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Updated: Feb 6, 2026

Characterization of Biological Absorption Spectra Spanning the Visible to the Short-Wave Infrared
Published on: January 10, 2025
A New Vegetation Index Infusing Visible-Infrared Spectral Absorption Feature for Natural Grassland FAPAR Retrieval
Abstract:
Considering the close relationship between spectral absorption features of visible-near infrared and “Fraction of Absorbed Photosynthetically Active Radiation(FAPAR)”, the “automatic recognition method of hyperspectral curve’s characteristic absorption peak” and “quantization method of spectral absorption characteristic parameters” were used to extract the hyperspectral absorption characteristic parameters which are sensitive to FAPAR. Referring to mathematical form of vegetation index, visible-near infrared spectral absorption characteristic parameters were used to replace spectral reflectance and create a new vegetation index to estimate FAPAR of vegetation. The data from 2014 and 2015 on typical natural grassland community canopy in the middle and eastern Inner Mongolia was chosen to build and verify the model of estimating FAPAR. The results showed that new vegetation index “SAI-VI” effectively raised the FAPAR estimating accuracy in the middle and low vegetation coverage areas. Compared with other seven different types of visible-near infrared vegetation index, it has a higher correlation with the value of FAPAR(the largest correlation coefficient is 0.801). The FAPAR prediction index model which takes “SAI-VI” as variable has higher precision and better stability(the determination coefficients of modeling and testing are the highest and both are above 0.75, the “Root Mean Square Error (RMSE)” and “Average Error Coefficient (MEC)” are the minimum). The research also showed that the new vegetation index “SAI-VI” infusing visible-infrared spectral absorption feature highlights the difference between visible spectral and near infrared spectral absorption characteristic parameters. While comparing with single spectral absorption characteristic parameter, “SAI-VI” can depress the influence of soil and enhance the sensitivity to the changes of FAPAR. “SAI-VI” also included the information of hyperspectral absorption characteristic parameters which are sensitive to FAPAR and expressed more detailed information of FAPAR while comparing with original spectral reflectance. “SAI-VI” can be used as a new parameter in inversion of vegetation canopy FAPAR, to some extent it could remedy defect of vegetation index method in estimating FAPAR.
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