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      rsmove—An r package to bridge remote sensing and movement ecology

      한글로보기

      https://www.riss.kr/link?id=O119761139

      • 저자
      • 발행기관
      • 학술지명
      • 권호사항
      • 발행연도

        2019년

      • 작성언어

        -

      • Online ISSN

        2041-210X

      • 등재정보

        SCOPUS;SCIE

      • 자료형태

        학술저널

      • 수록면

        1212-1221   [※수록면이 p5 이하이면, Review, Columns, Editor's Note, Abstract 등일 경우가 있습니다.]

      • 구독기관
        • 전북대학교 중앙도서관  
        • 성균관대학교 중앙학술정보관  
        • 부산대학교 중앙도서관  
        • 전남대학교 중앙도서관  
        • 제주대학교 중앙도서관  
        • 중앙대학교 서울캠퍼스 중앙도서관  
        • 인천대학교 학산도서관  
        • 숙명여자대학교 중앙도서관  
        • 서강대학교 로욜라중앙도서관  
        • 계명대학교 동산도서관  
        • 충남대학교 중앙도서관  
        • 한양대학교 백남학술정보관  
        • 이화여자대학교 중앙도서관  
        • 고려대학교 도서관  
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      부가정보

      다국어 초록 (Multilingual Abstract)

      Remote sensing is a valuable tool in movement ecology. However, the way it is combined with animal movement data is far from optimal as most studies overlook differences in the spatial, temporal and thematic resolutions between both data types.

      rsmove uses a pixel‐based approach to link animal tracking and remote sensing data that bridge the gap between these two disciplines while respecting the limitations of the latest. Additionally, if offers standardize methods to pre‐analyse the connection between animal movement and environmental change.

      The package guides the choice of study sites, satellite data and environmental predictors though data mining and visualization tools. rsmove offers a simple methodology to analyse animal–environment interactions that helps avoid unnecessary, time‐consuming satellite data processing through an informed decision process.

      The package offers a basis for a better communication between ecologists and remote sensing experts contributing to the definition of clear remote sensing data requirements. Additionally, it provides future studies on animal movement tools for a more critical approach on the selection of environmental data supporting the reproducibility of animal movement studies.
      번역하기

      Remote sensing is a valuable tool in movement ecology. However, the way it is combined with animal movement data is far from optimal as most studies overlook differences in the spatial, temporal and thematic resolutions between both data types. rsmov...

      Remote sensing is a valuable tool in movement ecology. However, the way it is combined with animal movement data is far from optimal as most studies overlook differences in the spatial, temporal and thematic resolutions between both data types.

      rsmove uses a pixel‐based approach to link animal tracking and remote sensing data that bridge the gap between these two disciplines while respecting the limitations of the latest. Additionally, if offers standardize methods to pre‐analyse the connection between animal movement and environmental change.

      The package guides the choice of study sites, satellite data and environmental predictors though data mining and visualization tools. rsmove offers a simple methodology to analyse animal–environment interactions that helps avoid unnecessary, time‐consuming satellite data processing through an informed decision process.

      The package offers a basis for a better communication between ecologists and remote sensing experts contributing to the definition of clear remote sensing data requirements. Additionally, it provides future studies on animal movement tools for a more critical approach on the selection of environmental data supporting the reproducibility of animal movement studies.

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