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

doi:10.1016/j.softx.2024.101767

All Outputs (4)

Validation and Conformity Testing of Sentinel-3 Green Instantaneous FAPAR and Canopy Chlorophyll Content Products (2024)
Journal Article

This article presents validation and conformity testing of the Sentinel-3 Ocean Land Colour Instrument (OLCI) green instantaneous fraction of absorbed photosynthetically active radiation (FAPAR) and OLCI terrestrial chlorophyll index (OTCI) canopy ch... Read More about Validation and Conformity Testing of Sentinel-3 Green Instantaneous FAPAR and Canopy Chlorophyll Content Products.

Not just a pretty picture: Mapping Leaf Area Index at 10 m resolution using Sentinel-2 (2024)
Journal Article

Achieving the Global Climate Observing System goal of 10 m resolution leaf area index (LAI) maps is critical for applications related to climate adaptation, sustainable agriculture, and ecosystem monitoring. Five strategies for producing 10 m LAI map... Read More about Not just a pretty picture: Mapping Leaf Area Index at 10 m resolution using Sentinel-2.

Hyperspectral Leaf Area Index and Chlorophyll Retrieval over Forest and Row-Structured Vineyard Canopies (2024)
Journal Article

As an unprecedented stream of decametric hyperspectral observations becomes available from recent and upcoming spaceborne missions, effective algorithms are required to retrieve vegetation biophysical and biochemical variables such as leaf area index... Read More about Hyperspectral Leaf Area Index and Chlorophyll Retrieval over Forest and Row-Structured Vineyard Canopies.

CoverPy: Automated estimates of plant area index, vegetation cover, crown cover, crown porosity, and uncertainties from digital cover photography in Python (2024)
Journal Article
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

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