• 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 the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1325-1332
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• 2023

Recently, much research is being conducted based on point cloud data for the growth of innovations such as construction automation in the transportation field and virtual national space. This data is often measured through remote control in terrain that is difficult for humans to access using devices such as UAVs and UGVs. Drones, one of the UAVs, are mainly used to acquire point cloud data, but photogrammetry using a vision camera, which takes a lot of time to create a point cloud map, is difficult to apply in construction sites where the terrain changes periodically and surveying is difficult. In this paper, we developed a point cloud mapping system by adopting non-repetitive scanning LiDAR and attempted to confirm improvements through field application. For accuracy analysis, a point cloud map was created through a 2 minute 40 second flight and about 30 seconds of software post-processing on a terrain measuring 144.5 × 138.8 m. As a result of comparing the actual measured distance for structures with an average of 4 m, an average error of 4.3 cm was recorded, confirming that the performance was within the error range applicable to the field.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.589-599
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• 2018

The land cover map has been produced by using satellite and aerial images. However, these two images have the limitations in spatial resolution, and it is difficult to acquire images of a area at desired time because of the influence of clouds. In addition, it is costly and time-consuming that mapping land cover map of a small area used by satellite and aerial images. This study used multispectral camera-based drone to acquire multi-temporal images for orthoimages generation. The efficiency of produced land cover map was evaluated using time series analysis. The results indicated that the proposed method can generated RGB orthoimage and multispectral orthoimage with RMSE (Root Mean Square Error) of ${\pm}10mm$, ${\pm}11mm$, ${\pm}26mm$ and ${\pm}28mm$, ${\pm}27mm$, ${\pm}47mm$ on X, Y, H respectively. The accuracy of the pixel-based and object-based land cover map was analyzed and the results showed that the accuracy and Kappa coefficient of object-based classification were higher than that of pixel-based classification, which were 93.75%, 92.42% on July, 92.50%, 91.20% on October, 92.92%, 91.77% on February, respectively. Moreover, the proposed method can accurately capture the quantitative area change of the object. In summary, the suggest study demonstrated the possibility and efficiency of using multispectral camera-based drone in production of land cover map.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.136-150
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• 2022

In this study, a comparative review was conducted on how to use RGB images to obtain river topographic information, which is one of the most essential data for eco-friendly river management and flood level analysis. In terms of the topographic information of river zone, to obtain the topographic information of flow section is one of the difficult topic, therefore, this study focused on estimating the river topographic information of flow section through RGB images. For this study, the river topography surveying was directly conducted using ADCP and RTK-GPS, and at the same time, and orthomosiac image were created using high-resolution images obtained by drone photography. And then, the existing developed regression equations were applied to the result of channel topography surveying by ADCP and the band values of the RGB images, and the channel bathymetry in the study area was estimated using the regression equation that showed the best predictability. In addition, CCHE2D flow modeling was simulated to perform comparative verification of the topographical informations. The modeling result with the image-based topographical information provided better water depth and current velocity simulation results, when it compared to the directly measured topographical information for which measurement of the sub-section was not performed. It is concluded that river topographic information could be obtained from RGB images, and if additional research was conducted, it could be used as a method of obtaining efficient river topographic information for river management.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.97-104
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• 2016

In this study, analyze and monitor the change of the ecological restoration area inside the open-pit mine in Gangwon-do. and to analyze and monitor the change of ecological restoration area. analyzed the distribution of vegetation using high-resolution orthophoto of various periods and analyzed terrain change using DSM/DEM in study area. Therefore, orthophoto and 포인트 클라우드 were collected from 2014 aerial laser surveying and 2015 fixed-wing drone photogrammetry. In addition, orhtophoto and 포인트 클라우드 were produced by using rotary-wing drone photogrammety in 2016, and change of ecological restoration area was analyzed using this. As a result, it's possible to perform change monitoring of the open-pit mine ecological restoration area. using nEGI and VARI, about 10-30% of the area ratio of the result of extracting vegetation distribution area is distributed, and the comparison DSM and DEM cross section and restoration plan line, the cross section made by using the drone were similar, and the earth-volume analysis was possible.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.203-209
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• 2021

With the recent development of satellite sensor technology, high-spatial-resolution imagery of various spectral wavelength bands have become possible. Worldview-3 satellite sensor provides panchromatic images with high-spatial-resolution and VNIR (Visible Near InfraRed) and SWIR (ShortWave InfraRed) bands with low-spatial-resolution, so it can be used in various fields such as defense, environment, and surveying. In this study, mineral detection was performed using Worldview-3 satellite imagery. In order to effectively utilize the VNIR and SWIR bands of the Worldview-3 satellite image, the sharpening technique was applied to the spatial resolution of the panchromatic image. To confirm the utility of SWIR bands for mineral detection, mineral detection using only VNIR bands was performed and comparatively evaluated. As the mineral detection technique, SAM (Spectral Angle Mapper), a representative similarity technique, was applied, and the pixels detected as minerals were selected by applying an empirical threshold to the analysis result. Quantitative evaluation was performed using reference data on the results of similarity analysis to evaluate the accuracy of mineral detection. As a result of the accuracy evaluation, the detection rate and false detection rate of mineral detecting using SWIR bands were calculated to be 0.882 and 0.011, respectively, and the results using only VNIR bands were 0.891 and 0.037, respectively. It was found that the detection rate when the SWIR bands were additionally used was lower than that when only the VNIR bands were used. However, it was found that the false detection rate was significantly reduced, and through this, it was possible to confirm the applicability of SWIR bands in mineral detection.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.5
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• pp.435-441
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• 2020

Sentinel-2A satellite imagery provides VNIR (Visible Near InfraRed) and SWIR (ShortWave InfraRed) wavelength bands, and it is known to be effective for land cover classification, cloud detection, and environmental monitoring. Greenhouse is one of the middle classification classes for land cover map provided by the Ministry of Environment of the Republic of Korea. Since greenhouse is a class that has a lot of changes due to natural disasters such as storm and flood damage, there is a limit to updating the greenhouse at a rapid cycle in the land cover map. In the present study, we utilized Sentinel-2A satellite images that provide both VNIR and SWIR bands for the detection of greenhouse. To utilize Sentinel-2A satellite images for the detection of greenhouse, we produced high-resolution SWIR bands applying to the fusion technique performed in two stages and carried out the detection of greenhouse using SVM (Support Vector Machine) supervised classification technique. In order to analyze the applicability of SWIR bands to greenhouse detection, comparative evaluation was performed using the detection results applying only VNIR bands. As a results of quantitative and qualitative evaluation, the result of detection by additionally applying SWIR bands was found to be superior to the result of applying only VNIR bands.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.163-180
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• 2020

In this study, to build a spatial information infrastructure, which is a component of a smart city, a 3D digital twin model in the downtown area was built based on the latest spatial information acquisition technology, the drone. Several analysis models were implemented by utilizing. While the data processing time and quality of the three types of drone photogrammetry software are different, the accuracy of the construction model is ± 0.04 in the N direction and ± 0.03m in the E direction. In the m and Z directions, ± 0.02m was found to be less than 0.1m, which is defined as the allowable range of surveying performance and inspection performance for the boundary point in the area where the registration of the boundary point registration is executed. 1: 500 to 1 of the aerial survey work regulation: The standard deviation, which is the error limit of the photographic reference point of the 600 scale, appeared within 0.14 cm, and it was found that the error limit of the large scale specified in the cadastral and aerial survey was satisfied. In addition, in order to increase the usability of smart city realization using a drone-based 3D urban digital twin model, the model built in this study was used to implement Prospect right analysis, landscape analysis, Right of light analysis, patrol route analysis, and fire suppression simulation training. Compared to the existing aerial photographic survey method, it was judged that the accuracy of the naked eye reading point is more accurate (about 10cm) than the existing aerial photographic survey, and it is possible to reduce the construction cost compared to the existing aerial photographic survey at a construction area of about 30㎢ or less.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.107-112
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• 2020

Recently, as the field of use of drones is diversified, it is actively used not only for surveying but also for search and rescue work. In these applications it is very important to know the location of the target or the location of the UAV. This paper proposes a target detection method using images taken from drones. The proposed method calculates the latitude and longitude information of the target by finding the location of the target by comparing it with the image to find the image taken by the drone. The exact latitude and longitude information of the target is calculated by calculating the actual distance corresponding to the distance of the image image using the characteristics of the pinhole camera. The proposed method through the actual experiment confirmed that the latitude and longitude of the target was accurately identified.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.541-548
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• 2021

Recently, multispectral cameras are being actively utilized in various application fields such as agriculture, forest management, coastal environment monitoring, and so on, particularly onboard UAV's. Resultant multispectral images are typically georeferenced primarily based on the onboard GPS (Global Positioning System) and IMU (Inertial Measurement Unit)or accurate positional information of the pixels, or could be integrated with ground control points that are directly measured on the ground. However, due to the high cost of establishing GCP's prior to the georeferencing or for inaccessible areas, it is often required to derive the positions without such reference information. This study aims to provide a means to improve the georeferencing performance of a multispectral camera images without involving such ground reference points, but instead with the simultaneously onboard high resolution RGB camera. The exterior orientation parameters of the drone camera are first estimated through the bundle adjustment, and compared with the reference values derived with the GCP's. The results showed that the incorporation of the images from a high resolution RGB camera greatly improved both the exterior orientation estimation and the georeferencing of the multispectral camera. Additionally, an evaluation performed on the direction estimation from a ground point to the sensor showed that inclusion of RGB images can reduce the angle errors more by one order.