• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.521-535
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• 2023

When converting rice fields into fields,sorghum (sorghum bicolor L. Moench) has excellent moisture resistance, enabling stable production along with soybeans. Therefore, it is a crop that is expected to improve the self-sufficiency rate of domestic food crops and solve the rice supply-demand imbalance problem. However, there is a lack of fundamental statistics,such as cultivation fields required for estimating yields, due to the traditional survey method, which takes a long time even with a large manpower. In this study, U-Net was applied to RGB images based on unmanned aerial vehicle to confirm the possibility of non-destructive segmentation of sorghum cultivation fields. RGB images were acquired on July 28, August 13, and August 25, 2022. On each image acquisition date, datasets were divided into 6,000 training datasets and 1,000 validation datasets with a size of 512 × 512 images. Classification models were developed based on three classes consisting of Sorghum fields(sorghum), rice and soybean fields(others), and non-agricultural fields(background), and two classes consisting of sorghum and non-sorghum (others+background). The classification accuracy of sorghum cultivation fields was higher than 0.91 in the three class-based models at all acquisition dates, but learning confusion occurred in the other classes in the August dataset. In contrast, the two-class-based model showed an accuracy of 0.95 or better in all classes, with stable learning on the August dataset. As a result, two class-based models in August will be advantageous for calculating the cultivation fields of sorghum.

• Tunnel and Underground Space
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• v.26 no.1
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• pp.24-31
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• 2016

Recently, many studies have been conducted to use fixed-wing and rotary-wing unmanned aerial vehicles (UAVs, Drones) for topographic surveying in open-pit mines. Because the fixed-wing and rotary-wing UAVs have different characteristics such as flight height, speed, time and performance of mounted cameras, their results of topographic surveying at a same site need to be compared. This study selected a construction site in Yangsan-si, Gyeongsangnam-do, Korea as a study area and compared the topographic surveying results from a fixed-wing UAV (SenseFly eBee) and a popular rotary-wing UAV (DJI Phantom2 Vision+). As results of data processing for aerial photos taken from eBee and Phantom2 Vision+, orthomosaic images and digital surface models with about 4 cm grid spacing could be generated. Comparisons of the X, Y, Z-coordinates of 7 ground control points measured by differential global positioning system and those determined by eBee and Phantom2 Vision+ revealed that the root mean squared errors of X, Y, Z-coordinates were around 10 cm, respectively.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.39-48
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• 2015

Lately, Unmanned Aerial Vehicles(UAV), Unmanned Aerial Systems(UAS) or also often known as drones, as a data acquisition platform and as a measurement instrument are becoming attractive for many photogrammetric surveying applications, especially generation of the high density point clouds(HDPC). This paper presents the performance evaluation of a low-cost rotary wing quadrocopter UAS for generation of the HDPC in a test bed environment. Its performance was assessed by comparing the coordinates of UAS based HDPC to the results of Network RTK GNSS surveying with 62 ground check points. The results indicate that the position RMSE of the check points are ${\sigma}_H={\pm}0.102m$ in Horizonatal plane, and ${\sigma}_V={\pm}0.209m$ in vertical, and the maxium deviation of Elevation was 0.570m within block area of ortho-photo mosaic. Therefore the required level of accuracy at NGII for production of ortho-images mosaic at a scale of 1:1000 was reached, UAS based imagery was found to make use of it to update scale 1:1000 map. And also, since this results are less than or equal to the required level in working rule agreement for airborne laser scanning surveying of NGII for Digital Elevation Model generation of grids $1m{\times}1m$ and 1:1000 scale, could be applied with production of topographic map and ortho-image mosaic at a scale of 1:1000~1:2500 over small-scale areas.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.3
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• pp.57-67
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• 2015

Land characteristics should be surveyed in an accurate and objective manner as they are important data to the formation of land prices. The ambiguous survey and estimation guidelines, however, make it possible for surveyors to intervene with their subjective judgments. There is thus a definite need for improvement. It is also extremely important to survey the characteristics of individual land lots in an accurate and objective manner in order to estimate officially assessed land prices in a swift and accurate way. For objective land appraisal and evaluation, this study set out to objectively identify the characteristics of lots according to various topographical conditions by using UAV based high quality geospatial information, panorama VR images, and GIS analysis technique and thus make a contribution to a rational and consistent estimation system of officially assessed land prices. Trying to assess the technique proposed in the study, the investigator analyzed the old data about the officially assessed land prices of the subject areas and then the evaluation data of certified public appraisers.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.201-207
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• 2020

In this study, the practicality of unmanned aerial vehicle photography information was identified. Therefore, a total of four consecutive surveys were conducted on the field-level survey areas among the areas subject to photography using unmanned aerial vehicles, and the changes in crop conditions were analyzed using pictures of unmanned aerial vehicles taken during each survey. It is appropriate to collect and utilize photographic information by directly taking pictures of the survey area according to the time of the on-site survey using unmanned aerial vehicles in the field layer, which is an area where many changes in topography, crop vegetation, and crop types are expected. And it turned out that it was appropriate to utilize satellite images in consideration of economic and efficient aspects in relatively unchanged rice paddies and facilities. If the survey area is well equipped with systems for crop cultivation, deep learning can be utilized in real time by utilizing libraries after obtaining photographic data for a certain area using unmanned aircraft in the future. Through this process, it is believed that it can be used to analyze the overall crop and shipment volume by identifying the crop status and surveying the quantity per unit area.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.537-549
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• 2023

The distribution characteristics of tidal flat sediment components are used as an essential data for coastal environment analysis and environmental impact assessment. Therefore, a reliable classification map of surface sedimentary facies is essential. This study evaluated the applicability of regression kriging to generate a classification map of the sedimentary facies of tidal flats. For this aim, various factors such as the number of field survey data and remote sensing-based auxiliary data, the effect of regression models on regression kriging, and the comparison with other prediction methods (univariate kriging and regression analysis) on surface sedimentary facies classification were investigated. To evaluate the applicability of regression kriging, a case study using unmanned aerial vehicle (UAV) data was conducted on the Hwang-do tidal flat located at Anmyeon-do, Taean-gun, Korea. As a result of the case study, it was most important to secure an appropriate amount of field survey data and to use topographic elevation and channel density as auxiliary data to produce a reliable tidal flat surface sediment facies classification map. In addition, regression kriging, which can consider detailed characteristics of the sediment distributions using ultra-high resolution UAV data, had the best prediction performance compared to other prediction methods. It is expected that this result can be used as a guideline to produce the tidal flat surface sedimentary facies classification map.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.551-560
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• 2014

Compare to other industrial sites, the civil construction work not only takes longer time but also has made of complicated processes, such as the integrated management, process control, and quality control until the completion. However, it is hard to take control the construction sites, since numerous issues are always emerged. The study purposes on providing the dataset to synthetically manage and monitor the civil construction site, main design, drawings, process, construction cost, and others at real-time by using the low altitude close-range aerial images, based on UAV, and the GPS surveying method for treating the three-dimensional spatial information quickly and accurately. As a result, we could provide the latest information for the quick decision-making following from planning to completion of the construction, and objective site evaluation by the high-resolution three-dimensional spatial information and drawings. Also, the present map, longitudinal map, and cross sectional view are developed to provide various datasets rapidly, such as earthwork volume table, specifications, and transition of ground level.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.947-958
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• 2021

This study was conducted to provide basic data for crop monitoring by comparing and analyzing changes in reflectance and vegetation index by sensor of multi-spectral sensors mounted on unmanned aerial vehicles. For four types of unmanned aerial vehicle-mounted multispectral sensors, such as RedEdge-MX, S110 NIR, Sequioa, and P4M, on September 14 and September 15, 2020, aerial images were taken, once in the morning and in the afternoon, a total of 4 times, and reflectance and vegetation index were calculated and compared. In the case of reflectance, the time-series coefficient of variation of all sensors showed an average value of about 10% or more, indicating that there is a limit to its use. The coefficient of variation of the vegetation index by sensor for the crop test group showed an average value of 1.2 to 3.6% in the crop experimental sites with high vitality due to thick vegetation, showing variability within 5%. However, this was a higher value than the coefficient of variation on a clear day, and it is estimated that the weather conditions such as clouds were different in the morning and afternoon during the experiment period. It is thought that it is necessary to establish and implement a UAV flight plan. As a result of comparing the NDVI between the multi-spectral sensors of the unmanned aerial vehicle, in this experiment, it is thought that the RedEdeg-MX sensor can be used together without special correction of the NDVI value even if several sensors of the same type are used in a stable light environment. RedEdge-MX, P4M, and Sequioa sensors showed a linear relationship with each other, but supplementary experiments are needed to evaluate joint utilization through off-set correction between vegetation indices.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.326-329
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• 2016

UAVs(Unmanned Aerial Vehicle) can be used in variant fields fornot only combat, but also recon, observation and exploration. Moreover, UAVs capacity can be expanded to impossible missions for existing surveillance system such as SAR(Synthetic Aperture Radar) technology that collecting images from all weather conditions. In recent days, with development of highly efficient IC and lightened system technology, there are significant increase of researches and demands to make SAR sensor as a payload of UAV. Therefore, this paper contains development process and results of small signal generator and RF device as a core module of SAR system based on the digital device of DDS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.693-698
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• 2018

This paper proposes a vehicle detection method for parking areas using unmanned aerial vehicles (UAVs) and using YOLOv2, which is a recent, known, fast, object-detection real-time algorithm. The YOLOv2 convolutional network algorithm can calculate the probability of each class in an entire image with a one-pass evaluation, and can also predict the location of bounding boxes. It has the advantage of very fast, easy, and optimized-at-detection performance, because the object detection process has a single network. The sliding windows methods and region-based convolutional neural network series detection algorithms use a lot of region proposals and take too much calculation time for each class. So these algorithms have a disadvantage in real-time applications. This research uses the YOLOv2 algorithm to overcome the disadvantage that previous algorithms have in real-time processing problems. Using Darknet, OpenCV, and the Compute Unified Device Architecture as open sources for object detection. a deep learning server is used for the learning and detecting process with each car. In the experiment results, the algorithm could detect cars in a dense area using UAVs, and reduced overhead for object detection. It could be applied in real time.