An insight into machine learning models to predict the distribution of Leucanthemum vulgare Lam. in northwestern rangelands of Iran
Author:
Funder
University of Mohaghegh Ardabili
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences,General Environmental Science
Link
https://link.springer.com/content/pdf/10.1007/s12517-022-10137-y.pdf
Reference84 articles.
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3. Ahmad R, Khuroo AA, Charles B, Hamid M, Rashid I, Aravind NA (2019) Global distribution modelling, invasion risk assessment and niche dynamics of Leucanthemum vulgare (ox-eye daisy) under climate change. Sci Rep-UK 9(1). https://doi.org/10.1038/s41598-019-47859-1
4. Ahmed N, Atzberger C, Zewdie W (2021) Species distribution modelling performance and its implication for Sentinel-2-based prediction of invasive Prosopis juliflora in lower Awash River basin. Ethiopia Ecol Process 10(18):1–16. https://doi.org/10.1186/s13717-021-00285-6
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