欧亚国际

来自Hiphen的科学家近期发布了题为FASPECT: A model of leaf optical properties accounting for the differences between upper and lower faces的文章。Hiphen是著名的室外遥感、表型成像设备与解决方案供应商。

FASPECT: A model of leaf optical properties accounting for the differences between upper and lower faces

Highlights

The FASPECT model is an evolution of the PROSPECT leaf optical properties model.

FASPECT can simulate the reflectance and transmittance of upper and lower leaf faces.

The specific absorption coefficients of chlorophyll and carotenoids were recalibrated.

Significant improvement is proved for dry matter content estimation with FASPECT.

Abstract

Many plant species have distinct optical properties between upper and lower leaf faces. These differences between faces are mainly attributed to the non-homogeneous distribution of absorbing and scattering materials within the leaf depth as well as particular surface features of both epidermises. We proposed the FASPECT model which is an evolution of the PROSPECT model to describe the differences in reflectance and transmittance between leaf faces. The upper and lower epidermis layers are characterized by distinct wavelength-independent reflectivities. Leaf mesophyll is made of a palisade and a spongy parenchyma layers using two parameters that describe the distribution of pigments and leaf structure between these two layers. As compared to the original PROSPECT model that treats the two leaf faces symmetrically, six additional parameters are required to describe the differences in leaf optical properties between the two faces. The specific absorption coefficients of chlorophyll and carotenoids have been recalibrated for the FASPECT model over a dedicated dataset. FASPECT was validated over eight datasets and compared with PROSPECT-5 and PROSPECT-D as well as with the DLM model that also accounts for the differences between the two faces. Results show that the FASPECT model simulates accurately the reflectance and transmittance of the two faces for species presenting distinct reflectance and transmittance properties between the faces. FASPECT outperforms PROSPECT-5 and PROSPECT-D, while providing generally more realistic simulations as compared to DLM. The capacity of the FASPECT model to retrieve leaf biochemical composition from reflectance and transmittance measurements was also evalsuated. Marginal improvement is observed for the estimation of chlorophyll, carotenoids, and water content. Conversely, significant improvement is observed for dry matter content estimation. Conclusions are finally drawn on the interest and limits of the FASPECT model.