Articles | Volume 23, issue 2
https://doi.org/10.5194/bg-23-623-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-23-623-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jan 2026
Research article |
| 22 Jan 2026
| 22 Jan 2026
Machine learning-based Alpine treeline ecotone detection on Xue Mountain in Taiwan
Geng-Gui Wang
Department of Civil Engineering, and Innovation and Development Center of Sustainable Agriculture, National Chung Hsing University, Taichung City 402, Taiwan
Min-Chun Liao
Taiwan Forestry Research Institute, Taipei City 100, Taiwan
Experimental Forest, National Chung Hsing University, 145 Xingda Rd., Taichung City 402, Taiwan
Department of Civil Engineering, and Innovation and Development Center of Sustainable Agriculture, National Chung Hsing University, Taichung City 402, Taiwan
Smart Sustainable New Agriculture Research Center (SMARTer), and i-Center for Advanced Science and Technology, National Chung Hsing University, Taichung City 402, Taiwan
Hsy-Yu Tzeng
Department of Forestry, National Chung Hsing University, Taichung City 402, Taiwan
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Short summary
Taiwan is characterized by high mountains density, with over 200 peaks exceeding 3,000 meters in elevation. This study analyzes treeline changes in Xue Mountain using satellite images from 2012 and 2021. By applying machine learning methods, we found forest are growing higher, rising by 32.00 ± 4.00 m, and forest cover expanded by 10.09 hectares. These findings help us understand climate change impacts on mountain ecosystems and support sustainable conservation efforts.
Taiwan is characterized by high mountains density, with over 200 peaks exceeding 3,000 meters...
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