A unified vegetation index for quantifying the terrestrial biosphere

Area of Science:

• Earth and Environmental Sciences
• Remote Sensing
• Ecology

Background:

• Empirical vegetation indices (VIs) from spectral data are crucial for biosphere remote sensing.
• Existing VIs serve as proxies for canopy structure, leaf pigments, and photosynthetic potential.

Purpose of the Study:

• To generalize commonly used vegetation indices by incorporating higher-order spectral channel relations.
• To enhance sensitivity to vegetation biophysical and physiological parameters.

Main Methods:

• Developed a nonlinear generalization of the normalized difference vegetation index (NDVI).
• Exploited higher-order relations between spectral channels for improved information extraction.

Main Results:

• The nonlinear NDVI consistently improves accuracy in monitoring leaf area index, gross primary productivity, and sun-induced chlorophyll fluorescence.
• The statistical approach maximizes spectral information utilization.

Conclusions:

• The nonlinear NDVI addresses long-standing challenges in satellite Earth Observation of the terrestrial biosphere.
• This method enables more accurate assessment of terrestrial carbon dynamics and climate change mitigation potentials.