Remote Sensing-based Variability Assessment

Remote Sensing-Based Variability Assessment is a methodological framework within spatial variability analysis that utilizes remotely sensed data to quantify and characterize the spatial heterogeneity of surface phenomena across multiple temporal and spectral scales.

122

Publications

7.2K

Citations

523

Authors

275

Institutions

Publications per year

2017–2026

41

Authors

523

  1. PJ
    Paul J. Curran

    University of Southampton, United Kingdom

    3 publications · 295 citations

    3

    h-index

  2. GM
    Giles M. Foody

    University of Nottingham, United Kingdom

    3 publications · 543 citations

    3

    h-index

  3. GS
    Gonzalo S. Saldías

    University of Concepción, Chile

    2 publications · 198 citations

    2

    h-index

  4. JL
    John L. Largier

    University of California, Davis, United States

    2 publications · 198 citations

    2

    h-index

  5. KS
    Keyvan Soltani

    Razi University, Iran

    2 publications · 127 citations

    2

    h-index

1–5 of 523

Venues

  1. Journal of Geophysical Research Atmospheres

    JGR · 8 publications · 745 citations

    8

    h-index

  2. Remote Sensing of Environment

    7 publications · 526 citations

    7

    h-index

  3. Remote Sensing

    7 publications · 364 citations

    7

    h-index

  4. 5

    h-index

  5. The Science of The Total Environment

    4 publications · 197 citations

    4

    h-index

1–5