Ground Reference Observations Underlying Novel Decametric Vegetation Data Products from Earth Observation

On the consistency and stability of vegetation biophysical variables retrievals from Landsat-8/9 and Sentinel-2 (2025)
Journal Article

Systematic decametric resolution global mapping of vegetation biophysical variables, including fraction of absorbed photosynthetically active radiation (fAPAR), fraction of vegetation cover (fCOVER), and leaf area index (LAI), is required to support... Read More about On the consistency and stability of vegetation biophysical variables retrievals from Landsat-8/9 and Sentinel-2.

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.

Near-infrared digital hemispherical photography enables correction of plant area index for woody material during leaf-on conditions (2023)
Journal Article

Indirect optical measurement techniques enable efficient and non-destructive estimation of plant area index (PAI). However, because they cannot distinguish between foliage and other canopy elements, corrections are needed to determine leaf area index... Read More about Near-infrared digital hemispherical photography enables correction of plant area index for woody material during leaf-on conditions.

Stage 1 Validation of Plant Area Index from the Global Ecosystem Dynamics Investigation (2023)
Journal Article

The Global Ecosystem Dynamics Investigation (GEDI) aims to provide improved characterization of forest structure, and plant area index (PAI) is one of many variables provided in the official GEDI Level 2B (L2B) product suite. However, since release,... Read More about Stage 1 Validation of Plant Area Index from the Global Ecosystem Dynamics Investigation.

HemiPy: A Python module for automated estimation of forest biophysical variables and uncertainties from digital hemispherical photographs (2023)
Journal Article

Digital hemispherical photography (DHP) is widely used to derive forest biophysical variables including leaf, plant, and green area index (LAI, PAI and GAI), the fraction of intercepted photosynthetically active radiation (FIPAR), and the fraction of... Read More about HemiPy: A Python module for automated estimation of forest biophysical variables and uncertainties from digital hemispherical photographs.