• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.2
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• pp.137-148
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• 2014

A multi-rotor is an autonomous flying robot with multiple rotors. Depending on the number of the rotors, multi-rotors are categorized as tri-, quad-, hexa-, and octo-rotor. Given their rapid maneuverability and vertical take-off and landing capabilities, multi-rotors can be used in various applications such as surveillance and reconnaissance in hostile urban areas surrounded by high-rise buildings. In this paper, the unified dynamic model of each tri-, quad-, hexa-, and octo-rotor are presented. Then, based on derived mathematical equations, the operation and control techniques of each multi-rotor are derived and analyzed. For verifying and validating the proposed models, operation and control technique simulations are carried out.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.781-789
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• 2021

In this paper, we quantitatively analyzed the required UAV(Unmanned Aerial Vehicle) failure rate of small UAV (≤25kg) based on the harm to human caused by UAV crash to fly over the populated area. We compute the number of harm to human when UAV falls to the ground at certain descent point by using population density, car traffic, building to land ratio, number of floors of building data of urban area and UAV descent trajectory modeling. Based on this, the maximum allowable UAV failure rate is calculated to satisfy the Target Level of Safety(TLS) for each UAV descent point. Then we can generate the failure rate requirement in the form of map. Finally, we divide UAV failure rate into few categories and analyze the possible flight area for each failure rate categories. Considering the Youngwol area, it is analyzed that the UAV failure rate of at least 10^-4 (failure/flight hour) is required to access the residential area.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.171-187
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• 2022

Recently, the demand and development for non-face-to-face services are rapidly progressing due to the pandemic caused by the COVID-19, and attention is focused on the metaverse at the center. Entering the era of the 4th industrial revolution, Metaverse, which means a world beyond virtual and reality, combines various sensing technologies and 3D reconstruction technologies to provide various information and services to users easily and quickly. In particular, due to the miniaturization and economic increase of convergence sensors such as unmanned aerial vehicle(UAV) capable of high-resolution imaging and high-precision LiDAR(Light Detection and Ranging) sensors, research on digital-Twin is actively underway to create and simulate real-life twins. In addition, Game engines in the field of computer graphics are developing into metaverse engines by expanding strong 3D graphics reconstuction and simulation based on dynamic operations. This study constructed a mirror-world type metaverse that reflects real-world coordinate-based reality using Unreal Engine 5, a recently announced metaverse engine, with accurate 3D spatial information data of convergence sensors based on unmanned aerial system(UAS) and LiDAR. and then, spatial information contents and simulations for users were produced based on various public data to verify the accuracy of reconstruction, and through this, it was possible to confirm the construction of a more realistic and highly utilizable metaverse. In addition, when constructing a metaverse that users can intuitively and easily access through the unreal engine, various contents utilization and effectiveness could be confirmed through coordinate-based 3D spatial information with high reproducibility.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1607-1622
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• 2022

The purpose of this study is to determine the actual performance of cool roof in preventing absorbed solar radiation. The spatial correlation between surface temperature and absorbed solar radiation is the method by which the performance of a cool roof can be understood and evaluated. The research area of this study is the vicinity of Jangyu Mugye-dong, Gimhae-si, Gyeongsangnam-do, where an actual cool roof is applied. FLIR Vue Pro R thermal infrared sensor, Micasense Red-Edge multi-spectral sensor and DJI H20T visible spectral sensor was used for aerial photography, with attached to the drone DJI Matrice 300 RTK. To perform the spatial correlation analysis, thermal infrared orthomosaics, absorbed solar radiation distribution maps were constructed, and land cover features of roof were extracted based on the drone aerial photographs. The temporal scope of this research ranged over 9 points of time at intervals of about 1 hour and 30 minutes from 7:15 to 19:15 on July 27, 2021. The correlation coefficient values of 0.550 for the normal roof and 0.387 for the cool roof were obtained on a daily average basis. However, at 11:30 and 13:00, when the Solar altitude was high on the date of analysis, the difference in correlation coefficient values between the normal roof and the cool roof was 0.022, 0.024, showing similar correlations. In other time series, the values of the correlation coefficient of the normal roof are about 0.1 higher than that of the cool roof. This study assessed and evaluated the potential of an actual cool roof to prevent solar radiation heating a rooftop through correlation comparison with a normal roof, which serves as a control group, by using high-resolution drone images. The results of this research can be used as reference data when local governments or communities seek to adopt strategies to eliminate the phenomenon of urban heat islands.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.28-43
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• 2022

This study classified UAV image-based physical spatial types for parks in urban areas of Changwon City and analyzed thermal comfort characteristics according to physical spatial types by comparing them with ENVI-met thermal comfort results. Physical spatial types were classified into four types according to UAV-based NDVI and SVF characteristics. As a result of ENVI-met thermal comfort, the T_MRT difference between the tree-dense area and other areas was up to 30℃ or more, and it was 19. 6℃ at 16:00, which was the largest during the afternoon. As a result of analyzing UAV-based physical spatial types and thermal comfort characteristics by time period, it was confirmed that the physical spatial types with high NDVI and high SVF showed a similar to thermal comfort change patterns by time when using UAV, and the physical spatial types with dense trees and artificial structures showed a low correlation to thermal comfort change patterns by time when using UAV. In conclusion, the possibility of identifying the distribution of thermal comfort based on UAV images was confirmed for the spatial type consisting of open and vegetation, and the area adjacent to the trees was found to be more thermally pleasant than the open area. Therefore, in the urban planning stage, it is necessary to create an open space in consideration of natural covering materials such as grass and trees, and when using artificial covering materials, it is judged that spatial planning should be done considering the proximity to trees and buildings. In the future, it is judged that it will be possible to quickly and accurately identify urban climate phenomena and establish urban planning considering thermal comfort through ground LIDAR and In-situ measurement-based UAV image correction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.499-506
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• 2019

NDSM (Normalized Digital Surface Model) is key information for the detailed analysis of remote sensing data. Although NDSM can be simply obtained by subtracting a DTM (Digital Terrain Model) from a DSM (Digital Surface Model), in case of UAV (Unmanned Aerial Vehicle) data, it is difficult to get an accurate DTM due to high resolution characteristics of UAV data containing a large number of complex objects on the ground such as vegetation and urban structures. In this study, RGB-based UAV vegetation index, ExG (Excess Green) was used to extract initial seed points having low ExG values for region growing such that a DTM can be generated cost-effectively based on high resolution UAV data. For this process, local window analysis was applied to resolve the problem of erroneous seed point extraction from local low ExG points. Using the DSM values of seed points, region growing was applied to merge neighboring terrain pixels. Slope criteria were adopted for the region growing process and the seed points were determined as terrain points in case the size of segments is larger than 0.25 ㎡. Various slope criteria were tested to derive the optimized value for UAV data-based NDSM generation. Finally, the extracted terrain points were evaluated and interpolation was performed using the terrain points to generate an NDSM. The proposed method was applied to agricultural area in order to extract the above ground heights of crops and check feasibility of agricultural monitoring.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.15-26
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• 2017

The decrease of green space according to the urbanization has caused many environmental problems as the destruction of habitat, air pollution, heat island effect. With interest growing in natural view recently, proper management of evergreen tree which is lived even the winter season has been on the rise importantly. This study analyzed the distribution area of evergreen tree using vegetation index based on unmanned aerial vehicle (UAV). Firstly, RGB and NIR+RG camera were loaded in fixed-wing UAV and image mosaic was achieved using GCPs based on Pix4d SW. And normalized differences vegetation index (NDVI) and soil adjusted vegetation index (SAVI) was calculated by band math function from acquired ortho mosaic image. validation points were applied to evaluate accuracy of the distribution of evergreen tree for each range value and analysis showed that kappa coefficient marked the highest as 0.822 and 0.816 respectively in "NDVI > 0.5" and "SAVI > 0.7". The area of evergreen tree in "NDVI > 0.5" and "SAVI > 0.7" was $11,824m^2$ and $15,648m^2$ respectively, that was ratio of 4.8% and 6.3% compared to total area. It was judged that UAV could supply the latest and high resolution information to vegetation works as urban environment, air pollution, climate change, and heat island effect.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.895-905
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• 2019

Commercial Unmanned Aerial Vehicle (UAV) image processing software products currently used in the industry provides camera calibration information and block bundle adjustment accuracy. However, they provide mapping accuracy achievable out of input UAV images. In this paper, the quality of mapping is calculated by using orientation parameters from UAV image processing software. We apply the orientation parameters to the digital photogrammetric workstation (DPW) for verifying the reliability of the mapping quality calculated. The quality of mapping accuracy was defined as three types of accuracy: Y-parallax, relative model and absolute model accuracy. The Y-parallax is an accuracy capable of determining stereo viewing between stereo pairs. The Relative model accuracy is the relative bundle adjustment accuracy between stereo pairs on the model coordinates system. The absolute model accuracy is the bundle adjustment accuracy on the absolute coordinate system. For the experimental data, we used 723 images of GSD 5 cm obtained from the rotary wing UAV over an urban area and analyzed the accuracy of mapping quality. The quality of the relative model accuracy predicted by the proposed technique and the maximum error observed from the DPW showed precise results with less than 0.11 m. Similarly, the maximum error of the absolute model accuracy predicted by the proposed technique was less than 0.16 m.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.1
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• pp.9-18
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• 2019

The intensity and the number of days of high temperature occurrence are also high and record heat occurred. In addition, the global warming phenomenon is intensifying globally, and especially in South Korea, the urban heat island phenomenon is also occurring due to rapid urbanization due to rapid industrial development. As the temperature of the city rises, it causes problems such as the comfort of the residential living and the cooling load. In this study, the cool roof performance is evaluated according to the roof color to reduce these problems. Unlike previous studies, UAV(Unmanned Aerial Vehicle) thermal infrared camera was used to obtain the surface temperature (white, grey, green, blue, brown, black) according to the rooftop color by remote sensing technique. As a result, the surface temperature of white color was $11{\sim}20^{\circ}C$ lower than other colors. Also air conditioning temperature of white color was $1.5{\sim}4.4^{\circ}C$ lower than other colors and the digital thermometer of white color was about $1.5{\sim}3.5^{\circ}C$ lower than other colors. It was confirmed that the white cool roof performance is the best, and the UAV and the thermal infrared camera can confirm the cool roof performa.