• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.841-850
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• 2019

The purpose of this study is to strengthen the capability of rapid mapping for disaster through improving the positioning accuracy of mapping and fusion of multi-sensing point cloud data derived from Unmanned Aerial Vehicles (UAVs) and disaster investigation vehicle. The positioning accuracy was evaluated for two procedures of drone mapping with Agisoft PhotoScan: 1) general geo-referencing by self-calibration, 2) proposed geo-referencing with optimized camera model by using fixed accurate Interior Orientation Parameters (IOPs) derived from indoor camera calibration test and bundle adjustment. The analysis result of positioning accuracy showed that positioning RMS error was improved 2~3 m to 0.11~0.28 m in horizontal and 2.85 m to 0.45 m in vertical accuracy, respectively. In addition, proposed data fusion approach of multi-sensing point cloud with the constraints of the height showed that the point matching error was greatly reduced under about 0.07 m. Accordingly, our proposed data fusion approach will enable us to generate effectively and timelinessly ortho-imagery and high-resolution three dimensional geographic data for national disaster management in the future.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.2
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• pp.107-120
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• 2021

Electric-powered distributed propulsion aircraft possess a complex wake flow and mutual interference with the airframe, due to the use of many propellers. Accordingly, in the early design stage, rapid aerodynamic and load analysis considering the effect of propellers for various configurations and flight conditions are required. In this study, an efficient panel-based aerodynamic analysis method that can take into account the propeller effects is developed and validated. The induced velocity field in the region of propeller wake is calculated based on Actuator Disk Theory (ADT) and is considered as the boundary condition at the vehicle's surface in the three-dimensional steady source-doublet panel method. Analyses are carried out by selecting an isolated propeller of the Korea Aerospace Research Institute (KARI)'s Quad Tilt Propeller (QTP) aircraft and the propeller-wing configuration of the former experimental study as benchmark problems. Through comparisons with the results of computational fluid dynamics (CFD) based on actuator methods, the wake velocity of propeller and the changes in the aerodynamic load distribution of the wing due to the propeller operation are validated. The method is applied to the analysis of the Optional Piloted Personal Aerial Vehicle (OPPAV) and QTP, and the practicality and validity of the method are confirmed through comparison and analysis of the computational time and results with CFD.

• Applied Chemistry for Engineering
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• v.32 no.4
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• pp.361-370
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• 2021

Carbon fiber reinforced polymer (CFRP) is one of the composite materials, which has a unique property that is lightweight but strong. The CFRPs are widely used in various industries where their unique characteristics are required. In particular, electric and unmanned aerial vehicles critically need lightweight parts and bodies with sufficient mechanical strengths. Vehicles using the battery as a power source should simultaneously meet two requirements that the battery has to be safely protected. The vehicle should be light of increasing the mileage. The CFRP has considered as the one that satisfies the requirements and is widely used as battery housing and other vehicle parts. On the other hand, in the battery area, carbon fibers are intensively tested as battery components such as electrodes and/or current collectors. Furthermore, using carbon fibers as both structure reinforcements and battery components to build a structural battery is intensively investigated in Sweden and the USA. This mini-review encompasses recent research trends that cover the classification of structural batteries in terms of functionality of carbon fibers and issues and efforts in the battery and discusses the prospect of structural batteries.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.553-562
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• 2017

GPS (Global Positioning System) receiver among various sensors mounted on UAV (Unmanned Aerial Vehicle) helps to perform various functions such as hovering flight and waypoint flight based on GPS signals. GPS receiver can be used in an environment where GPS signals are smoothly received. However, recently, the use of UAV has been diversifying into various fields such as facility monitoring, delivery service and leisure as UAV's application field has been expended. For this reason, GPS signals may be interrupted by UAV's flight in a shadow area where the GPS signal is limited. Multipath can also include various noises in the signal, while flying in dense areas such as high-rise buildings. In this study, we used analytical photogrammetry and auto tracking total station technique for 3D positioning of UAV. The analytical photogrammetry is based on the bundle adjustment using the collinearity equations, which is the geometric principle of the center projection. The auto tracking total station technique is based on the principle of tracking the 360 degree prism target in units of seconds or less. In both techniques, the target used for positioning the UAV is mounted on top of the UAV and there is a geometric separation in the x, y and z directions between the targets. Data were acquired at different speeds of 0.86m/s, 1.5m/s and 2.4m/s to verify the flight speed of the UAV. Accuracy was evaluated by geometric separation of the target. As a result, there was an error from 1mm to 12.9cm in the x and y directions of the UAV flight. In the z direction with relatively small movement, approximately 7cm error occurred regardless of the flight speed.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.989-1006
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• 2020

Building change monitoring based on building detection is one of the most important fields in terms of monitoring artificial structures using high-resolution multi-temporal images such as CAS500-1 and 2, which are scheduled to be launched. However, not only the various shapes and sizes of buildings located on the surface of the Earth, but also the shadows or trees around them make it difficult to detect the buildings accurately. Also, a large number of misdetection are caused by relief displacement according to the azimuth and elevation angles of the platform. In this study, object-based building detection was performed using the azimuth angle of the Sun and the corresponding main direction of shadows to improve the results of building change detection. After that, the platform's azimuth and elevation angles were used to detect changed buildings. The object-based segmentation was performed on a high-resolution imagery, and then shadow objects were classified through the shadow intensity, and feature information such as rectangular fit, Gray-Level Co-occurrence Matrix (GLCM) homogeneity and area of each object were calculated for building candidate detection. Then, the final buildings were detected using the direction and distance relationship between the center of building candidate object and its shadow according to the azimuth angle of the Sun. A total of three methods were proposed for the building change detection between building objects detected in each image: simple overlay between objects, comparison of the object sizes according to the elevation angle of the platform, and consideration of direction between objects according to the azimuth angle of the platform. In this study, residential area was selected as study area using high-resolution imagery acquired from KOMPSAT-3 and Unmanned Aerial Vehicle (UAV). Experimental results have shown that F1-scores of building detection results detected using feature information were 0.488 and 0.696 respectively in KOMPSAT-3 image and UAV image, whereas F1-scores of building detection results considering shadows were 0.876 and 0.867, respectively, indicating that the accuracy of building detection method considering shadows is higher. Also among the three proposed building change detection methods, the F1-score of the consideration of direction between objects according to the azimuth angles was the highest at 0.891.

• The Korean Journal of Air & Space Law and Policy
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• v.29 no.2
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• pp.135-161
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• 2014

An unmanned aerial vehicle (UAV), commonly known as a drone and also referred to as an unpiloted aerial vehicle and a remotely piloted aircraft (RPA) by the International Civil Aviation Organization (ICAO), is an aircraft without a human pilot aboard. ICAO classify unmanned aircraft into two types under Circular 328 AN/190. Unmanned aircraft, which is the core of the development of the aviation industry. However, there are also elements of the legal dispute. Unmanned aircraft are manufactured in small size, it is possible to shoot a record peripheral routes stored in high-performance cameras and sensors without the consent of the citizens, there is a risk of invasion of privacy. In addition, the occurrence of the people of invasion of privacy is expected to use of civilian unmanned aircraft. If the exposure of private life that people did not want for unmanned aircraft has occurred, may occur liability to the operator of unmanned aircraft, this is a factor to be taken into account for the development of unmanned aircraft industry. In the United States, which is currently led by the unmanned aircraft industry, policy related to unmanned aircraft, invasion of privacy is under development, is preparing an efficient measures making. Unmanned aircraft special law has not been enforced. So there is a need for legal measures based on infringement of privacy by the unmanned aircraft. US was presented Privacy Protection Act of unmanned aircraft (draft). However Korea has many laws have been enacted, to enact a new law, but will be able to harm the legal stability, there is a need for the enactment of laws for public safety of life. Although in force Personal Information Protection Law, unmanned aerospace, when the invasion of privacy occurs, it is difficult to apply the Personal Information Protection Law. So, it was presented a privacy protection bill with infringement of privacy of unmanned aircraft in the reference US legislation and the Personal Information Protection Act.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.327-336
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• 2019

Soybean is one of the most important crops of which the grains contain high protein content and has been consumed in various forms of food. Soybean plants are generally cultivated on the field and their yield and quality are strongly affected by climate change. Recently, the abnormal climate conditions, including heat wave and heavy rainfall, frequently occurs which would increase the risk of the farm management. The real-time assessment techniques for quality and growth of soybean would reduce the losses of the crop in terms of quantity and quality. The objective of this work was to develop a simple model to estimate the growth of soybean plant using a multispectral sensor mounted on a rotor-wing unmanned aerial vehicle(UAV). The soybean growth model was developed by using simple linear regression analysis with three phenotypic data (fresh weight, dry weight, leaf area index) and two types of vegetation indices (VIs). It was found that the accuracy and precision of LAI model using GNDVI (R²= 0.789, RMSE=0.73 ㎡/㎡, RE=34.91%) was greater than those of the model using NDVI (R²= 0.587, RMSE=1.01 ㎡/㎡, RE=48.98%). The accuracy and precision based on the simple ratio indices were better than those based on the normalized vegetation indices, such as RRVI (R²= 0.760, RMSE=0.78 ㎡/㎡, RE=37.26%) and GRVI (R²= 0.828, RMSE=0.66 ㎡/㎡, RE=31.59%). The outcome of this study could aid the production of soybeans with high and uniform quality when a variable rate fertilization system is introduced to cope with the adverse climate conditions.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.

• The Korean Journal of Air & Space Law and Policy
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• v.35 no.1
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• pp.153-180
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• 2020

This study is meaningful in finding out what legal and policy issues need to be improved in order to foster the aircraft industry, which is relatively underdeveloped compared to the fact that some heavy industries, such as the automobile industry and shipbuilding industry, have achieved a high level of production and technology globally. Korea's aircraft industry has been growing at a slower pace than other industries, largely due to the country's economic growth and the lack of a market structure to properly use variables such as the level of development in related industries, aircraft technology and demand for aircraft manufacturing. While most industries are privately led by the market structure of the competition system, heavy industries such as the aircraft industry generally grow under the market structure of the incomplete competition system, because only by securing huge initial investment costs, high technology, and sufficient demand, they can maintain minimum economic feasibility. The Korean aircraft industry was focused on developing and mass-producing military aircraft focusing on military demand, but it sought to turn the tide by signing the BASA (Bileral Aviation Safety Agreement) with the U.S. A preliminary feasibility study was conducted in 2010 to develop next-generation medium-sized aircraft, but was cancelled due to differences in position with Canada's Bombardier, which is subject to the concourse, and Korea Aerospace Industries (KAI) is pushing for the production of Bombardier's Q400 license on its own. Compared to the mid-to-large sized civil aircraft that are facing difficulties in development, KAI and KARI are successfully developing technologies to unmanned aerial vehicles and civil helicopters. In addition, the unmanned aerial vehicle sector is not yet suitable for manufacturers that have an exclusive global influence, so we believe that it is necessary to pursue government-led research and development projects with a focus on the areas of commercial helicopters and unmanned aerial vehicles in order to foster the aircraft industry in the future. In addition, since military aircraft such as KT-1 and T-50 are currently being exported smoothly, and it cannot be overlooked that the biggest demand for aircraft manufacturing in the Korea is the military, it is necessary to push forward national R&D projects and defense R&D program simultaneously to enable both civilian-military development. However, there are many differences between the two projects in the way they are implemented, the department in charge and the royalty system. Through this study, we learned about the technology ownership and implementation rights of national R&D projects and defense R&D programs, as well as the royalty system. In addition, problems with the system were identified and improvement measures were derived.

• 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.