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    단보 : 삼각벡터구조를 이용한 고해상도 위성 단영상에서의 건물 높이 추출 = Building Height extraction using Triangular Vector Structure from a Single High Resolution Satellite Image

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    https://www.riss.kr/link?id=A82398970

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    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.
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    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 ...

    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.

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    참고문헌 (Reference)

    1 "단일 고해상도 위성영상으로부터 그림자를 이용한 3차원 건물정보 추출 연구" 인하대학교 2006

    2 "Single-image high-resolution satellite data for 3D information extraction High -Resolution Earth Imaging for Geospatial Information ISPRS workshop" han (han): 2005

    3 "Single-image high-resolution satellite data for 3D information extraction High -Resolution Earth Imaging for Geospatial Information ISPRS workshop" han (han): 2005

    4 "Single and stereo based 3D metrology from high-resolution imagery: methodologies and accuracies" 2004

    5 "Infrastructure Inventory Compilation Using Single High Resolution Satellite Images" Chiba University 2005

    6 "Create Digital City Models from a Single High-Resolution Satellite Image" 38-40, 2003

    7 "Automatic extraction of shadow regions in high-resolution ADS40 images" 808-810, 2004

    8 "Automated building extraction from high-resolution satellite imagery in urban areas using structural, contextual, and spectral information" 2196-2206, 2005

    1 "단일 고해상도 위성영상으로부터 그림자를 이용한 3차원 건물정보 추출 연구" 인하대학교 2006

    2 "Single-image high-resolution satellite data for 3D information extraction High -Resolution Earth Imaging for Geospatial Information ISPRS workshop" han (han): 2005

    3 "Single-image high-resolution satellite data for 3D information extraction High -Resolution Earth Imaging for Geospatial Information ISPRS workshop" han (han): 2005

    4 "Single and stereo based 3D metrology from high-resolution imagery: methodologies and accuracies" 2004

    5 "Infrastructure Inventory Compilation Using Single High Resolution Satellite Images" Chiba University 2005

    6 "Create Digital City Models from a Single High-Resolution Satellite Image" 38-40, 2003

    7 "Automatic extraction of shadow regions in high-resolution ADS40 images" 808-810, 2004

    8 "Automated building extraction from high-resolution satellite imagery in urban areas using structural, contextual, and spectral information" 2196-2206, 2005

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    학술지 이력

    학술지 이력
    연월일 이력구분 이력상세 등재구분
    2027 평가 재인증평가 신청대상 (재인증)
    2021-01-01 등재 등재학술지 유지 (재인증) KCI등재
    2018-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2015-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2011-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2009-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2007-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2006-07-24 학술지등록 한글명 : 대한원격탐사학회지
    외국어명 : Korean Journal of Remote Sensing
    KCI등재
    2005-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2002-07-01 등재 등재학술지 선정 (등재후보2차) KCI등재
    2000-01-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
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    학술지 인용정보

    학술지 인용정보
    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 0.52 0.52 0.54
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    0.53 0.44 0.725 0.12
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