Covariance Function Modeling

Covariance Function Modeling is a statistical framework in geodesy that characterizes the spatial correlation structure of geoid undulations by specifying a mathematical function describing the covariance between gravity anomalies or geoid heights at different locations as a function of their separation.

109

Publications

7.9K

Citations

257

Authors

164

Institutions

Publications per year

2017–2026

24

Authors

257

  1. PM
    Pablo Moreno-Muñoz

    Universidad Carlos III de Madrid, Spain

    2 publications · 59 citations

    2

    h-index

  2. TS
    T. Söderström

    Uppsala University, Sweden

    2 publications · 44 citations

    2

    h-index

  3. AM
    Andrew M. Liebhold

    Northern Research Station, United States

    2 publications · 339 citations

    2

    h-index

  4. EL
    Ethan Ligon

    University of California, Berkeley, United States

    2 publications · 270 citations

    2

    h-index

  5. MB
    Moreno Bevilacqua

    University of Valparaíso, Chile

    2 publications · 30 citations

    2

    h-index

1–5 of 257

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 124 citations

    4

    h-index

  2. Ecology

    3 publications · 366 citations

    3

    h-index

  3. Water Resources Research

    3 publications · 334 citations

    3

    h-index

  4. Statistics & Probability Letters

    3 publications · 81 citations

    3

    h-index

  5. Journal of Geophysical Research Atmospheres

    JGR · 2 publications · 38 citations

    2

    h-index

1–5