Model-based Spatial Sampling

Model-Based Spatial Sampling is a spatial sampling paradigm that relies on an explicit statistical or mathematical model of the underlying spatial process to guide the selection and inference of sample locations, distinguishing it from design-based approaches by incorporating assumed spatial dependence structures.

32

Publications

2.3K

Citations

109

Authors

69

Institutions

Publications per year

2017–2026

8

Authors

109

  1. DB
    D.J. Brus

    Wageningen University & Research, Netherlands

    3 publications · 453 citations

    3

    h-index

  2. MD
    Michael Dumelle

    NOAA National Marine Fisheries Service Alaska Fisheries Science Center, United States

    2 publications · 100 citations

    2

    h-index

  3. RE
    Robin Engler

    University of Lausanne, Switzerland

    2 publications · 615 citations

    2

    h-index

  4. JD
    J.J. de Gruijter

    Wageningen University & Research, Netherlands

    2 publications · 420 citations

    2

    h-index

  5. AR
    Anthony R. Olsen

    Environmental Protection Agency, United States

    2 publications · 100 citations

    2

    h-index

1–5 of 109

Venues

  1. 2

    h-index

  2. Forest Science

    2 publications · 34 citations

    2

    h-index

  3. Geoderma

    2 publications · 420 citations

    2

    h-index

  4. Environmental and Ecological Statistics

    2 publications · 69 citations

    2

    h-index

  5. Biological Conservation

    1 publications · 15 citations

    1

    h-index

1–5