• Journal of Korean Society for Geospatial Information Science
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• v.14 no.1 s.35
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• pp.37-47
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• 2006

In the last years a low-altitude image acquisition technology has been developed in application of frequent change monitoring in urban area md speedy surveillance in disaster area. A low-altitude photogrammetric system have advantages of accurate observation and free data-acquisition time. Especially, an unmaned RC-helicopter, improving safety, durability and portability, comes into the spotlight as a built-in vehicle in close range photogrammetric application due to their capability of safe near-by observation and effective flight performance. This paper gives a methodology for generating image map by development of low cost and timesaving low-altitude photogrammetric UAV(unmaned aerial vehicles) for collecting high-resolution image data, and implement of geo-rectification and image mosaicking.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.1
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• pp.11-19
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• 2019

Recently, with the development of the fourth industrial revolution that has been achieved through the fusion of information and communication technology (ICT), the technologies of AI, IOT, BIG-DATA, it is increasing utilization rate by industry and research and development of application technologies are being actively carried out. Especially, in the case of unmanned aerial vehicles, the construction market is expected to be one of the most commercialized areas in the world for the next decade. However, research on utilization of unmanned aerial vehicles in the construction field in Korea is insufficient. In this study, We have developed a quantitative building inspection method using the unmanned aerial vehicle and presented the protocol for it. The proposed protocol was verified by applying it to existing old buildings, and defect information could be quantified by calculating length, width, and area for each defect. Through this technical research, the final goal is to contribute to the development of safety diagnosis technology using unmanned aerial vehicle and risk assessment technology of buildings in case of disaster such as earthquake.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.234-252
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• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.19-25
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• 2005

Nowadays, it is possible to construct the DEMs of urban area effectively and economically by LiDAR system. But the data from LiDAR system has form of DSM which is included various objects as trees and buildings. So the preprocess is necessary to extract the DEMs from LiDAR DSMs for particular purpose as effects analysis of man-made objects for flood prediction. As this study is for extracting DEM from LiDAR DSM of urban area, we detected the edges of various objects using edge detecting algorithm of image process. And, we tried mean value filtering, median value filtering and minimum value filtering or detected edges instead of interpolation method which is used in the previous study and could be modified the source data. it could minimize the modification of source data, and the extracting process of DEMs from DSMs could be simplified and automated.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.1
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• pp.1-6
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• 2010

The lens distortion in the machine vision system is inevitable phenomenon. Distortion is getting worse, due to the selection of lens in the trend of reducing prices and size of the system. In this trend, the distortion correction becomes more important. But, the traditional correction methods has problems, such as complexity and requiring more operations. Effective distorted digital image correction is the precondition of target detection and recognition based on vision inspection. To overcome the disadvantage of traditional distortion correction algorithms, such as complex modeling, massive computation and marginal information loss, an image distortion correction algorithm based on photogrammetry method is proposed in this paper. In our method, we use the lattice image as the measurement target. Through the experimental results, we could find that we can reduce the processing time by 4ms. And also the inspection failure rate of our method was reduced by 2.3% than human-eyes inspection method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.289-297
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• 2009

In the paper, we propose the methodology to extract training dataset automatically for supervised classification of road networks. For the preprocessing, we co-register the airborne photos, LIDAR data and large-scale digital maps and then, create orthophotos and intensity images. By overlaying the large-scale digital maps onto generated images, we can extract the initial training dataset for the supervised classification of road networks. However, the initial training information is distorted because there are errors propagated from registration process and, also, there are generally various objects in the road networks such as asphalt, road marks, vegetation, cars and so on. As such, to generate the training information only for the road surface, we apply the Expectation Maximization technique and finally, extract the training dataset of the road surface. For the accuracy test, we compare the training dataset with manually extracted ones. Through the statistical tests, we can identify that the developed method is valid.

• Korean Journal of Construction Engineering and Management
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• v.10 no.6
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• pp.3-12
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• 2009

In order to effectively distribute the resources, it is very critical to understand the status or progress of construction site quickly and accurately. Augmented Reality (AR) can provide this situation with information which is convenient and intuitive. Conventional implementation of AR in outdoor or construction site condition requires additional sensors or markers to track the position and direction of camera. This research is aimed to develop the technologies which can be utilized in gathering the information of constructing or constructed buildings and structures. The AR technique that does not require additional devices except for the camera was implemented to simplify the system and improve utility in inaccessible area. In order to do so, the position of camera's perspective center and direction of camera was estimated using exterior orientation techniques. And 3D drawing model of building was projected and overlapped using this information. The result shows that by using this technique, the virtual drawing image was registered on real image with few pixels of error. The technique and procedure introduced in this paper simplifies the hardware organization of AR system that makes it easier for the AR technology to be utilized with ease in construction site. Moreover, this technique will help the AR to be utilized even in inaccessible areas. In addition to this, it is expected that combining this technique and 4D CAD technology can provide the project manager with more intuitive and comprehensive information that simplifies the monitoring work of construction progress and planning.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.403-412
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• 2022

As the 4th industrial revolution is in full swing and next-generation ICT(Information & Communications Technology) convergence technology is being developed, various smart construction technologies are being rapidly introduced in the construction field to respond to technological changes. In particular, since the earth-volume calculation process for site design accounts for a large part of the design cost at the construction site, related researches are being actively conducted to improve the efficiency of the process and accurately calculate the earth-volume. The purpose of this study is to present a method for quickly constructing the topography of a construction site in 3D and efficiently calculating earth-volume using the results. For this purpose, the construction site was constructed as a 3D realistic model using large-scale aerial photos obtained from UAV(Unmanned Aerial Vehicle). At this time, since the constructed 3D realistic model has a surface model structure in which volume calculation is impossible, the structure was converted into a 3D solid model to enable volume calculation. And we devised a methodology to calculate earth-volume based on CAD(Computer-Aided Design and Drafting) using the converted solid model. Automatically calculating earth-volume from the solid model by applying the method. As a result, It was possible to confirm a relative deviation of 1.52% from the calculated earth-volume from the existing survey results. In addition, as a result of comparative analysis of the process time required for each method, it was confirmed that the time required is reduced of 60%. The technique presented in this study is expected to be utilized as a technology for smart construction management, such as periodic site monitoring throughout the entire construction process, as well as cost reduction for earth-volume calculation.

• Spatial Information Research
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• v.16 no.3
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• pp.373-383
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• 2008

LiDAR, unlike satellite imagery and aerial photographs, which provides irregularly distributed three-dimensional coordinates of ground surface, enables three-dimensional modeling. In this study, urban area was classified based on 3D information collected by LiDAR. Morphological and spatial properties are determined by the ratio of ground and non-ground point that are estimated with the number of ground reflected point data of LiDAR raw data. With this information, the residential and forest area could be classified in terms of height and density of trees. The intensity of the signal is distinguished by a statistical method, Jenk's Natural Break. Vegetative area (high or low density) and non-vegetative area (high or low density) are classified with reflective ratio of ground surface.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.53-59
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• 2009

The general urban plan is the plane plan which limits general and uniformed constructions; however, the district unit plan is the solid plan that can leads various constructions by discriminating by plot, housing area and lot. Therefore, for the zone plan, not only the two-dimensional plot information such as plot usage plan, but also the three-dimensional plot information needs to be used to analyze lighting, sewerage and directions. To fulfill such requirements, the information can be gathered using GIS and photogrammetric method for the reasonable and efficient zone plan. In this research, the information about the testing area for the zone plan has been gathered using GIS method, and the three-dimensional model about the area has been built using the satellite image and DEM. As the result, plot usage analysis, direction analyst, water system analysis, and slope analysis has been done and used efficiently to build the district unit plan. Also, after the result after applying the analyzed result to the actual area says this is very appropriate and efficient.