Combal, B., et al. "Retrieval of canopy biophysical variables from bidirectional reflectance: Using prior information to solve the ill-posed inverse problem." Remote sensing of environment 84.1 (2003): 1-15.
Wang, Z., Skidmore, A. K., Wang, T., Darvishzadeh, R., & Hearne, J. (2015). Applicability of the PROSPECT model for estimating protein and cellulose+ lignin in fresh leaves. Remote sensing of environment , 168 , 205- Physical models also include empirical parts. PROSPECT does so, too. In the paper, leaf potein and lignin + cellulose were decoupled from LMA.
Féret, J.B. et al., 2019. Estimating leaf mass per area and equivalent water thickness based on leaf optical properties: Potential and limitations of physical modeling and machine learning. Remote Sensing of Environment, 231. Physical model has more ability to generalize itself then empirical or statistical models. But the calibration and the inversion algorithm can be essential and complicated step.
Dechant, B., et al. (2017). "Estimation of photosynthesis traits from leaf reflectance spectra: Correlation to nitrogen content as the dominant mechanism." Remote Sensing of Environment 196: 279-292. Photosynthetic traits has its mechanism by leaf internal components. Comparing the spectroscopic absorption of causing components and their traits, they can be detected and correlation. In the case of Vcmax, N dominantly controls it.
Jacquemoud, S., et al. "Estimating leaf biochemistry using the PROSPECT leaf optical properties model." Remote sensing of environment 56.3 (1996): 194-202. Leaf reflectance is affected by leaf biochemicals as well as by pigments or water. Inspecting NIR reflectance, N which is highly correlated to protein and C which are highly correlated to cellulose and lignin can be detected.
Jacquemoud, Stéphane, and F. Baret. PROSPECT A model of leaf optical properties spectra. Remote sensing of environment 34.2 (1990) 75-91. Light travels to a leaf and scatters within the leaf. Interacting with the leaf, the beam could represent the intra-structure. NIR, where absorption would minimized, is the best range.