## 5 Conclusions  
This study evaluated the feasibility of SIF escape probability estimation methods in discontinuous forest canopies. In general, these estimation methods based on spectral invariants theory have good accuracy for relatively dense forest canopies. The use of NDVI can partly improve the low estimation accuracy for sparse forest canopies. However, if the forest background is partly or totally covered by vegetation, NDVI failed to eliminate the effects of background reflectance on the estimation of SIF escape probability, because NDVI failed to totally reduce the contamination of background reflectance on canopy reflectance. SIF escape probability estimated at a high solar zenith angle will have a higher accuracy than those estimated at a low solar zenith angle in most studied cases due to the potential link between solar zenith angle and background reflectance. For global-scale remote sensing applications, spectral invariant canopy interceptance can be remotely sensed using the current satellite LAI and CI products. However, additional errors will be introduced with the use of satellite products, especially when the product of LAI and CI was underestimated. Our simulation results also show that canopy interceptance can be replaced by fAPAR with a comparable estimation accuracy, and the direct use of fAPAR\({}_{canopy}\) may have a potential advantage than fAPAR\({}_{leaf}\) in sparse forest canopies due to a contamination compensation mechanism. To summarize, our results improved our understanding of SIF escape probability estimation methods in discontinuous forest canopies. However, future work is required to evaluate these findings using measurement data. Such work could explore OCO-2 or TROPOMI SIF retrievals or field observations.  
The following are available online at [[http://www.mdpi.com/2072-4292/12/23/3962/s1](http://www.mdpi.com/2072-4292/12/23/3962/s1)]([http://www.mdpi.com/2072-4292/12/23/3962/s1](http://www.mdpi.com/2072-4292/12/23/3962/s1)), Figure S1: Three background reflectance spectra used for DART simulations (Ref-1: bare soil; Ref-2: soil is partly covered by vegetation; Ref-3: soil is totally covered by vegetation), Figure S2: DART-simulated radiative budgets (Intercepted, Scattered, Absorbed, and Emitted radiance) at each layer of the forest crown (a), emitted SIF at each layer under different simulation settings (b). SIF was simulated at 740 nm. The solar zenith angle was set to 30\({}^{\circ}\) for all simulations, Figure S3: Simulated canopy interceptance (i.e., first row) and corresponding SIF escape probabilities (i.e., second row) using'real' LAI\({}^{\ast}\)CI, \(-\)50% error LAI\({}^{\ast}\)CI, and +50% error LAI\({}^{\ast}\)CI (a,d) FVC = 0.8; (b,e) FVC = 0.6; (c,f) FVC = 0.3.  
Conceptualization, W.L. and S.L.; methodology, W.L., S.L., X.L., J.A. and J.-P.G.-E.; software, W.L. and J.-P.G.-E.; writing--original draft preparation, W.L.; writing--review and editing, W.L., S.L., J.A., and J.-P.G.-E.; visualization, W.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Natural Science Foundation of Fujian Province, China (No. 2019J01396).  
We thank [PERSON] of Natural Resources Institute (Luke) of Finland for Lidar data acquisition, and Dr. [PERSON] for supplementary leaf level fluorescence data collection.  
The authors declare no conflict of interest.