Multiresolution Spatial Representations

Multiresolution Spatial Representations is a geographic data structure that enables the representation of spatial phenomena at varying levels of detail or scales within a single, integrated framework, distinguished by its capacity to support efficient data storage, visualization, and analysis across multiple resolutions.

41

Publications

1.8K

Citations

122

Authors

63

Institutions

Publications per year

2017–2026

8

Authors

122

  1. EP
    Enrico Puppo

    University of Genoa, Italy

    2 publications · 62 citations

    2

    h-index

  2. JO
    Jeff Orchard

    University of Waterloo, Canada

    2 publications · 61 citations

    2

    h-index

  3. JG
    John G. Stell

    University of Leeds, United Kingdom

    2 publications · 92 citations

    2

    h-index

  4. YW
    Yanwei Wang

    Tsinghua University, China

    2 publications · 61 citations

    2

    h-index

  5. KR
    Kannan Ramchandran

    University of California, Berkeley, United States

    2 publications · 61 citations

    2

    h-index

1–5 of 122

Venues

  1. 2

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  2. 2

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  3. Data & Knowledge Engineering

    DKE · 1 publications · 48 citations

    1

    h-index

  4. Experimental Brain Research

    1 publications · 33 citations

    1

    h-index

  5. Computational Materials Science

    1 publications · 44 citations

    1

    h-index

1–5