Transforming remotely-sensed SIF to ecosystem structure, functions, and service: Part II - Harnessing data

Authors: SUN, YING - Cornell University; WEN, JIAMING - Cornell University; GU, JIAMING - Oak Ridge National Laboratory; VAN DER TOL, CHRISTIAAN - University Of Twente; PORCAR-CASTELL, ALBERT - University Of Helsinki; JOINER, JOANNA - Nasa Goddard Institute For Space Studies; Chang, Christine; MAGNEY, TROY - University Of California, Davis; WANG, LIXIN - Indiana University-Purdue University; HU, LEIQIU - University Of Alabama; RASCHER, UWE - Forschungszentrum Juelich Gmbh; ZARCO-TEJADA, PABLO - University Of Melbourne; BARRETT, CHRISTOPHER - Cornell University; LAI, JIAMENG - Cornell University; HAN, JIMEI - Cornell University

Submitted to: Global Change Biology
Publication Type: Review Article
Publication Acceptance Date: 2/14/2023
Publication Date: 2/18/2023
Citation: Sun, Y., Wen, J., Gu, J., Van Der Tol, C., Porcar-Castell, A., Joiner, J., Chang, C.Y., Magney, T.S., Wang, L., Hu, L., Rascher, U., Zarco-Tejada, P., Barrett, C.B., Lai, J., Han, J. 2023. Transforming remotely-sensed SIF to ecosystem structure, functions, and service: Part II - Harnessing data. Global Change Biology. 29(11):2893-2925. https://doi.org/10.1111/gcb.16646.
DOI: https://doi.org/10.1111/gcb.16646

Interpretive Summary: This review paper outlines the state of the art, challenges and next steps required to accelerate the development of an emerging remote sensing technology (solar-induced chlorophyll fluorescence, or SIF) for widespread use across diverse research sectors. This effort provides a comprehensive overview to outline the existing observational data and instrumentation available for tracking SIF, clarify inconsistencies and contradictory findings, and discuss how data variability, scale and uncertainty can impact process interpretation for SIF applications. This review also identifies existing data and technology gaps to direct future innovation for advancing SIF research.

Technical Abstract: The past two decades have witnessed a rapid growth in research using remote sensing of solar-induced chlorophyll fluorescence (SIF). An explosion in availability of SIF data at increasingly higher spatial and temporal resolution has sparked applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, socioeconomics). These applications theoretical inferences envisioned in Sun et al. (2022a) can only be achieved with the support of high quality SIF observations at relevant scales with optimized SIF instrumentation and resolution of relationships between broadband and spectral SIF and between observable and total SIF. At present, there are considerable inconsistencies among diverse SIF datasets and contradictory findings in applying them. The present paper, as a companion review to Sun et al. (2022a), aims to provide clarifications on the apparent inconsistencies and contradictory findings, and therefore address the forward, inference, and innovation questions laid out in (Sun et al., 2022a) from the data perspective. This paper expands the discussion of how SIF data variety, scale, and uncertainty may impact process interpretation for various applications and contribute to inconsistency across findings. We also offer our perspectives on existing data gaps in SIF observations and innovations needed to move forward to help improve monitor/predict ecosystem structure, function, and service under climate change.