model based $T_{mrt}$ comparison method by using both (1) urban tree canopy presence examples and (2) urban tree canopy absence examples as constructed from airborne LiDAR system based three-dimensional point cloud data. As a result, it was found that an urban tree canopy can provide a decrease in the entire domain averaged daily mean $T_{mrt}$ about $5^{\circ}C$ and that the difference can increase up to $33^{\circ}C$ depending both on sun position and site conditions. These results will enhance urban microclimate studies such as indices (e.g., wind speed, humidity, air temperature) and biometeorology (e.g., perceived temperature) and will be used to support forest based public green policy development.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.139-149
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• 2008

A load effect by vehicles running on a road and an increase of traffic is distinguished as a serious issue in the level of bridges' maintenance and management since it causes a quick damage of bridges. The expansion joint is the most important since it makes vehicles' traveling amicable and stress or additional load harmful to molding patterns minimized. However, it is very difficult to measure its expansion length since vehicles continue to pass on the expansion joint. Therefore, the study could see that it was possible to carry out a qualitative and quantitative maintenance and management if its expansion length is extracted with images. The study could acquire three dimensional coordinates of expansion joints with images. As the results of calculating RMSE of check point residual at 32 points in A area and at 28 points in B area, both A and B areas had very good results of RMSEsms 0.829mm~1.680mm. As the results of analyzing expansion length and immediate value extracted by images, the study analyzed that RMSE of A area was 0.64mm and RMSE of B area was 0.28. The average residual of A area was 0.60% and the average rresidual of B area was 0.27%. Therefore, it is judged that it is more scientific and efficient than the past to measure expansion length with images at the time of repairing and managing bridges in the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.6
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• pp.541-547
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• 2017

Climate change has become the main cause of the exacerbation in natural disasters. Social Overhead Capital(SOC) structure needs to be checked for displacement and crack periodically to prevent damage and the collapse caused by natural disaster and ensure the safety. For efficient structure maintenance, the optical image technology is applied to the Structure Health Monitoring(SHM). However, optical image is sensitive to environmental factors. So it is necessary to verify its validity. In this paper, the accuracy of estimating the vertical displacement was verified with respect to environmental condition such as natural light, measurement distance, and the number of image sheets. The result of experiments showed that the effect of natural light on accuracy of estimating vertical displacement was the greatest of all. The measurement angle which was affected by the change in measurement distance was also important to check the vertical displacement. These findings will be taken into account by applying appropriate environmental condition to minimize errors when the bridge was measured by camera. It will also enable the application of optical images to the SHM.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.91-102
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• 2012

As the basis of the environmental ecological river management, this research developed a method of habitat classification using imagery information to understand a distribution characteristics of fish living in a natural river. First, topographic survey and investigation of discharge and water temperature were carried out to analyze hydraulic characteristics of fish habitat, and the unmanned aerial photography was applied to acquire river imagery at the observation time. Riffle, pool, and glide regions were selected as river habitat to analyze fish distribution characteristics. Analysis showed that the standard deviation of RGB on the riffle is higher than pool and glide because of fast stream flow. From the classification accuracy estimation on riffle region according to resolution and kernel size using the characteristics of standard deviation of RGB, the highest classification accuracy was 77.17% for resolution with 30cm and kernel size with 11. As the result of water temperature observation on pool and glide using infrared camera, they were $19.6{\sim}21.3^{\circ}C$ and $15.5{\sim}16.5^{\circ}C$ respectively with the differences of $4{\sim}5^{\circ}C$. Therefore it is possible to classify pool and glide region using the infrared photography information. The habitat classification to figure out fish distribution can be carried out more efficiently, if unmanned aerial photography system with RGB and infrared band is applied.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.28 no.3
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• pp.105-113
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• 2010

This study is for the preservation plan of the tradition space which is performed by the damage status analysis through performing the value assessment. Especially, it is an experimental study for finding the process and methods by analyzing the major element for the value assessment of the selected object's damage status through the expert group who are systematized in their interest to conserve the traditional structure in traditional space. For that purpose, this study should be performed by the fundamental understanding of the physical property of the Supyo-bridge and the condition of the selected site's environment. Meanwhile, this study has been done that 'map of the damage status distribution' for making records of damage status of the Supyo-bridge on the property utilized field measurement adapted by photogrammetry and assessment guidelines, which are for investigation on damage status of objects that are standardized 'Raccomandazioni Normal' which could be said construction culture assets management guidelines of Italian government. As the result of investigation, damage status of each part in the Supyo-bridge was mostly composed of damage by sediment and corrosion and in case of 9 damage types including corrosion, in consideration of physical and chemical properties and distribution status of those elements, it is made an judgement that is not working as a threatened factor regarding security of the Supyo-bridge. On the contrary, for the improvement landscape, in case of 'Thermoclastism' phenomenon observed in 'upper floor', 'Myungae stone' and 'bridge pier' is that when taking it into consideration that is widely distributed concentrated on the bridge pier, surface reinforcement job along with elimination of damage part will be judged to be requested for earliest treatment.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.501-509
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• 2018

Purpose: UAV-based photo measurements are being researched using UAVs in the space information field as they are not only cost-effective compared to conventional aerial imaging but also easy to obtain high-resolution data on desired time and location. In this study, the UAV-based high-resolution images were used to perform the land cover classification. Method: RGB cameras were used to obtain high-resolution images, and in addition, multi-distribution cameras were used to photograph the same regions in order to accurately classify the feeding areas. Finally, Land cover classification was carried out for a total of seven classes using created ortho image by RGB and multispectral camera, DSM(Digital Surface Model), NDVI(Normalized Difference Vegetation Index), GLCM(Gray-Level Co-occurrence Matrix) using RF (Random Forest), a representative supervisory classification system. Results: To assess the accuracy of the classification, an accuracy assessment based on the error matrix was conducted, and the accuracy assessment results were verified that the proposed method could effectively classify classes in the region by comparing with the supervisory results using RGB images only. Conclusion: In case of adding orthoimage, multispectral image, NDVI and GLCM proposed in this study, accuracy was higher than that of conventional orthoimage. Future research will attempt to improve classification accuracy through the development of additional input data.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.