CoverPy: Automated estimates of plant area index, vegetation cover, crown cover, crown porosity, and uncertainties from digital cover photography in Python

Brown, Luke A.; Leblanc, Sylvain

Abstract

Implemented in Python, CoverPy enables automated estimation of plant area index (PAI), the fraction of vegetation cover (FCOVER), crown cover (CC), and crown porosity (CP) from digital cover photography (DCP). When compared to available alternatives, a key strength of CoverPy is the incorporation of end-to-end uncertainty propagation, enabling uncertainties due to within-plot variability and the user-specified extinction coefficient to be quantified. CoverPy is made available to the community on an open-source basis via GitHub, and should prove useful for researchers and citizen scientists interested in quantifying vegetation structure using inexpensive, non-specialist hardware.

Citation

Brown, L. A., & Leblanc, S. (2024). CoverPy: Automated estimates of plant area index, vegetation cover, crown cover, crown porosity, and uncertainties from digital cover photography in Python. SoftwareX, 27, 101767. https://doi.org/10.1016/j.softx.2024.101767

• Journal Article Type: Article
• Acceptance Date: May 17, 2024
• Online Publication Date: May 30, 2024
• Publication Date: 2024-09
• Deposit Date: May 31, 2024
• Publicly Available Date: Jun 7, 2024
• Journal: SoftwareX
• Print ISSN: 2352-7110
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 27
• Pages: 101767
• DOI: https://doi.org/10.1016/j.softx.2024.101767