• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.599-608
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• 2017

Cracks on the asphalt road surface can affect the speed of the car, the consumption of fuel, the ride quality of the road, and the durability of the road surface. Such cracks in roads can lead to very dangerous consequences for long periods of time. To prevent such risks, it is necessary to identify cracks and take appropriate action. It takes too much time and money to do it. Also, it is difficult to use expensive laser equipment vehicles for initial cost and equipment operation. In this paper, we propose an effective detection method of road surface defect using ROI (Region of Interest) setting and cany edge detection method using UAV image. The results of this study can be presented as efficient method for road surface flaw detection and maintenance using UAV. In addition, it can be used to detect cracks such as various buildings and civil engineering structures such as buildings, outer walls, large-scale storage tanks other than roads, and cost reduction effect can be expected.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.4
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• pp.369-377
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• 2012

Recently, development of IT technology and enhancement of spatial information technology increases the necessity about effective technology of damage investigation in the area of disaster prevention. Quick damage investigation is necessary to deal with the natural hazard and plan the recovery. To do this, UAV is the useful mean for quick damage investigation. In this study, it was evaluated based on UAV that utilization of real-time aerial monitoring system for effective damage investigation of natural hazard. Accuracy analysis was implemented to evaluate the application of this system. And utilization of damage investigation was evaluated based on the domestic regulations that is appled the system according to the type of hazard. As a result, damage investigation was possible about house, farmland, agriculture and forestry facilities and public facilities. Henceforth, it will be effectively possible to inspect damage for natural disaster and to establish restoration plan through utilization of acceptable image data by Real-time Aerial Monitoring System in real various natural disaster.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.657-672
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• 2016

Coastal erosion happens frequently in many different types. To control coastal erosion zone effectively and establish response plans, we need to accumulate data indicating topography changes through monitoring the erosion situation continuously. UAV photogrammetric systems, which can fly autonomously at a low altitude, are recommended as an economical and precision means to monitor the coastal zones. In this study, we aim to verify the accuracy of the generated orthoimages and DEM as a result of processing the UAV data of a coastal zone by comparing them with various reference data. We established a verification routine and examined the possibilities of applying the UAV photogrammetric systems to monitoring coastal erosion by checking the analyzed accuracy by the routine. As a result of verifying the generated the geospatial information from acquired data under various configurations, the horizontal and vertical accuracy (RMSE) were about 2.7 cm and 4.8 cm respectively, which satisfied 5 cm, the accuracy required for coastal erosion monitoring.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.431-441
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• 2016

Since the use of UAV (Unmanned Aerial Vehicle) is convenient for the acquisition of data on broad or inaccessible regions, it is nowadays used to establish spatial information for various fields, such as the environment, ecosystem, forest, or for military purposes. In this study, the process of estimating FVC (Fractional Vegetation Cover), based on multi-spectral UAV, to overcome the limitations of conventional methods is suggested. Hence, we propose that the FVC map is generated by using multi-spectral imaging. First, two types of result classifications were obtained based on RF (Random Forest) using RGB images and NDVI (Normalized Difference Vegetation Index) with RGB images. Then, the result map was reclassified into vegetation and non-vegetation. Finally, an FVC map-based RF were generated by using pixel calculation and FVC map-based GI (Gutman and Ignatov) model were indirectly made by fixed parameters. The method of adding NDVI shows a relatively higher accuracy compared to that of adding only RGB, and in particular, the GI model shows a lower RMSE (Root Mean Square Error) with 0.182 than RF. In this regard, the availability of the GI model which uses only the values of NDVI is higher than that of RF whose accuracy varies according to the results of classification. Our results showed that the GI mode ensures the quality of the FVC if the NDVI maintained at a uniform level. This can be easily achieved by using a UAV, which can provide vegetation data to improve the estimation of FVC.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.249-260
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• 2009

The georeferencing accuracy of the sensory data acquired by an aerial monitoring system heavily depends on the performance of the GPS/IMU mounted on the system. The employment of a high performance but expensive GPS/IMU unit causes to increase the developmental cost of the overall system. In this study, we simulate the images and GPS/IMU data acquired by an UAV-based aerial monitoring system using an inexpensive integrated GPS/IMU of a MEMS type, and perform the image georeferencing by applying the aerial triangulation to the simulated sensory data without any GCP. The image georeferencing results are then analyzed to assess the accuracy of the estimated exterior orientation parameters of the images and ground points coordinates. The analysis indicates that the RMSEs of the exterior orientation parameters and ground point coordinates is significantly decreased by about 90% in comparison with those resulted from the direct georeferencing without the aerial triangulation. From this study, we confirmed the high possibility to develop a low-cost real-time aerial monitoring system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.175-186
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• 2017

In this study was to survey method of national/public land actual condition survey to utilization of UAV, in order to evaluate the economic and accuracy. we carried out the comparative evaluation of the cadastral status surveying in terms of accuracy of parcel checkpoint, economical costs. The results are summarized as follows. First, average position error of the orthoimage was 0.033m in X error, 0.023m in Y error when the RMSE average calculated 0.046m from the intersection of plane distance connections. Secondly, it was appeared the accuracy of the orthophotograph is 0.076m at the maximum RMSE of the UAV orthoimage check point and 0.042m at the minimum RMSE compared with the VRS-GNSS survey results. Thirdly, when the allowable error specified in the implementing regulation of the current cadastral survey is applied, all of the checkpoint of 0.360m tolerance corresponding to the scale of 1/1,200 is satisfied. Finally, UAV utilization method in national/public land actual condition survey is 26,497,436(KRW) cheaper than cadastral survey method for In the economic evaluation of national/public land actual condition survey. Therefore, as a result of this study shows that the method of utilizing UAV in the national/public land actual condition survey satisfies legal standards in terms of accuracy and economical aspect is a way to further reduce the local government budget.

• Korean Journal of Computational Design and Engineering
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• v.22 no.1
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• pp.44-58
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• 2017

The inspection for building occupancy authorization has lacked objectivity due to manual measurement methods. This is why connivance of the illegal buildings has been rampant, which has led to so many incidents. Consequently, this law has lost its intent to protect people's lives and property. In this study, for the purpose of improvement of this law, the research was conducted by the utilization of unmanned aerial vehicle for automated inspection for building occupancy authorization. Theoretical considerations about building occupancy authorization and the trend of UAV technology were accomplished. Secondly, a series of reverse engineering was conducted including digital photography, network RTK-VRS surveying and post-processing data. Thirdly, the resultant spatial information was used for building occupancy inspection authorization in a BIM platform and the effectiveness and applicability of UAV-based inspection was analyzed. As a result, methodology for UAV-based automated building occupancy inspection authorization was derived. And it was found that eleven items would be possible to be automated among thirty total items for building occupancy authorization. Also it was found that UAV-based automated inspection could be valid in inspecting building occupancy authorization due to authentic accuracy, effectiveness and applicability with government policy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.49-56
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• 2020

In this study, we analyzed the sharpness of UAV-images using the gradient formula and produced a MATLAB GUI (Graphical User Interface)-based sharpness analysis tool for easy use. In order to verify the reliability of the proposed sharpness analysis method, sharpness values of the UAV-images measured by the proposed method were compared with those by measured the commercial software Metashape of the Agisoft. As a result of measuring the sharpness with both tools on 10 UAV-images, sharpness values themselves were different from each other for the same image. However, there was constant bias of 011 ~ 0.20 between two results, and then the same sharpness was obtained by eliminating this bias. This fact proved the reliability of the proposed sharpness analysis method in this study. In addition, in order to verify the practicality of the proposed sharpness analysis method, unsharp images were classified as low quality ones, and the quality of orthoimages was compared each other, which were generated included low quality images and excluded them. As a result, the quality of orthoimage including low quality images could not be analyzed due to blurring of the resolution target. However, the GSD (Ground Sample Distance) of orthoimage excluding low quality images was 3.2cm with a Bar target and 4.0cm with a Siemens star thanks to the clear resolution targets. It therefore demonstrates the practicality of the proposed sharpness analysis method in this study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.741-747
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• 2009

For construction of 3D virtual city models, airborne digital cameras, laser scanners, multi-oblique photograph systems and other devices are currently being used. With such advanced techniques, precise 3D spatial information can be collected and high quality 3D city models can be built in a considerably large area. The 3D spatial information to be built has to provide the latest information that quickly reflects the causes of any change due to urban development. In this study, a UAV photogrammetric method using low cost UAV and digital camera was proposed to acquire and update 3D spatial information effectively on small areas where information continuously change. In the proposed UAV photogrammetric method, the elements of interior orientation were acquired through camera calibration and the vertical and oblique photographs were taken at 9 points and the 3D drawing of ground control points and buildings was performed using 20 images among the pictured images. This study also analyzed the accuracy of the proposed method comparing with ground survey data and digital map in order to examine whether the method can be used in on-demand 3D spatial information update on relatively small areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.353-361
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• 2020

Due to the rapid urbanization, various traffic problems such as traffic jams during commute and regular traffic jams are occurring. In order to solve these traffic problems, it is necessary to quickly and accurately estimate and analyze traffic volume. ITS (Intelligent Transportation System) is a system that performs optimal traffic management by utilizing the latest ICT (Information and Communications Technology) technologies, and research has been conducted to analyze fast and accurate traffic volume through various techniques. In this study, we proposed a deep learning-based vehicle detection method using UAV (Unmanned Aerial Vehicle) video for real-time traffic analysis with high accuracy. The UAV was used to photograph orthogonal videos necessary for training and verification at intersections where various vehicles pass and trained vehicles by classifying them into sedan, truck, and bus. The experiment on UAV dataset was carried out using YOLOv3 (You Only Look Once V3), a deep learning-based object detection technique, and the experiments achieved the overall object detection rate of 90.21%, precision of 95.10% and the recall of 85.79%.