• Journal of Information Processing Systems
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• v.19 no.5
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• pp.614-630
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• 2023

Dead trees significantly impact forest production and the ecological environment and pose constraints to the sustainable development of forests. A lightweight YOLOv4 dead tree detection algorithm based on unmanned aerial vehicle images is proposed to address current limitations in dead tree detection that rely mainly on inefficient, unsafe and easy-to-miss manual inspections. An improved logarithmic transformation method was developed in data pre-processing to display tree features in the shadows. For the model structure, the original CSPDarkNet-53 backbone feature extraction network was replaced by MobileNetV3. Some of the standard convolutional blocks in the original extraction network were replaced by depthwise separable convolution blocks. The new ReLU6 activation function replaced the original LeakyReLU activation function to make the network more robust for low-precision computations. The K-means++ clustering method was also integrated to generate anchor boxes that are more suitable for the dataset. The experimental results show that the improved algorithm achieved an accuracy of 97.33%, higher than other methods. The detection speed of the proposed approach is higher than that of YOLOv4, improving the efficiency and accuracy of the detection process.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.39-45
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• 2016

In this study, with arbitrary reference points on the water, photogrammetry accuracy analysis was conducted using unmanned aerial vehicle(UAV). A small reservoir is a research area, and twenty buoys were used as arbitrary reference points. Errors of location coordinate were identified with control of amounts of used reference points. cases are categorized by index scores per photos. Accuracy of X is 0.141m~0.166m and accuracy of Y is 0.136m~0.241m. Considering that allowable error for the maritime boundary survey is ${\pm}2m$, it is possible to get the accuracy data available for the photogrammetry of UAV using an reference point. In addition, the coefficient of correlation between the number of reference points per unit and number of buoys used as reference point and the ratio of the reference point per square measure, and percentage of buoys used as reference point and the coefficient of x and y were performed. Each element, x, and y showed a strong correlation and the coefficient of number of buoys used as reference point was irrelevant. The results of this correlation analysis can be analyzed that the number of reference points used in each picture is greater than the actual number of reference points used in location accuracy.

• 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.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.941-951
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• 2018

Utilization and demand of UAV (unmanned aerial vehicle) for the generation of 3D city model are increasing. In this study, we performed an experiment to adjustment position/orientation of UAV with incomplete attitude information and to extract point cloud data. In order to correct the attitude of the UAV, the rotation angle was calculated by using the continuous position information of UAV movements. Based on this, the corrected position/orientation information was obtained by applying IBA (Incremental Bundle Adjustment) based on photogrammetry. Each pair was transformed into an epipolar image, and the MDR (Multi-Dimensional Relaxation) technique was applied to obtain high precision DSM. Each extracted pair is aggregated and output in the form of a single point cloud or DSM. Using the DJI inspire1 and Phantom4 images, we can confirm that the point cloud can be extracted which expresses the railing of the building clearly. In the future, research will be conducted on improving the matching performance and establishing sensor models of oblique images. After that, we will continue the image processing technology for the generation of the 3D city model through the study of the extraction of 3D cloud It should be developed.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.136-142
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• 2021

Open-pit mine development requires continuous management because of topographical changes and there is a risk of accidents if the current status survey is performed directly in the process of calculating the earthwork. In this study, the application of UAV photogrammetry, which can acquire spatial information without direct human access, was applied to open-pit mines development area and analyzed the accuracy, earthwork, and mountain restoration plan to determine its applicability. As a result of accuracy analysis at checkpoint using ortho image and Digital Surface Model(DSM) by UAV photogrammetry, Root Mean Square Error(RMSE) is 0.120 m in horizontal and 0.150 m in vertical coordinates. This satisfied the tolerance range of 1:1,000 digital map. As a result of the comparison of the earthwork, UAV photogrammetry yielded 11.7% more earthwork than the conventional survey method. It is because UAV photogrammetry shows more detailed topography. And result of monitoring mountain restoration showed possible to determine existence of rockfall prevention nets and vegetation. If the terrain changes are monitored by acquiring images periodically, the utility of UAV photogrammetry will be further useful to open-pit mine development.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.97-108
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• 2016

In this paper, we consider a cooperative monitoring network, which consists of a large number of UAVs, in order to promptly detect event in a disaster area. A command center may not be able to control each UAV individually due to resource constraints. Therefore, UAVs need to autonomously construct a mobile monitoring network in order to maximize monitoring coverage and to adapt the network formation according to environment changes in the disaster area. To that end, we propose multiple UAVs-based cooperative monitoring schemes that uses virtual forces. In this monitoring scheme, an effective monitoring is enabled by extending monitoring coverage using each UAV's circle movements. The UAVs-based monitoring network can also be splitted or merged in order to increase the monitoring effectiveness. Through simulations, we show that the proposed scheme can effectively monitor a large area and achieve a high event detection ratio.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.2
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• pp.459-466
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• 2017

Several reservoirs that were managed by local governments and the Korea Rural Community Corporation have recently collapsed. One of them is the Goeyeon reservoir in Yeongcheon-si, Gyeongsangbuk-do that collapsed mainly around the spillway due to heavy rain at 9 O'clock, on 21 August 2014. The Goeyeon reservoir was an aging agricultural reservoir over 70 years since it was built. In this study, the collapse situation of the reservoir was reproduced through the DAMBRK model. Flood inundation maps were reconstructed for the breach outflow of the dam analyzed by the DAMBRK model. We estimated the breach duration and outflow of the reservoir as compared with the inundation image taken by the Unmanned Aerial Vehicle (UAV) at the time when the Goeyeon reservoir collapsed. The results of this study are expected to be useful for predicting damage in the downstream inundation area when a reservoir collapses.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.6
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• pp.458-464
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• 2013

This paper presents an algorithm for autonomous landing approach of a unmanned aerial vehicle. The main purpose of the autonomous landing approach in this study is to help a safe landing at night. From any initial position of the aircraft when this function is engaged, a flight path command is generated from the initial position. The shortest combination of an initial circular arc, a straight line segment, and a final circular arc is chosen for the flight path that will lead the aircraft to one end of runway for a landing. The algorithm is initially validated through numerous simulations with various initial conditions of aircraft. Then it is successfully validated through a number of flight tests.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2005.11a
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• pp.149-153
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• 2005

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle). In ordo to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. In this investigation, it was found that the newly proposed map generation method would be more effective than the traditional scaling method.