Spatial Time Series Analysis

Spatial Time Series Analysis is a computational framework within spatial data analytics that integrates temporal dynamics with geographic dependencies to model and analyze sequences of spatially referenced observations over time, distinguishing itself from conventional time series analysis by explicitly accounting for spatial heterogeneity and autocorrelation.

342

Publications

17.7K

Citations

929

Authors

476

Institutions

Publications per year

2017–2026

106

Authors

929

  1. DA
    Daniel A. Griffith

    The University of Texas at Dallas, United States

    5 publications · 232 citations

    5

    h-index

  2. RV
    Ronny Vallejos

    Federico Santa María Technical University, Chile

    4 publications · 82 citations

    4

    h-index

  3. PK
    Phaedon Kyriakidis

    University of California, Santa Barbara, United States

    3 publications · 128 citations

    3

    h-index

  4. CC
    Coro Chasco

    Universidad Autónoma de Madrid, Spain

    3 publications · 36 citations

    3

    h-index

  5. FA
    Fernando A. López Hernández

    Universidad Politécnica de Cartagena, Spain

    3 publications · 36 citations

    3

    h-index

1–5 of 929

Venues

  1. Journal of the American Statistical Association

    15 publications · 955 citations

    12

    h-index

  2. 5

    h-index

  3. Remote Sensing

    4 publications · 101 citations

    4

    h-index

  4. Water Resources Research

    4 publications · 237 citations

    4

    h-index

  5. International Regional Science Review

    IRSR · 4 publications · 222 citations

    4

    h-index

1–5