• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.3-12
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• 2010

In previous studies, the digital measurement systems and analysis algorithms were developed by using the related techniques, such as the aerial photograph detection and high resolution satellite image process. However, these studies were limited in 2-dimensional geo-processing. Therefore, it is necessary to apply the 3-dimensional spatial information and coordinate system for higher accuracy in recognizing and locating of geo-features. The objective of this study was to develop a stochastic algorithm for the optimal sensor placement using the 3-dimensional spatial analysis method. The 3-dimensional information of the LiDAR was applied in the sensor field algorithm based on 2- and/or 3-dimensional gridded points. This study was conducted with three case studies using the optimal sensor placement algorithms; the first case was based on 2-dimensional space without obstacles(2D-non obstacles), the second case was based on 2-dimensional space with obstacles(2D-obstacles), and lastly, the third case was based on 3-dimensional space with obstacles(3D-obstacles). Finally, this study suggested the methodology for the optimal sensor placement - especially, for ground-settled sensors - using the LiDAR data, and it showed the possibility of algorithm application in the information collection using sensors.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.137-143
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• 2014

Recently, as new paradigm for government operation called government 3.0, government is actively operating policy opening and sharing public data. In addition, the Ministry of Land are operating an open platform integrated map service (the VWorld) which provides a variety of video contents such as the country's national spatial information, traffic information and three-dimensional building for the public. According to W3C Foundation's Open Data Status Report(2013), our country has the evaluated results that the part of the government's policy support and planning is good while the part of the data management is vulnerable. So our country needs the quality improvement for the data management. In addition, a digital aerial photograph image data is required to be up-to-date for the three-dimensional spatial object data. In this paper, we present the method for enhancement of the accuracy of vertical position and for maintainment of up-to-date vertical position. Our methods evaluate the data quality and analyze the cause of error of measurement utilizing the national standard quality assessment method. The result of research shows that the accuracy of vertical position is improved if the height of the building captain is adjusted by the quality assessment values and a three-dimensional model has up-to-date data if reconstruction and extension information of construction register is utilized.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.87-98
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• 2012

A river boundary is defined as the intersection between a main stream of a river and the land. Mapping of the river boundary is important for the protection of the properties in river areas, the prevention of flooding and the monitoring of the topographic changes in river areas. However, the utilization of the ground surveying technologies is not efficient for the mapping of the river boundary due to the irregular surfaces of river zones and the dynamic changes of water level of a river stream. Recently, the spatial information data sets such as the airborne LiDAR and aerial images are widely used for coastal mapping due to the acquisition of the topographic information without human accessibility. Due to these advantages, this research proposes a semi-automatic method for mapping of the river boundary using the spatial information data set such as the airborne LiDAR and the aerial photographs. Multiple image processing technologies such as the image segmentation algorithm and the edge detection algorithm are applied for the generation of the 3D river boundary using the aerial photographs and airborne topographic LiDAR data. Check points determined by the experienced expert are used for the measurement of the horizontal and vertical accuracy of the generated 3D river boundary. Statistical results show that the generated river boundary has a high accuracy in horizontal and vertical direction.

• Korean Journal of Heritage: History & Science
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• v.53 no.2
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• pp.36-63
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• 2020

Percival Lowell took photographs of 80s during his stay in Korea in the winter of 1883 and 1884. The photographs are the first in the history of Korea and contain various and precious information about Korea of the day. As such, they could be used for purposes of studying late 19th century Chosōn society. The 61 photographs that are archived in Boston Museum of Fine Art were catalogued by National Research Institute of Cultural Heritage and have been posted online with incorrect explanations by Boston Museum of Fine Art. The explanations have been composed and revised at least four times on the basis of Lowell's writings and archivists' understandings of Korea. However these explanations contain many errors regarding the content of the photographs, yet have been cited by researchers and books concerning the history of Korea. I examined the explanations, analyzed Lowell's writings and diplomatic documents, and confirmed the locations where the photographs were taken. Accordingly, I suggest improved explanations of the photographs to prevent misuse of the Boston Museum of Fine Art's online archive. Lowell's photographs of Chosōn have very high historical value and could be used in various cultural fields because of their various contents and high definition. However, they belong to America and are not cared for sufficiently. Therefore, I suggest that high definition digital scans and prints of the photographs be generated for the sake of overseas Korean cultural heritage collection.

• Journal of the Korean Society of Propulsion Engineers
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• v.4 no.4
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• pp.18-25
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• 2000

A two-color particle image velocimetry (PIV) has been developed for measuring two dimensional velocity flowfields and applied to a Mach 2.0 supersonic nozzle. This technique is similar to a single-color PIV technique except that two different color laser beams are used to solve the directional ambiguity problem. A green-color laser sheet (532 nm: 2nd harmonic beam of YAG laser) and a red-color laser sheet (619 nm: output beam from YAG pumped Dye laser using Rhodamine 640) are employed to illuminate the seeded particles. A high resolution (3060${\times}$2036) digital color CCD camera is used to record the particle positions. This system eliminates the photographic-film processing time and subsequent digitization time as well as the complexities associated with conventional image shifting techniques for solving directional ambiguity problem. The two-color PIV also has the advantage that velocity distributions in high speed flowfields can be measured simply and accurately by varying the time interval between two different laser beams due to its high signal-to-noise ratio and thereby less requirement of panicle pair numbers for a velocity vector in one interrogation spot. The velocity distribution in the Mach 2.0 supersonic nozzle has been measured and the over-expanded shock cell structure can be predicted by the strain rate field. These results are compared and analyzed with the schlieren photograph for the velocity distributions and shock location.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.187-193
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• 2022

In the Yeongdong region of Gangwon-do, coastal areas are important resources in terms of cultural, social and economic aspects. However, the coast of Gangwon-do is experiencing severe erosion, and it is concerned that its adverse effects will gradually increase. In this study, coastline changes of Yangyang and Gangneung in Gangwon-do were tracked and analyzed over a long period of time. In order to build time series image data, aerial photos from the 1940s to the present were mainly used, and data from CORONA satellite, which operated from the 1960s to the early 1970s, were collected and used together. Using 51cm resolution ortho image and 2m resolution Digital Elevation Model(DEM) as reference, ground control points were selected to perform geometric correction on the aerial photos and CORONA images. Subsequently, Canny edge detector applied to these images to extract the coastlines. As a result of analyzing the extracted and vectorized coastlines by overlaying them in chronological order, erosion and deposition occurring around the artificial structures and on the nearby beaches were observed. In this study, the effect of seasonal variation, tide, and various coastal management including the beach filling were not considered. Because coastal erosion is greatly affected by geographic factors, each local government must find its own solution. Continuous research and local data accumulation are required.

• Trans-
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• v.12
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• pp.81-106
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• 2022

The possibility of metaverse system to be a catalyst for hyper-connected society will be dependent on the speed of connected technological development and its social utilization in the same manner as AI technology. Putting these technical realization processes in brackets, this paper focus on some philosophical-political issues in connection with cognitive-ecological changes in the future cinema which will be influenced by the complexive techno-socio couples of accelerated development of metaverse system. Generally speaking, essence of metaverse system seems to be the degree of immersion by technical accuracy, but is not true. In perspective of cognitive-ecology, flow degree of a picture or photograph is relied not on 'accuracy of representation' but on its message's contextual link-up. In this aspect, real potentiality of metaverse system shall be understood in the context of cognitive-ecological changes of human brain's multi-intelligence networking abilities(intersection of augmentation-simulation and outside-inside) which will be activated in the new structure of natural-social-technological coupling of metaverse system. These cognitive-ecological potentialities have been partially actualized in the cinematic process of tripod mimesis for the longest time, [real contradiction/conflicts (Mimesis-1) -->fictional solutions of cinema (Mimesis-2) --> selective interpretation of spectator's wish fulfillment (Mimesis-3) --> real change (Mimesis-1')]. Therefore metaverse's real potentiality must be considered to be dependent on the possibility of deepening and extending of cinematic circulation between real seperation/problems and ideal connection/solutions. In this context, advanced metaverse system can be compared as a modern technical version of ideal circulation of physics and metaphysics

• Journal of Korean Society of Rural Planning
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• v.27 no.4
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• pp.55-70
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• 2021

In this study, in the field of remote sensing, where the scope of application is rapidly expanding to fields such as land monitoring, disaster prediction, facility safety inspection, and maintenance of cultural properties, monitoring of rural space and surrounding environment using UAV is utilized. It was carried out to verify the possibility, and the following main results were derived. First, the aerial image taken with an unmanned aerial vehicle had a much higher image size and spatial resolution than the aerial image provided by the National Geographic Information Service. It was suitable for analysis due to its high accuracy. Second, the more the number of photographed photos and the more complex the terrain features, the more the point cloud included in the aerial image taken with the UAV was extracted. As the amount of point cloud increases, accurate 3D mapping is possible, For accurate 3D mapping, it is judged that a point cloud acquisition method for difficult-to-photograph parts in the air is required. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. Fourth, the digital elevation model(DEM) produced with aerial image taken with an UAV can visually express the altitude and shape of the topography of the study site, so it can be used as data to predict the effects of topographical changes due to changes in rural space. Therefore, it is possible to utilize various results using the data included in the aerial image taken by the UAV. In this study, the superiority of images acquired by UAV was verified by comparison with existing images, and the effect of 3D mapping on rural space monitoring was visually analyzed. If various types of spatial data such as GIS analysis and topographic map production are collected and utilized using data that can be acquired by unmanned aerial vehicles, it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.