B007-05
The impact of spatial and temporal aggregation on the relationships among SIF, GPP, and hyperspectral reflectance using airborne data

Monday, 7 December 2020: 05:46
Virtual
Erica Orcutt1, Troy Magney1, Kyle Andreas Arndt2, Eugenie Susanne Euskirchen3, Christopher Florian4, Gabriel Hould Gosselin5, Manuel Helbig6, Hiroki Ikawa7, Hideki Kobayashi8, Andrew Maguire9, Stefan Metzger10, Walter C Oechel11, Ryan Pavlick12, Adrian V Rocha13, Christopher Schulze14, Oliver Sonnentag15, Donatella Zona16 and Christian Frankenberg17, (1)University of California Davis, Plant Sciences, Davis, CA, United States, (2)Washington, DC, United States, (3)University of Alaska Fairbanks, Fairbanks, AK, United States, (4)National Ecological Observatory Network, Battelle, Boulder, CO, United States, (5)University of Montreal, Department of Geography, Montreal, Canada, (6)Dalhousie University, Department of Physics and Atmospheric Science, Halifax, NS, Canada, (7)International Arctic Research Center, Fairbanks, AK, United States, (8)Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan, (9)University of Idaho, Moscow, ID, United States, (10)NEON, Battelle, Boulder, CO, United States, (11)San Diego State University, Global Change Research Group, San Diego, CA, United States, (12)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (13)Univ of Notre Dame, Notre Dame, IN, United States, (14)University of Alberta, Department of Renewable Resources, Edmonton, AB, Canada, (15)Université de Montréal, Département de Géographie, Montréal, QC, Canada, (16)San Diego State University, San Diego, CA, United States, (17)NASA Jet Propulsion Laboratory, Pasadena, CA, United States
Recorded Presentation
Abstract:
Solar-induced fluorescence (SIF) has become an increasingly important spectral signal used to approximate photosynthetic activity in plants. SIF is commonly collected at leaf-level, tower, and increasingly at the satellite scale, but intermediate airborne collection has yet to be fully utilized, particularly in heterogeneous ecosystems. We use data from the Chlorophyll Fluorescence Imaging Spectrometer (CFIS) flown as part of NASA’s Arctic-Boreal Vulnerability Experiment (ABoVE) domain airborne flight campaign in 2017, to compare airborne SIF measurements with gross primary productivity (GPP) estimates from a network of eddy covariance flux towers across ecoregions within the Arctic-Boreal Zone. Additionally, we compare the performance of CFIS to other spectral indices (NIRv, NDVI, PRI, and CCI) derived from collocated observations by NASA’s hyperspectral Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG). Our preliminary results suggest that ecoregions with lower productivity (e.g. herbaceous tundra, linear regression SIF slope estimate= -16.69 R2 = 0.5) are more difficult to correlate GPP with airborne SIF than higher productivity ecoregions (e.g. boreal forests, linear regression SIF slope estimate= 8.65 R2 = 0.03). Additionally, the relationship between GPP and SIF is stronger between when spatiotemporal averaging is conducted to reduce bias in the snapshot nature of airborne measurements (no averaging, R2 = 0.1, averaging daily measurements and over 200m diameter around the tower R2 = 0.15) Our results illustrate the importance of several potential considerations when linking eddy covariance derived CO2 fluxes to airborne SIF and hyperspectral data: 1) canopy structure/heterogeneity; 2) spatiotemporal averaging; 3) flux tower footprint; 4) pixel alignment between data products and across sensors; and 5) light environment. Given these considerations, spectral techniques with higher signal:noise ratios and increased sensitivity to canopy structure (NIRv, NDVI, etc.) provide a stronger link to flux tower GPP in heterogeneous ecoregions.
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