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 obser...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(SIF_(obs)),it is recommended to derive total canopy SIF _(emission)(SIF_(total))of leaves within a canopy using canopy interception(i0)and reflectance of vegetation(R_(V)).However,the effects of the uncertainties in i_(0) and R_(V) 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 R^(2) between GPP and SIF_(total) was clearly higher than that between GPP and SIFobs and the differences in R^(2)(ΔR^(2))tend to decrease with the increasing levels of uncertainties in i_(0) and RV.The resultantΔR^(2) 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,SIF_(total) derived using any combination of i_(0)(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(SIF_(total))using current satellite products.展开更多
基金supported by the National Key R&D Pro-gram of China(2016YFA0600202)the General Program of NSFC(42071388)the fellowship of China Postdoctoral Science Foundation(2021M691491).
文摘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(SIF_(obs)),it is recommended to derive total canopy SIF _(emission)(SIF_(total))of leaves within a canopy using canopy interception(i0)and reflectance of vegetation(R_(V)).However,the effects of the uncertainties in i_(0) and R_(V) 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 R^(2) between GPP and SIF_(total) was clearly higher than that between GPP and SIFobs and the differences in R^(2)(ΔR^(2))tend to decrease with the increasing levels of uncertainties in i_(0) and RV.The resultantΔR^(2) 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,SIF_(total) derived using any combination of i_(0)(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(SIF_(total))using current satellite products.
