Back to Search Start Over

Sensitivity of Estimated Total Canopy SIF Emission to Remotely Sensed LAI and BRDF Products

Authors :
Zhaoying Zhang
Yongguang Zhang
Jing M. Chen
Weimin Ju
Mirco Migliavacca
Tarek S. El-Madany
Source :
Journal of Remote Sensing, Vol 2021 (2021)
Publication Year :
2021
Publisher :
American Association for the Advancement of Science (AAAS), 2021.

Abstract

Remote sensing of solar-induced chlorophyll fluorescence (SIF) provides new possibilities to estimate terrestrial gross primary production (GPP). To mitigate the angular and canopy structural effects on original SIF observed by sensors (SIFobs), it is recommended to derive total canopy SIF emission (SIFtotal) of leaves within a canopy using canopy interception (i0) and reflectance of vegetation (RV). However, the effects of the uncertainties in i0 and RV on the estimation of SIFtotal have not been well understood. Here, we evaluated such effects on the estimation of GPP using the Soil-Canopy-Observation of Photosynthesis and the Energy balance (SCOPE) model. The SCOPE simulations showed that the R2 between GPP and SIFtotal was clearly higher than that between GPP and SIFobs and the differences in R2 (ΔR2) tend to decrease with the increasing levels of uncertainties in i0 and RV. The resultant ΔR2 decreased to zero when the uncertainty level in i0 and RV was ~30% for red band SIF (RSIF, 683 nm) and ~20% for far-red band SIF (FRSIF, 740 nm). In addition, as compared to the TROPOspheric Monitoring Instrument (TROPOMI) SIFobs at both red and far-red bands, SIFtotal derived using any combination of i0 (from MCD15, VNP15, and CGLS LAI products) and RV (from MCD34, MCD19, and VNP43 BRDF products) showed comparable improvements in estimating GPP. With this study, we suggest a way to advance our understanding in the estimation of a more physiological relevant SIF datasets (SIFtotal) using current satellite products.

Details

Language :
English
ISSN :
26941589
Volume :
2021
Database :
Directory of Open Access Journals
Journal :
Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.322963921a634e15b67770f417d635d5
Document Type :
article
Full Text :
https://doi.org/10.34133/2021/9795837