• Title/Summary/Keyword: Geo-based images

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Detection of the Coastal Wetlands Using the Sentinel-2 Satellite Image and the SRTM DEM Acquired in Gomsoman Bay, West Coasts of South Korea (Sentinel-2 위성영상과 SRTM DEM을 활용한 연안습지 탐지: 서해안 곰소만을 사례로)

  • CHOUNG, Yun-Jae;KIM, Kyoung-Seop;PARK, Insun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.2
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    • pp.52-63
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    • 2021
  • In previous research, the coastal wetlands were detected by using the vegetation indices or land cover classification maps derived from the multispectral bands of the satellite or aerial imagery, and this approach caused the various limitations for detecting the coastal wetlands with high accuracy due to the difficulty of acquiring both land cover and topographic information by using the single remote sensing data. This research suggested the efficient methodology for detecting the coastal wetlands using the sentinel-2 satellite image and SRTM(Shuttle Radar Topography Mission) DEM (Digital Elevation Model) acquired in Gomsoman Bay, west coasts of South Korea through the following steps. First, the NDWI(Normalized Difference Water Index) image was generated using the green and near-infrared bands of the given Sentinel-2 satellite image. Then, the binary image that separating lands and waters was generated from the NDWI image based on the pixel intensity value 0.2 as the threshold and the other binary image that separating the upper sea level areas and the under sea level areas was generated from the SRTM DEM based on the pixel intensity value 0 as the threshold. Finally, the coastal wetland map was generated by overlaying analysis of these binary images. The generated coastal wetland map had the 94% overall accuracy. In addition, the other types of wetlands such as inland wetlands or mountain wetlands were not detected in the generated coastal wetland map, which means that the generated coastal wetland map can be used for the coastal wetland management tasks.

Developing Forecast Technique of Landslide Hazard Area by Integrating Meteorological Observation Data and Topographical Data -A Case Study of Uljin Area- (기상과 지형자료를 통합한 산사태 위험지 예측 기법 개발 -울진지역을 대상으로-)

  • Jo, Myung-Hee;Jo, Yun-Won
    • Journal of the Korean Association of Geographic Information Studies
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    • v.12 no.2
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    • pp.1-10
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    • 2009
  • Recently the large scale of forest disaster such as landslide and forest fire gives a very bad impact on not only forest ecosystem but also farm business so that it has became the main issue of environmental problems. In this study, the landslide hazard area forecast method was developed by considering not only the topographic thematic maps based on GIS and satellite images but also amount of rainfall data, which are very important factors of landslide. Uljin-gun was selected as the study area and the GIS weight score and overlay analysis were applied to topographical map and meteorological observation map. Finally the landslide area distribution map was constructed by considering the evaluation criteria. Also, the accuracy could be acquired by comparing the landslide hazard area forecast map and real damaged area extracted from satellite image.

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URBAN ENVIRONMENTAL QUALITY ANALYSIS USING LANDSAT IMAGES OVER SEOUL, KOREA

  • Lee, Kwon-H.;Wong, Man-Sing;Kim, Gwan-C.;Kim, Young-J.;Nichol, Janet
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.556-559
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    • 2007
  • The Urban Environmental Quality (UEQ) indicates a complex and various parameters resulting from both human and natural factors in an urban area. Vegetation, climate, air quality, and the urban infrastructure may interact to produce effects in an urban area. There are relationships among air pollution, vegetation, and degrading environmental the urban heat island (UHI) effect. This study investigates the application of multi-spectral remote sensing data from the Landsat ETM and TM sensors for the mapping of air quality and UHI intensity in Seoul from 2000 to 2006 in fine resolution (30m) using the emissivity-fusion method. The Haze Optimized Transform (HOT) correction approach has been adopted for atmospheric correction on all bands except thermal band. The general UHI values (${\Delta}(T_{urban}-T_{rural})$) are 8.45 (2000), 9.14 (2001), 8.61 (2002), and $8.41^{\circ}C$ (2006), respectively. Although the UHI values are similar during these years, the spatial coverage of "hot" surface temperature (>$24^{\circ}C$) significantly increased from 2000 to 2006 due to the rapid urban development. Furthermore, high correlations between vegetation index and land surface temperature were achieved with a correlation coefficients of 0.85 (2000), 0.81 (2001), 0.84(2002), and 0.89 (2006), respectively. Air quality is shown to be an important factor in the spatial variation of UEQ. Based on the quantifiable fine resolution satellite image parameters, UEQ can promote the understanding of the complex and dynamic factors controlling urban environment.

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D4AR - A 4-DIMENSIONAL AUGMENTED REALITY - MODEL FOR AUTOMATION AND VISUALIZATION OF CONSTRUCTION PROGRESS MONITORING

  • Mani Golparvar-Fard;Feniosky Pena-Mora
    • International conference on construction engineering and project management
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    • 2009.05a
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    • pp.30-31
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    • 2009
  • Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

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Calculation Method of Oil Slick Area on Sea Surface Using High-resolution Satellite Imagery: M/V Symphony Oil Spill Accident (고해상도 광학위성을 이용한 해상 유출유 면적 산출: 심포니호 기름유출 사고 사례)

  • Kim, Tae-Ho;Shin, Hye-Kyeong;Jang, So Yeong;Ryu, Joung-Mi;Kim, Pyeongjoong;Yang, Chan-Su
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1773-1784
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    • 2021
  • In order to minimize damage to oil spill accidents in the ocean, it is essential to collect a spilled area as soon as possible. Thus satellite-based remote sensing is a powerful source to detect oil spills in the ocean. With the recent rapid increase in the number of available satellites, it has become possible to generate a status report of marine oil spills soon after the accident. In this study, the oil spill area was calculated using various satellite images for the Symphony oil spill accident that occurred off the coast of Qingdao Port, China, on April 27, 2021. In particular, improving the accuracy of oil spill area determination was applied using high-resolution commercial satellite images with a spatial resolution of 2m. Sentinel-1, Sentinel-2, LANDSAT-8, GEO-KOMPSAT-2B (GOCI-II) and Skysat satellite images were collected from April 27 to May 13, but five images were available considering the weather conditions. The spilled oil had spread northeastward, bound for coastal region of China. This trend was confirmed in the Skysat image and also similar to the movement prediction of oil particles from the accident location. From this result, the look-alike patch observed in the north area from the Sentinel-1A (2021.05.01) image was discriminated as a false alarm. Through the survey period, the spilled oil area tends to increase linearly after the accident. This study showed that high-resolution optical satellites can be used to calculate more accurately the distribution area of spilled oil and contribute to establishing efficient response strategies for oil spill accidents.

Performance Testing of Satellite Image Processing based on OGC WPS 2.0 in the OpenStack Cloud Environment (오픈스택 클라우드 환경 OGC WPS 2.0 기반 위성영상처리 성능측정 시험)

  • Yoon, Gooseon;Kim, Kwangseob;Lee, Kiwon
    • Korean Journal of Remote Sensing
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    • v.32 no.6
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    • pp.617-627
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    • 2016
  • Many kinds of OGC-based web standards have been utilized in the lots of geo-spatial application fields for sharing and interoperable processing of large volume of data sets containing satellite images. As well, the number of cloud-based application services by on-demand processing of virtual machines is increasing. However, remote sensing applications using these two huge trends are globally on the initial stage. This study presents a practical linkage case with both aspects of OGC-based standard and cloud computing. Performance test is performed with the implementation result for cloud detection processing. Test objects are WPS 2.0 and two types of geo-based service environment such as web server in a single core and multiple virtual servers implemented on OpenStack cloud computing environment. Performance test unit by JMeter is five requests of GetCapabilities, DescribeProcess, Execute, GetStatus, GetResult in WPS 2.0. As the results, the performance measurement time in a cloud-based environment is faster than that of single server. It is expected that expansion of processing algorithms by WPS 2.0 and virtual processing is possible to target-oriented applications in the practical level.

Individual Ortho-rectification of Coast Guard Aerial Images for Oil Spill Monitoring (유출유 모니터링을 위한 해경 항공 영상의 개별정사보정)

  • Oh, Youngon;Bui, An Ngoc;Choi, Kyoungah;Lee, Impyeong
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1479-1488
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    • 2022
  • Accidents in which oil spills occur intermittently in the ocean due to ship collisions and sinkings. In order to prepare prompt countermeasures when such an accident occurs, it is necessary to accurately identify the current status of spilled oil. To this end, the Coast Guard patrols the target area with a fixed-wing airplane or helicopter and checks it with the naked eye or video, but it was difficult to determine the area contaminated by the spilled oil and its exact location on the map. Accordingly, this study develops a technology for direct ortho-rectification by automatically geo-referencing aerial images collected by the Coast Guard without individual ground reference points to identify the current status of spilled oil. First, meta information required for georeferencing is extracted from a visualized screen of sensor information such as video by optical character recognition (OCR). Based on the extracted information, the external orientation parameters of the image are determined. Images are individually orthorectified using the determined the external orientation parameters. The accuracy of individual orthoimages generated through this method was evaluated to be about tens of meters up to 100 m. The accuracy level was reasonably acceptable considering the inherent errors of the position and attitude sensors, the inaccuracies in the internal orientation parameters such as camera focal length, without using no ground control points. It is judged to be an appropriate level for identifying the current status of spilled oil contaminated areas in the sea. In the future, if real-time transmission of images captured during flight becomes possible, individual orthoimages can be generated in real time through the proposed individual orthorectification technology. Based on this, it can be effectively used to quickly identify the current status of spilled oil contamination and establish countermeasures.

Deep Learning Approach for Automatic Discontinuity Mapping on 3D Model of Tunnel Face (터널 막장 3차원 지형모델 상에서의 불연속면 자동 매핑을 위한 딥러닝 기법 적용 방안)

  • Chuyen Pham;Hyu-Soung Shin
    • Tunnel and Underground Space
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    • v.33 no.6
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    • pp.508-518
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    • 2023
  • This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

Geotomography Applied for the Integrity Test of Cast-in-place Piles (현장타설콘크리트말뚝의 건전도 평가를 위한 geotomography의 적용 연구)

  • Lee Jae-Kyung;Park Jong-Nam
    • Journal of the Korean Geotechnical Society
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    • v.21 no.4
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    • pp.5-12
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    • 2005
  • Recently, geophysical prospecting methods have played very important roles in civil and environmental engineering problems. Technical advances in geophysical instruments and computer system made it possible to get underground images with very high resolution far purposes to resolve those problems. It was possible partly due to ever increasing demand for development of technologies needed to precisely detect polluted areas and prevent ground-related accidents. Based on the same demand, integrity tests of cast-in place piles draw more attention and development of accurate test procedures is required. Ultrasonic methods is one of most advanced non-destructive procedures. In the paper, a geotomography method is employed for the cast-in place pile integrity test using ultrasonic waves. The image of pile interior is scanned and scrutinized far better and more accurate decision in the cast-in place pile integrity. In this study, we firstly examined the accuracy fur tomography program with idealized synthetic models built in water tank: their position and size were changed in the tank and each case was studied. In the next stage, real concrete pile models were fabricated and images of anomaly areas inside the pile were scanned to successfully locate those areas.

Production and Accuracy Analysis of Topographic Status Map Using Drone Images (드론영상을 이용한 지형 현황도 제작 및 정확도 분석)

  • Kim, Doopyo;Back, Kisuk;Kim, Sungbo
    • Journal of the Korean GEO-environmental Society
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    • v.22 no.2
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    • pp.35-39
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    • 2021
  • Photogrammetry using drone can produce high-resolution ortho image and acquire high-accuracy 3D information, which is useful. Therefore, this study attempted to determine the possibility of using drone-photogrammetry in park construction by producing a topographic map using drone-photogrammetry and analyzing the problems and accuracy generated during production. For this purpose, we created ortho image and DSM (digital surface model) using drone images and created topographic status map by vectorizing them. Accuracy was compared based on topographic status map by GPS (global positioning system) and TS (total station). The resulting of analyzing mean of the residuals at check points showed that 0.044 m in plane and 0.066 m in elevation, satisfying the tolerance range of 1/1,000 numerical maps, and result of compared lake size showed a difference of about 4.4%. On the other hand, it was difficult to obtain accurate height values for terrain in which existed vegetation when producing the topographic map, and in the case of underground buried objects, it is not possible to confirm it in the image, so direct spatial information acquisition was necessary. Therefore, it is judged that the topographic status map using drone photogrammetry can be efficiently constructed if direct spatial data acquisition is achieved for some terrain.