Influence of canopy biochemical and biophysical variables on reflectance spectra based on canopy radiative transfer model with adding noise

Pudong Liu; Runhe Shi; Hong Wang; Chaoshun Liu; Zhibin Sun; Wei Gao

doi:10.1117/12.2186727

4 September 2015 Influence of canopy biochemical and biophysical variables on reflectance spectra based on canopy radiative transfer model with adding noise

Pudong Liu, Runhe Shi, Hong Wang, Chaoshun Liu, Zhibin Sun, Wei Gao

Author Affiliations +

Proceedings Volume 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII; 96100F (2015) https://doi.org/10.1117/12.2186727
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

Abstract

To provide a reference for canopy parameters inversion, sensitivity analysis of plant canopy parameters based on remote sensing model is a prerequisite for the inversion. Because the local sensitivity analysis do not consider the coupling effect among the parameters, the EFAST (i.e., Extended Fourier Amplitude Sensitivity Test), a global sensitivity analysis, can be used not only for the analysis of each parameter, but also consider the interacted effect among each parameter. Based on PROSAIL model, the paper focused on the parameters’ sensitivity by using simulated data and EFAST method. The results showed that the EFAST considered not only the contribution of single parameter, but also the interactive effects among each parameter, and four parameters, leaf area index (LAI), leaf mesophyll structure (N), the controller factor of the average leaf slope (LIDFa) and soil moisture condition (psoil) had great effect on the canopy reflectance in the whole wavelength from 400 to 2500 nm than other canopy parameters, and the EFAST method enlarged the contribution of some parameters that had little effects.

Citation Download Citation

Pudong Liu, Runhe Shi, Hong Wang, Chaoshun Liu, Zhibin Sun, and Wei Gao "Influence of canopy biochemical and biophysical variables on reflectance spectra based on canopy radiative transfer model with adding noise", Proc. SPIE 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII, 96100F (4 September 2015); https://doi.org/10.1117/12.2186727

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KEYWORDS

Reflectivity

Data modeling

Soil science

Vegetation

Remote sensing

Radiative transfer

Curium

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