Biogeosciences
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Articles | Volume 22, issue 21
Articles | Volume 22, issue 21
https://doi.org/10.5194/bg-22-6509-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/bg-22-6509-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 21
Research article
 | 
06 Nov 2025
Research article |  | 06 Nov 2025

Identifying alpine treeline species using high-resolution WorldView-3 multispectral imagery and convolutional neural networks

Laurel A. Sindewald, Ryan Lagerquist, Matthew D. Cross, Theodore A. Scambos, Peter J. Anthamatten, and Diana F. Tomback

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Short summary
We used high-resolution satellite imagery and artificial intelligence models to identify six tree and shrub species commonly found at alpine treeline in the Rocky Mountains with accuracies from 44.1% to 86.2%. We are the first to attempt species identification using satellite imagery in treeline systems, where trees are small and difficult to identify remotely. Our work provides a method to identify species with satellite imagery over a broader geographic range than can be achieved with drones.
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Treeline ecotones under global change: linking spatial patterns...
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