Spatial Autocorrelation

Spatial Autocorrelation is a spatial statistical phenomenon in which the values of a variable at nearby locations are more similar (or dissimilar) than would be expected under spatial randomness, reflecting the degree of dependency among observations in a geographic space.

1.8K

Publications

148.7K

Citations

3.4K

Authors

1.5K

Institutions

Publications per year

2017–2026

383

Authors

3.4K

  1. DA
    Daniel A. Griffith

    The University of Texas at Dallas, United States

    62 publications · 4.6K citations

    36

    h-index

  2. LA
    Luc Anselin

    Arizona State University, United States

    19 publications · 5.5K citations

    18

    h-index

  3. BH
    Badi H. Baltagi

    Syracuse University, United States

    23 publications · 2.1K citations

    17

    h-index

  4. RR
    Robert R. Sokal

    Stony Brook University, United States

    16 publications · 3.6K citations

    16

    h-index

  5. LL
    Lung‐fei Lee

    The Ohio State University, United States

    16 publications · 967 citations

    15

    h-index

1–5 of 3.4K

Venues

  1. Geographical Analysis

    86 publications · 12.4K citations

    42

    h-index

  2. Journal of Econometrics

    36 publications · 5.9K citations

    28

    h-index

  3. Papers of the Regional Science Association

    27 publications · 2K citations

    24

    h-index

  4. Regional Science and Urban Economics

    31 publications · 4K citations

    24

    h-index

  5. Environment and Planning A Economy and Space

    29 publications · 3.2K citations

    24

    h-index

1–5