Hierarchical Spatial Decomposition

Hierarchical Spatial Decomposition is a hierarchical data organization method that partitions three-dimensional space into successively finer levels of spatial resolution through recursive subdivision, enabling efficient representation and selective refinement of volumetric data.

131

Publications

8.6K

Citations

361

Authors

179

Institutions

Publications per year

2017–2026

17

Authors

361

  1. JC
    J. C. Phillips

    University of Illinois Urbana-Champaign, United States

    3 publications · 47 citations

    3

    h-index

  2. LV
    Laxmikant V. Kalé

    University of Illinois Urbana-Champaign, United States

    3 publications · 47 citations

    3

    h-index

  3. AB
    Achi Brandt

    Weizmann Institute of Science, Israel

    3 publications · 369 citations

    3

    h-index

  4. RB
    Ronen Basri

    Weizmann Institute of Science, Israel

    3 publications · 369 citations

    3

    h-index

  5. AN
    Aiichiro Nakano

    University of Southern California, United States

    2 publications · 117 citations

    2

    h-index

1–5 of 361

Venues

  1. 3

    h-index

  2. Transactions in GIS

    3 publications · 45 citations

    3

    h-index

  3. IEEE Transactions on Image Processing

    3 publications · 425 citations

    3

    h-index

  4. Geographical Analysis

    3 publications · 180 citations

    3

    h-index

  5. Communications in Mathematical Sciences

    2 publications · 163 citations

    2

    h-index

1–5