Map Uncertainty Quantification

Map Uncertainty Quantification is a formal framework within spatial prediction that characterizes the uncertainty associated with spatially explicit predictions by systematically assessing the reliability, variability, and confidence of predicted values across geographic space.

153

Publications

8.5K

Citations

515

Authors

272

Institutions

Publications per year

2017–2026

54

Authors

515

  1. SV
    Stephen V. Stehman

    SUNY College of Environmental Science and Forestry, United States

    4 publications · 104 citations

    4

    h-index

  2. RE
    Ronald E. McRoberts

    Northern Research Station, United States

    3 publications · 63 citations

    3

    h-index

  3. MF
    Michael F. Goodchild

    University of California, Santa Barbara, United States

    3 publications · 262 citations

    3

    h-index

  4. CR
    Carlo Ricotta

    Sapienza University of Rome, Italy

    3 publications · 432 citations

    3

    h-index

  5. DK
    Divyani Kohli

    University of Twente, Netherlands

    3 publications · 130 citations

    3

    h-index

1–5 of 515

Venues

  1. 8

    h-index

  2. Remote Sensing of Environment

    6 publications · 165 citations

    6

    h-index

  3. Photogrammetric Engineering & Remote Sensing

    6 publications · 332 citations

    6

    h-index

  4. Remote Sensing

    5 publications · 185 citations

    5

    h-index

  5. Geoderma

    5 publications · 490 citations

    5

    h-index

1–5