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Comparing the effectiveness of random forest and generalized linear models in predicting ungulate browsing impact on Kyiv Polissya’s young pine forests Cover

Comparing the effectiveness of random forest and generalized linear models in predicting ungulate browsing impact on Kyiv Polissya’s young pine forests

Folia Forestalia Polonica
Volume 67 (2025): Issue 1 (March 2025)
By: Natalia Vysotska,  Oleksandr Khromuliak,  Oleksandr Borysenko,  Maksym Rumiantsev,  Iryna Yashchuk and  Oleksandr Kipran  
Open Access
|Mar 2025

Authors

Natalia Vysotska

natalia.vysotska@emu.ee

Estonian University of Life Sciences, Institute of Forestry and Engineering, Tartu, Estonia
Ukrainian Research Institute of Forestry and Forest Melioration, Kharkiv, Ukraine

Oleksandr Khromuliak

Dniprovsko-Teterivske State Forest and Hunting Enterprise, Kyiv, Ukraine

Oleksandr Borysenko

University of Tartu, Department of Remote Sensing, Tartu Observatory, Toravere, Estonia
National Aerospace University ‘Kharkiv Aviation Institute’, Department of Geoinformation Technologies and Space Monitoring of the Earth, Kharkiv, Ukraine

Maksym Rumiantsev

Ukrainian Research Institute of Forestry and Forest Melioration, Kharkiv, Ukraine

Iryna Yashchuk

State Enterprise ‘Klavdiivska Forest Research Station’, Kyiv, Ukraine

Oleksandr Kipran

Ukrainian Research Institute of Forestry and Forest Melioration, Kharkiv, Ukraine
DOI: https://doi.org/10.2478/ffp-2025-0001 | Journal eISSN: 2199-5907 | Journal ISSN: 0071-6677
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Language: English
Page range: 1 - 11
Submitted on: Mar 9, 2024
|
Accepted on: Jan 2, 2025
|
Published on: Mar 7, 2025
Published by: Forest Research Institute
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
browsing,
tree species composition,
ungulate density,
tree damage,
machine learning
Related subjects:
Life sciences,
Plant science,
Medicine,
Veterinary medicine

© 2025 Natalia Vysotska, Oleksandr Khromuliak, Oleksandr Borysenko, Maksym Rumiantsev, Iryna Yashchuk, Oleksandr Kipran, published by Forest Research Institute
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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