Spatial Data Compression

Spatial Data Compression is a data reduction technique that belongs to the class of spatial database optimization methods, distinguished by its focus on minimizing the storage footprint and transmission overhead of spatial data through algorithmic encoding while preserving topological and geometric fidelity.

189

Publications

7K

Citations

622

Authors

271

Institutions

Publications per year

2017–2026

49

Authors

622

  1. BZ
    Baihua Zheng

    Singapore Management University, Singapore

    4 publications · 254 citations

    4

    h-index

  2. HN
    Hajime Nakata

    University of Occupational and Environmental Health Japan, Japan

    3 publications · 60 citations

    3

    h-index

  3. JH
    Jeong-Hyon Hwang

    University at Albany, State University of New York, United States

    3 publications · 212 citations

    3

    h-index

  4. HS
    Heung‐Yeung Shum

    Microsoft Research Asia (China), China

    3 publications · 181 citations

    3

    h-index

  5. SQ
    Shen‐En Qian

    Canadian Space Agency, Canada

    3 publications · 79 citations

    3

    h-index

1–5 of 622

Venues

  1. 8

    h-index

  2. 5

    h-index

  3. arXiv (Cornell University)

    Repository · 4 publications · 150 citations

    4

    h-index

  4. 3

    h-index

  5. International Journal of Remote Sensing

    3 publications · 262 citations

    3

    h-index

1–5