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From the ground to space: using solar-induced chlorophyll fluorescence to estimate crop productivity

Timely and accurate monitoring of crops is essential for food security. Here, we examine how well solar-induced chlorophyll fluorescence (SIF) can inform crop productivity across the United States. Based on tower-level observations and process-based modeling, we find highly linear gross primary prod...

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Hauptverfasser: He, Liyin (VerfasserIn) , Magney, Troy (VerfasserIn) , Dutta, Debsunder (VerfasserIn) , Yin, Yi (VerfasserIn) , Köhler, Philipp (VerfasserIn) , Großmann, Katja (VerfasserIn) , Stutz, Jochen (VerfasserIn) , Dold, Christian (VerfasserIn) , Hatfield, Jerry (VerfasserIn) , Guan, Kaiyu (VerfasserIn) , Peng, Bin (VerfasserIn) , Frankenberg, Christian (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 09 March 2020
In: Geophysical research letters
Year: 2020, Jahrgang: 47, Heft: 7
ISSN:1944-8007
DOI:10.1029/2020GL087474
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1029/2020GL087474
Verlag, lizenzpflichtig, Volltext: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020GL087474
Volltext
Verfasserangaben:Liyin He, Troy Magney, Debsunder Dutta, Yi Yin, Philipp Köhler, Katja Grossmann, Jochen Stutz, Christian Dold, Jerry Hatfield, Kaiyu Guan, Bin Peng, and Christian Frankenberg
Beschreibung
Zusammenfassung:Timely and accurate monitoring of crops is essential for food security. Here, we examine how well solar-induced chlorophyll fluorescence (SIF) can inform crop productivity across the United States. Based on tower-level observations and process-based modeling, we find highly linear gross primary production (GPP):SIF relationships for C4 crops, while C3 crops show some saturation of GPP at high light when SIF continues to increase. C4 crops yield higher GPP:SIF ratios (30-50%) primarily because SIF is most sensitive to the light reactions (does not account for photorespiration). Scaling to the satellite, we compare SIF from the TROPOspheric Monitoring Instrument (TROPOMI) against tower-derived GPP and county-level crop statistics. Temporally, TROPOMI SIF strongly agrees with GPP observations upscaled across a corn and soybean dominated cropland (R2 = 0.89). Spatially, county-level TROPOMI SIF correlates with crop productivity (R2 = 0.72; 0.86 when accounting for planted area and C3/C4 contributions), highlighting the potential of SIF for reliable crop monitoring.
Beschreibung:Gesehen am 18.09.2020
Beschreibung:Online Resource
ISSN:1944-8007
DOI:10.1029/2020GL087474

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