• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.13-21
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• 2011

Update of road facilities database such as road sign, traffic lights, and street lights is interesting business in a local government. Recently, existing road facilities database, aerial photo and topographic map are referred for the installation and complement of road facilities. But it is difficult to comprehend road facilities' condition and additional expenses may appear in field survey. Therefore, it is necessary to establish and update road facility DB and many studies has been carried out to efficiently collect road related spatial data. In this study, the establishment of various complicated road facility DB was conducted by images that had been obtained by digital camera with a built-in bluetooth and DGPS. Results showed that road facility DB was constructed effectively and suggested the possibility of road facility management using images based on coordinate through accuracy analyses using total-station surveying. And using digital camera and DGPS is expected to effective real-time update and management of road facility DB.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.117-126
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• 2018

Due to intelligent transport systems, location-based applications, and augmented reality, demand for image maps and 3D (Three-Dimensional) maps is increasing. As a result, data acquisition using UAV (Unmanned Aerial Vehicles) has flourished in recent years. However, even though orthophoto map production and research using UAVs are flourishing, few studies on 3D modeling have been conducted. In this study, orthophoto and 3D modeling research was performed using various angle images acquired by a UAV. For orthophotos, accuracy was evaluated using a GPS (Global Positioning System) survey that employed VRS (Virtual Reference Station) acquired checkpoints. 3D modeling was evaluated by calculating the RMSE (Root Mean Square Error) of the difference between the outline height values of buildings obtained from the GPS survey to the corresponding 3D modeling height values. The orthophotos satisfied the acceptable accuracy of NGII (National Geographic Information Institute) for a 1/500 scale map from all angles. In the case of 3D modeling, models based on images taken at 45 degrees revealed better accuracy of building outlines than models based on images taken at 30, 60, or 75 degrees. To summarize, it was shown that for orthophotos, the accuracy for 1/500 maps was satisfied at all angles; for 3D modeling, images taken at 45 degrees produced the most accurate models.

• Journal of Cadastre & Land InformatiX
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• v.46 no.1
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• pp.87-100
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• 2016

The acquisition of the forest resource information has depended on a partial sampling method or aerial photographs which demand a lot of effort and time because of the vast areas and the difficult approach. For the acquisition of the forest resource information, there have been the optical remote-sensing and the multi-spectrum image to offer only horizontal distributions of trees, but a new technological approach, such as Airborne LiDAR, is more necessary to acquire directly three dimensional information related to the forest terrains and trees' features. This paper proposes an algorithm for the forest information extraction such as trees' individual numbers and the heights of trees by using LiDAR data. Especially, this proposed algorithm adopts a region growing method for the extraction of the vegetation-point and extracts the forest information using morphological features of trees.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.45-45
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• 2017

On-site monitoring of vegetable growth parameters, such as leaf length, leaf area, and fresh weight, in an agricultural field can provide useful information for farmers to establish farm management strategies suitable for optimum production of vegetables. Unmanned Aerial Vehicles (UAVs) are currently gaining a growing interest for agricultural applications. This study reports on validation testing of previously developed vegetable growth estimation models based on UAV-based RGB images for white radish and Chinese cabbage. Specific objective was to investigate the potential of the UAV-based RGB camera system for effectively quantifying temporal and spatial variability in the growth status of white radish and Chinese cabbage in a field. RGB images were acquired based on an automated flight mission with a multi-rotor UAV equipped with a low-cost RGB camera while automatically tracking on a predefined path. The acquired images were initially geo-located based on the log data of flight information saved into the UAV, and then mosaicked using a commerical image processing software. Otsu threshold-based crop coverage and DSM-based crop height were used as two predictor variables of the previously developed multiple linear regression models to estimate growth parameters of vegetables. The predictive capabilities of the UAV sensing system for estimating the growth parameters of the two vegetables were evaluated quantitatively by comparing to ground truth data. There were highly linear relationships between the actual and estimated leaf lengths, widths, and fresh weights, showing coefficients of determination up to 0.7. However, there were differences in slope between the ground truth and estimated values lower than 0.5, thereby requiring the use of a site-specific normalization method.

• Journal of the Korean Geographical Society
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• v.37 no.5
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• pp.511-521
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• 2002

Coastal sand dunes in West coast of Korea are under stress. Due to the newly constructed Seohaean(West Coast) Highways, the number of visitors and the anthropogenic pressures will keep rising in near future. Sea level rise due to the global warming may cause a lot of damage to the natural resources and residents of coastal area. Therefore, many countries including United States are doing nationwide coastline survey using highly sophisticated methodology. In this study, high resolution IKONOS satellite images along with aerial photographs taken since 1960's have been sequentially analyzed using GIS software (Erdas Imagine 8.3). Onsite monitoring has been performed at the 31 measuring points in 10 beaches since the May of 2001 in order to measure the sand budget. Post-construction monitoring after installation of sand fences is also being done on sites regularly. Restoration works seem to be effective at this moment.

• Journal of the Korean earth science society
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• v.39 no.1
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• pp.46-52
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• 2018

This paper is to study the development of three dimensional Digital Surface Model (DSM) using photogrammetry technique based on self-developed Drone (Unmanned Aerial Vehicle (UAV)). To develop DSM, we selected a study area in Jeju island and took 24 pictures from the drone. The three dimensional coordinates of the photos were made by Differential Global Positioning System (DGPS) surveying with 10 ground control points (GCP). From the calculated three dimensional coordinates, we produced orthographic image and DSM. The accuracy of DSM was calculated using three GCPs. The average accuracy of X and Y was from 8.8 to 14.7 cm, and the accuracy of Z was 0.8 to 12.4 cm. The accuracy was less than the reference accuracy of 1/1,000 digital map provided by National Geographic Information Institute (NGII). From the results, we found that the self-developed drone and the photogrammetry technique are a useful tool to make DSM and digital map of Jeju.

• 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.

• The Journal of Engineering Geology
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• v.26 no.1
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• pp.23-32
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• 2016

This study evaluates landslide susceptibility using statistical analysis by SVM (support vector machine) and the illite index of clay minerals extracted from ASTER(advanced spaceborne thermal emission and reflection radiometer) imagery which can be use to create mineralogical mapping. Landslide locations in the study area were identified from aerial photographs and field surveys. A GIS spatial database was compiled containing topographic maps (slope, aspect, curvature, distance to stream, and distance to road), maps of soil properties (thickness, material, topography, and drainage), maps of timber properties (diameter, age, and density), and an ASTER satellite imagery (illite index). The landslide susceptibility map was constructed through factor correlation using SVM to analyze the spatial database. Comparison of area under the curve values showed that using the illite index model provided landslide susceptibility maps that were 76.46% accurate, which compared favorably with 74.09% accuracy achieved without them.

• 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.

• Spatial Information Research
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• v.18 no.3
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• pp.23-32
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• 2010

LIDAR data are useful for forest applications such as bare-earth DEM generation for forest areas, and estimation of tree height and forest biomass. As a core preprocessing procedure for most forest applications, this study attempts to develop an efficient method to detect forest areas from LIDAR data. First, we suggest three perceptual cues based on multiple return characteristics, height deviation and spatial distribution, being expected as reliable perceptual cues for forest area detection from LIDAR data. We then classify the potential forest areas based on the individual cue and refine them with a bi-morphological process to eliminate falsely detected areas and smoothing the boundaries. The final refined forest areas have been compared with the reference data manually generated with an aerial image. All the methods based on three types of cues show the accuracy of more than 90%. Particularly, the method based on multiple returns is slightly better than other two cues in terms of the simplicity and accuracy. Also, it is shown that the combination of the individual results from each cue can enhance the classification accuracy.