[1] Accurate estimation of spatially distributed chlorophyll content (Chl) in crops is of great importance for regional and global studies of carbon balance and responses to fertilizer (e.g., nitrogen) application. In this paper a recently developed conceptual model was applied for remotely estimating Chl in maize and soybean canopies. We tuned the spectral regions to be included in the model, according to the optical characteristics of the crops studied, and showed that the developed technique allowed accurate estimation of total Chl in both crops, explaining more than 92% of Chl variation. This new technique shows great potential for remotely tracking the physiological status of crops, with contrasting canopy architectures, and their responses to environmental changes.

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Remote estimation of canopy chlorophyll content in crops

http://www.geog.ucl.ac.uk/~mdisney/teaching/GEOGG141/papers/jacquemoud_et_al_prospect_4_5.pdf

PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments

https://www.ipgp.fr/~jacquemoud/publications/ustin2009.pdf

Retrieval of foliar information about plant pigment systems from high resolution spectroscopy

http://www.yorku.ca/jrmiller/Papers/05Zarco_RSE_vineyard_condition.pdf

Assessing vineyard condition with hyperspectral indices: Leaf and canopy reflectance simulation in a row-structured discontinuous canopy

https://www.calmit.unl.edu/people/agitelson2/pdf/2011/2011-RSE-GLAI.pdf

Comparison of different vegetation indices for the remote assessment of green leaf area index of crops

https://www.calmit.unl.edu/people/agitelson2/pdf/06_JPP-2003.pdf

Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves

Yuri Gritz

Papers

Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves