Network Spatial Autocorrelation

Network Spatial Autocorrelation is a spatial statistical measure that quantifies the degree to which related observations on a network exhibit similar values at neighboring locations, distinguished from planar spatial autocorrelation by accounting for connectivity and distance along network pathways rather than Euclidean space.

65

Publications

3.4K

Citations

183

Authors

107

Institutions

Publications per year

2017–2026

30

Authors

183

  1. MM
    Malcolm M. Dow

    Northwestern University, United States

    5 publications · 301 citations

    5

    h-index

  2. YC
    Yongwan Chun

    The University of Texas at Dallas, United States

    4 publications · 393 citations

    4

    h-index

  3. TC
    Tao Cheng

    University College London, United Kingdom

    3 publications · 267 citations

    3

    h-index

  4. JW
    Jiaqiu Wang

    Queensland University of Technology, Australia

    3 publications · 267 citations

    3

    h-index

  5. DA
    Daniel A. Griffith

    The University of Texas at Dallas, United States

    2 publications · 189 citations

    2

    h-index

1–5 of 183

Venues

  1. Journal of Geographical Systems

    5 publications · 416 citations

    5

    h-index

  2. Social Networks

    3 publications · 217 citations

    3

    h-index

  3. Geographical Analysis

    3 publications · 140 citations

    3

    h-index

  4. Population Space and Place

    3 publications · 230 citations

    3

    h-index

  5. Cross-Cultural Research

    2 publications · 69 citations

    2

    h-index

1–5