• Title/Summary/Keyword: Single high resolution satellite image

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3D BUILDING INFORMATION EXTRACTION FROM A SINGLE QUICKBIRD IMAGE

  • Kim, Hye-Jin;Han, Dong-Yeob;Kim, Yong-Il
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.409-412
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    • 2006
  • Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Recognizing this potential use of high resolution satellite imagery, KARI is performing a project for developing Korea multipurpose satellite 3(KOMPSAT-3). Therefore, it is necessary to develop techniques for various GIS applications of KOMPSAT-3, using similar high resolution satellite imagery. As fundamental studies for this purpose, we focused on the extraction of 3D spatial information and the update of existing GIS data from QuickBird imagery. This paper examines the scheme for rectification of high resolution image, and suggests the convenient semi-automatic algorithm for extraction of 3D building information from a single image. The algorithm is based on triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and enhance the digitizing accuracy and the computation efficiency.

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A Semi-Automatic Building Modeling System Using a Single Satellite Image (단일 위성 영상 기반의 반자동 건물 모델링 시스템)

  • Oh, Seon-Ho;Jang, Kyung-Ho;Jung, Soon-Ki
    • The KIPS Transactions:PartB
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    • v.16B no.6
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    • pp.451-462
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    • 2009
  • The spread of satellite image increases various services using it. Especially, 3D visualization services of the whole earth such as $Google\;Earth^{TM}$ and $Virtual\;Earth^{TM}$ or 3D GIS services for several cities provide realistic geometry information of buildings and terrain of wide areas. These service can be used in the various fields such as urban planning, improvement of roads, entertainment, military simulation and emergency response. The research about extracting the building and terrain information effectively from the high-resolution satellite image is required. In this paper, presents a system for effective extraction of the building model from a single high-resolution satellite image, after examine requirements for building model extraction. The proposed system utilizes geometric features of satellite image and the geometric relationship among the building, the shadow of the building, the positions of the sun and the satellite to minimize user interaction. Finally, after extracting the 3D building, the fact that effective extraction of the model from single high-resolution satellite will be show.

Image Fusion Framework for Enhancing Spatial Resolution of Satellite Image using Structure-Texture Decomposition (구조-텍스처 분할을 이용한 위성영상 융합 프레임워크)

  • Yoo, Daehoon
    • Journal of the Korea Computer Graphics Society
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    • v.25 no.3
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    • pp.21-29
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    • 2019
  • This paper proposes a novel framework for image fusion of satellite imagery to enhance spatial resolution of the image via structure-texture decomposition. The resolution of the satellite imagery depends on the sensors, for example, panchromatic images have high spatial resolution but only a single gray band whereas multi-spectral images have low spatial resolution but multiple bands. To enhance the spatial resolution of low-resolution images, such as multi-spectral or infrared images, the proposed framework combines the structures from the low-resolution image and the textures from the high-resolution image. To improve the spatial quality of structural edges, the structure image from the low-resolution image is guided filtered with the structure image from the high-resolution image as the guidance image. The combination step is performed by pixel-wise addition of the filtered structure image and the texture image. Quantitative and qualitative evaluation demonstrate the proposed method preserves spectral and spatial fidelity of input images.

Detection of The Pine Trees Damaged by Pine Wilt Disease using High Resolution Satellite and Airborne Optical Imagery

  • Lee, Seung-Ho;Cho, Hyun-Kook;Lee, Woo-Kyun
    • Korean Journal of Remote Sensing
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    • v.23 no.5
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    • pp.409-420
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    • 2007
  • Since 1988, pine wilt disease has spread over rapidly in Korea. It is not easy to detect the damaged pine trees by pine wilt disease from conventional remote sensing skills. Thus, many possibilities were investigated to detect the damaged pines using various kinds of remote sensing data including high spatial resolution satellite image of 2000/2003 IKONOS and 2005 QuickBird, aerial photos, and digital airborne data, too. Time series of B&W aerial photos at the scale of 1:6,000 were used to validate the results. A local maximum filtering was adapted to determine whether the damaged pines could be detected or not at the tree level from high resolution satellite images, and to locate the damaged trees. Several enhancement methods such as NDVI and image transformations were examined to find out the optimal detection method. Considering the mean crown radius of pine trees, local maximum filter with 3 pixels in radius was adapted to detect the damaged trees on IKONOS image. CIR images of 50 cm resolution were taken by PKNU-3(REDLAKE MS4000) sensor. The simulated CIR images with resolutions of 1 m, 2 m, and 4 m were generated to test the possibility of tree detection both in a stereo and a single mode. In conclusion, in order to detect the pine tree damaged by pine wilt disease at a tree level from satellite image, a spatial resolution might be less than 1 m in a single mode and/or 1 m in a stereo mode.

AUTOMATIC 3D BUILDING INFORMATION EXTRACTION FROM A SINGLE QUICKBIRD IMAGE AND DIGITAL MAPS

  • Kim, Hye-Jin;Byun, Young-Gi;Choi, Jae-Wan;Han, You-Kyung;Kim, Yong-Il
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.238-242
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    • 2007
  • Today's commercial high resolution satellite imagery such as that provided by IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Digital maps supply the most generally used GIS data probiding topography, road, and building information. Currently, the building information provided by digital maps is incompletely constructed for GIS applications due to planar position error and warped shape. We focus on extracting of the accurate building information including position, shape, and height to update the building information of the digital maps and GIS database. In this paper, we propose a new method of 3D building information extraction with a single high resolution satellite image and digital map. Co-registration between the QuickBird image and the 1:1,000 digital maps was carried out automatically using the RPC adjustment model and the building layer of the digital map was projected onto the image. The building roof boundaries were detected using the building layer from the digital map based on the satellite azimuth. The building shape could be modified using a snake algorithm. Then we measured the building height and traced the building bottom automatically using triangular vector structure (TVS) hypothesis. In order to evaluate the proposed method, we estimated accuracy of the extracted building information using LiDAR DSM.

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ESTIMATING CROWN PARAMETERS FROM SPACEBORNE HIGH RESOLUTION IMAGERY

  • Kim, Choen;Hong, Sung-Hoo
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.247-249
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    • 2007
  • Crown parameters are important roles in tree species identification, because the canopy is the aggregate of all the crowns. However, crown measurements with spaceborne image data have remained more difficult than on aerial photographs since trees show more structural detail at higher resolutions. This recognized problem led to the initiation of the research to determine if high resolution satellite image data could be used to identify and classify single tree species. In this paper, shape parameters derived from pixel-based crown area measurements and texture features derived from GLCM parameters in QuickBird image were tested and compared for individual tree species identification. As expected, initial studies have shown that the crown parameters and the canopy texture parameters provided a differentiating method between coniferous trees and broad-leaved trees within the compartment(less than forest stand) for single extraction from spaceborne high resolution image.

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Building Height Extraction using Triangular Vector Structure from a Single High Resolution Satellite Image (삼각벡터구조를 이용한 고해상도 위성 단영상에서의 건물 높이 추출)

  • Kim, Hye-Jin;Han, Dong-Yeob;Kim, Yong-Il
    • Korean Journal of Remote Sensing
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    • v.22 no.6
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    • pp.621-626
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    • 2006
  • Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Extraction of 3D building information from high resolution satellite imagery is one of the most active research topics. There have been many previous works to extract 3D information based on stereo analysis, including sensor modelling. Practically, it is not easy to obtain stereo high resolution satellite images. On single image performance, most studies applied the roof-bottom points or shadow length extracted manually to sensor models with DEM. It is not suitable to apply these algorithms for dense buildings. We aim to extract 3D building information from a single satellite image in a simple and practical way. To measure as many buildings as possible, in this paper, we suggested a new way to extract building height by triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and decrease the digitizing error and the computation efficiency.

Development of the forest type classification technique for the mixed forest with coniferous and broad-leaved species using the high resolution satellite data

  • Sasakawa, Hiroshi;Tsuyuki, Satoshi
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.467-469
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    • 2003
  • This research aimed to develop forest type classification technique for the mixed forest with coniferous and broad-leaved species using the high resolution satellite data. QuickBird data was used as satellite data. The method of this research was to extract satellite data for every single tree crown using image segmentation technique, then to evaluate the accuracy of classification by changing grouping criteria such as tree species, families, coniferous or broad-leaved species, and timber prices. As a result, the classification of tree species and families level was inaccurate, on the other hand, coniferous or broad-leaved species and timber price level was high accurate.

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EXTRACTING BASE DATA FOR FLOOD ANALYSIS USING HIGH RESOLUTION SATELLITE IMAGERY

  • Sohn, Hong-Gyoo;Kim, Jin-Woo;Lee, Jung-Bin;Song, Yeong-Sun
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.426-429
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    • 2006
  • Flood caused by Typhoon and severe rain during summer is the most destructive natural disasters in Korea. Almost every year flood has resulted in a big lost of national infrastructure and loss of civilian lives. It usually takes time and great efforts to estimate the flood-related damages. Government also has pursued proper standard and tool for using state-of-art technologies. High resolution satellite imagery is one of the most promising sources of ground truth information since it provides detailed and current ground information such as building, road, and bare ground. Once high resolution imagery is utilized, it can greatly reduce the amount of field work and cost for flood related damage assessment. The classification of high resolution image is pre-required step to be utilized for the damage assessment. The classified image combined with additional data such as DEM and DSM can help to estimate the flooded areas per each classified land use. This paper applied object-oriented classification scheme to interpret an image not based in a single pixel but in meaningful image objects and their mutual relations. When comparing it with other classification algorithms, object-oriented classification was very effective and accurate. In this paper, IKONOS image is used, but similar level of high resolution Korean KOMPSAT series can be investigated once they are available.

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CREATION OF DIGITAL CITY MODEL FROM A SINGLE KOMPSAT-2 IMAGE

  • Kim, Hye-Jin;Choi, Jae-Wan;Han, You-Kyung;Kim, Yong-II
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.365-367
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    • 2008
  • A digital city model represents a 3D environment of a city with various city object information such as 3D building model, road, and land cover. Usually, at least two satellite images with some image overlap are necessary and a complex satellite-related computation needs to be carried out to create a city model. This is an expensive technique, because it requires many resources and excessive computational cost. The authors propose a methodology to create a digital city model including 3D building model and land cover information from a single high resolution satellite image. The approach consists of image pan-sharpening, shadow recovery, building occlusion restoration, building model extraction, and land cover classification. We create a digital city model using a single KOMPSAT-2 image and review the result.

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