Spatial Multiscale Inference

Spatial Multiscale Inference is a formal analytical framework that integrates spatial data across multiple scales to infer overarching patterns or processes, distinguished by its explicit modeling of scale-dependent relationships and spatial heterogeneity within a unified inferential structure.

8

Publications

714

Citations

18

Authors

16

Institutions

Publications per year

2017–2026

4

Authors

18

  1. WK
    Wei Kang

    University of California, Riverside, United States

    2 publications · 416 citations

    2

    h-index

  2. HY
    Hanchen Yu

    Arizona State University, United States

    2 publications · 416 citations

    2

    h-index

  3. ZL
    Ziqi Li

    Arizona State University, United States

    2 publications · 416 citations

    2

    h-index

  4. TM
    Taylor M. Oshan

    Arizona State University, United States

    2 publications · 416 citations

    2

    h-index

  5. LJ
    Levi John Wolf

    University of Bristol, United Kingdom

    2 publications · 416 citations

    2

    h-index

1–5 of 18

Venues

  1. Geographical Analysis

    2 publications · 455 citations

    2

    h-index

  2. Ecological Modelling

    1 publications · 26 citations

    1

    h-index

  3. 1

    h-index

  4. Ecography

    1 publications · 57 citations

    1

    h-index

  5. IEEE Transactions on Cognitive and Developmental Systems

    TCDS · 1 publications · 20 citations

1–5