Spatio-temporal Process Modeling

Spatio-Temporal Process Modeling is a spatial process modeling approach that integrates both spatial and temporal dimensions to represent, analyze, and predict dynamic phenomena evolving over space and time.

191

Publications

13.7K

Citations

505

Authors

267

Institutions

Publications per year

2017–2026

55

Authors

505

  1. AE
    Alan E. Gelfand

    Duke University, United States

    8 publications · 486 citations

    8

    h-index

  2. SB
    Sudipto Banerjee

    University of Minnesota, United States

    7 publications · 493 citations

    7

    h-index

  3. HL
    Han‐Xiong Li

    City University of Hong Kong, Hong Kong SAR China

    6 publications · 171 citations

    6

    h-index

  4. JK
    J. Keith Ord

    Pennsylvania State University, United States

    6 publications · 4.7K citations

    6

    h-index

  5. CQ
    Chenkun Qi

    Shanghai Jiao Tong University, China

    5 publications · 154 citations

    5

    h-index

1–5 of 505

Venues

  1. 9

    h-index

  2. The Annals of Applied Statistics

    AOAS · 6 publications · 323 citations

    6

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 163 citations

    4

    h-index

  4. Transactions in GIS

    4 publications · 153 citations

    4

    h-index

  5. Spatial Statistics

    4 publications · 98 citations

    4

    h-index

1–5