Maximum Entropy Modeling

Maximum Entropy Modeling is a statistical modeling framework within habitat suitability analysis that belongs to the class of presence-only species distribution models and is distinguished by its use of the principle of maximum entropy to estimate the most uniform probability distribution of species occurrences given environmental constraints and observed presence data.

2.1K

Publications

165.9K

Citations

6.8K

Authors

2.3K

Institutions

Publications per year

2017–2026

776

Variants

Maxent Modeling

Authors

6.8K

  1. ML
    Marc L. Serre

    University of North Carolina at Chapel Hill, United States

    12 publications · 546 citations

    11

    h-index

  2. RW
    Rulin Wang

    Sichuan Agricultural University, China

    9 publications · 814 citations

    9

    h-index

  3. EM
    Erik M. Vartiainen∥

    Lappeenranta-Lahti University of Technology, Finland

    9 publications · 606 citations

    9

    h-index

  4. HN
    Hermann Ney

    RWTH Aachen University, Germany

    9 publications · 1.4K citations

    9

    h-index

  5. JZ
    Jingjie Zhang

    Chinese Academy of Sciences, China

    9 publications · 441 citations

    9

    h-index

1–5 of 6.8K

Venues

  1. PLoS ONE

    76 publications · 4.9K citations

    43

    h-index

  2. Forests

    40 publications · 1.5K citations

    25

    h-index

  3. Scientific Reports

    35 publications · 1.6K citations

    21

    h-index

  4. Diversity and Distributions

    23 publications · 12.4K citations

    21

    h-index

  5. Ecology and Evolution

    27 publications · 1.4K citations

    21

    h-index

1–5