A study of fraction of absorbed photosynthetically active radiation characteristics based on SAIL model simulation

Li Li; Yongming Du; Yong Tang; Qinhuo Liu

doi:10.1117/12.977769

21 November 2012 A study of fraction of absorbed photosynthetically active radiation characteristics based on SAIL model simulation

Li Li, Yongming Du, Yong Tang, Qinhuo Liu

Author Affiliations +

Proceedings Volume 8524, Land Surface Remote Sensing; 85242J (2012) https://doi.org/10.1117/12.977769
Event: SPIE Asia-Pacific Remote Sensing, 2012, Kyoto, Japan

Abstract

The photosynthetically Active Radiation reached to plant canopy could be divided into two parts that are direct radiation and diffuse radiation. The paths into the vegetation canopy are different of these two kinds of radiation. It makes Fraction of Absorbed Photosynthetically Active Radiation (FPAR) different. So this difference between direct FPAR and diffuse FPAR must be determined to decide whether it should be considered into the FPAR inversion model. In this study, the SAIL model was modified which could output direct FPAR and diffuse FPAR. Then with the change of input parameters such as solar zenith angle, visiblity and LAI, the direct FPAR and diffuse FPAR would be change. When the visibility is set as 5km, 15km and 30km, the contribution of scattering of FPAR on the total FPAR is 52.6%, 29.3% and 21.7%. The error between whole FPAR and direct FPAR is reduced with the increasing of visibility and increased with the reducing of LAI. The maximum relative error is 13.2%. From the simulation analyses, we could see that direct and diffuse FPAR are different with the changes of environment variables. So when modeling of FPAR, the diffuse part cannot be ignored. Direct FPAR and diffuse FPAR must be modeled respectively. This separation will help improve the accuracy of FPAR inversion.

Citation Download Citation

Li Li, Yongming Du, Yong Tang, and Qinhuo Liu "A study of fraction of absorbed photosynthetically active radiation characteristics based on SAIL model simulation", Proc. SPIE 8524, Land Surface Remote Sensing, 85242J (21 November 2012); https://doi.org/10.1117/12.977769

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