• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1731-1738
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• 2021

The objective of this study was to extract individual trees and tree heights using UAV drone images. The study site was Gongju national university experiment forest, located in Yesan-gun, Chungcheongnam-do. The thinning intensity study sites consisted of 40% thinning, 20% thinning, 10% thinning and control. The image was filmed by using the "Mavic Pro 2" model of DJI company, and the altitude of the photo shoot was set at 80% of the overlay between 180m pictures. In order to prevent image distortion, a ground reference point was installed and the end lap and side lap were set to 80%. Tree heights were extracted using Digital Surface Model (DSM) and Digital Terrain Model (DTM), and individual trees were split and extracted using object-based analysis. As a result of individual tree extraction, thinning 40% stands showed the highest extraction rate of 109.1%, while thinning 20% showed 87.1%, thinning 10% showed 63.5%, and control sites showed 56.0% of accuracy. As a result of tree height extraction, thinning 40% showed 1.43m error compared with field survey data, while thinning 20% showed 1.73 m, thinning 10% showed 1.88 m, and control sites showed the largest error of 2.22 m.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.602-607
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• 2018

The destruction of forests requires continuous management due to the risk of disasters such as landslides and landslides. However, existing forest inspection methods are inefficient as they require a lot of manpower and time. Recently, drones are attracting attention as an effective way to construct and utilize spatial information. The size of the drone-related industrial market is rapidly increasing. In this study, we attempted to increase the efficiency of forest investigation utilizing drones. The study area was photographed through the use of drones, and ortho image and DSM were generated through data processing. Study results found that it was possible to calculate the area and the volume for the forest damaged area effectively by employing drones, and suggested the applicability of drones. In the future, it is expected that the method of analyzing the forested area using drones can save manpower and time compared to existing methods.

• 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 Cadastre & Land InformatiX
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• v.47 no.1
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• pp.213-223
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• 2017

Recently, the air quality of South Korea has deteriorated and public interest has been increasing. Various observation means are used for the monitoring of the atmospheric environment, but it relies on the experience and judgment of the observer in the absence of spatial information on the emission facilities. The purpose of this study was to determine the availability of using drones for monitoring air pollutant emission facilities. A texture transformation method was applied to the drone ortho image to detect the small gas emission facility and the slope data calculated by the digital surface model (DSM) was used to reduce the false alarm ratio. As a result, it shows the possibility of using drones in the detection of small gas emission facilities by showing about 80% of positive detection ratio and 40% of false alarm ratio. In the future, various researches are required to the improve positive detection ratio and the reduction of the false alarm ratio. Based on these results, it is necessary to construct a database including 3D spatial information of air pollutant emission facilities.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.47-54
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• 2021

Calculation of quantity at construction sites is a factor that has a great influence on construction costs, and it is important to calculate accurate values. In this study, topographic model was created by using drone photogrammetry and drone LiDAR to estimate earthwork volume. ortho image and DSM (Digital Surface Model) were constructed for the study area by drone photogrammetry, and DEM (Digital Elevation Model) of the target area was established using drone LiDAR. And through accuracy evaluation, accuracy of each method are 0.034m, 0.35m in horizontal direction, 0.054m, 0.25m in vertical direction. Through the research, the usability of drone photogrammetry and drone LiDAR for constructing geospatial information was presented. As a result of calculating the volume of the study site, the UAV photogrammetry showed a difference of 1528.1㎥ from the GNSS (Global Navigation Satellite System) survey performance, and the 3D Laser Scanner showed difference of 160.28㎥. The difference in the volume of earthwork is due to the difference in the topographic model, and the efficiency of volume calculation by drone LiDAR could be suggested. In the future, if additional research is conducted using GNSS surveying and drone LiDAR to establish topographic model in the forest area and evaluate its usability, the efficiency of terrain model construction using drone LiDAR can be suggested.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.325-331
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• 2017

In this study, digital elevation models(DEM) of tidal flat, according to different times, was produced by means of the Drone and commercial software in order to measure seawater change during high tide at water-channel in the Hampyung Bay. To correct the produced DEMs of the tidal flat where is inaccessible to collect control points, the DEM matching method was applied by using the reference DEM, that is previously obtained, instead of the survey. After the ortho-image was made from the corrected DEM, the land cover classified image was produced. The changes of seawater amount according to the times were analyzed by using the classified images and DEMs. As a result, it was confirmed that the amount of water rapidly increased as the time passed during high tide.

• Tunnel and Underground Space
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• v.25 no.5
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• pp.462-469
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• 2015

This study carried out a topographic survey at a small-scale open-pit limestone mine in Korea (the Daesung MDI Seoggyo office) using a popular rotary-wing unmanned aerial vehicle (UAV, Drone, DJI Phantom2 Vision+). 89 sheets of aerial photos could be obtained as a result of performing an automatic flight for 30 minutes under conditions of 100m altitude and 3m/s speed. A total of 34 million cloud points with X, Y, Z-coordinates was extracted from the aerial photos after data processing for correction and matching, then an orthomosaic image and digital surface model with 5m grid spacing could be generated. A comparison of the X, Y, Z-coordinates of 5 ground control points measured by differential global positioning system and those determined by UAV photogrammetry revealed that the root mean squared errors of X, Y, Z-coordinates were around 10cm. Therefore, it is expected that the popular rotary-wing UAV photogrammetry can be effectively utilized in small-scale open-pit mines as a technology that is able to replace or supplement existing topographic surveying equipments.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.21-35
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• 2020

Vegetation information is a very important factor used in various fields such as urban planning, landscaping, water resources, and the environment. Vegetation varies according to canopy density or chlorophyll content, but vegetation vitality is not considered when classifying vegetation areas in previous studies. In this study, in order to satisfy various applied studies, a study was conducted to set a threshold value of vegetation index considering vegetation vitality. First, an eBee fixed-wing drone was equipped with a multi-spectral camera to construct optical and near-infrared orthomosaic images. Then, GIS calculation was performed for each orthomosaic image to calculate the NDVI, GNDVI, SAVI, and MSAVI vegetation index. In addition, the vegetation position of the target site was investigated through VRS survey, and the accuracy of each vegetation index was evaluated using vegetation vitality. As a result, the scenario in which the vegetation vitality point was selected as the vegetation area was higher in the classification accuracy of the vegetation index than the scenario in which the vegetation vitality point was slightly insufficient. In addition, the Kappa coefficient for each vegetation index calculated by overlapping with each site survey point was used to select the best threshold value of vegetation index for classifying vegetation by scenario. Therefore, the evaluation of vegetation index accuracy considering the vegetation vitality suggested in this study is expected to provide useful information for decision-making support in various business fields such as city planning in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.117-127
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• 2018

The author tried to propose the orthographic and DTM (digital terrain model) creation and evaluate the accuracy for an university campus using UAV (unmanned aerial vehicle) system. Most previous studies used GPS-based data, but in this paper, the observations of triangulation level measurements was used for comparison of accuracy. Accuracy analysis results showed that the operational requirements for aerial photographic standards are satisfied in all scenaries. The author confirmed availability in aviation photo measurements and applications using UAV (Drone). In order to create a sophisticated DTM and contour, we need to eliminate interference from building, trees, and artificial objects. The results of this study are expected to be used as the basis for future studies in the creation of DTM and the accuracy assessments using Drone.

• 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.