Vegetation is an important component of the earth system and is playing a critical role in the global carbon cycle. Satellite remote sensing has provided highly useful spatial and temporal information on vegetation conditions.
In the early decades of the satellite era starting from 1970’s, scientists were successful in retrieving vegetation structural parameters, including leaf area index (LAI) using multi-spectral data and clumping index (CI) using multi-angle data. These parameters quantify the amount of solar energy absorbed by vegetation that drives its photosynthetic, evaporative and other processes.
Based on these structural parameters, several advances are made in recent years to retrieve vegetation biochemical and physiological parameters, such as leaf chlorophyll content (LCC) and leaf maximum carboxylation rate (Vcmax). LCC defines the ability of plant leaves to harvest photosynthetically active radiation, while Vcmax quantifies the capacity of plant leaves to turn the harvested radiative energy into carbohydrate. Successful retrievals of LCC and Vcmax represent a leap forward in vegetation remote sensing that provides much needed information for global change studies.
In this presentation, I will give a brief overview on key milestones in vegetation structural parameter remote sensing and elaborate on the principles of deriving LCC from multi-spectral data and Vcmax from Sun-induced chlorophyll fluorescence (SIF) data. I will also show some improvements in global vegetation productivity estimation using new Vcmax products.
