EGU23-11596, updated on 26 Feb 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Monitoring daily cropland CO2-exchange at field scale with Sentinel-2 satellite imagery

Pia Gottschalk1, Aram Kalhori1, Zhan Li2, Christian Wille1, and Torsten Sachs1
Pia Gottschalk et al.
  • 1German Research Centre for Geosciences, Geodesy, Section 1.4 Remote Sensing, Potsdam, Germany (
  • 2BASF Digital Farming GmbH, Im Zollhafen 24, 50678 Köln, Germany

The cropland carbon (C) balance at regional scale still contains high uncertainties not the least due to the problem of up-scaling C fluxes of temporarily and spatially highly divers ecosystems. The C-exchange between the terrestrial ecosystem and the atmosphere constitute the largest and most uncertain flux of the cropland C balance, as opposed to C import from organic (manure) and C export through harvest which are lower and less uncertain.

Combining satellite data with local eddy covariance CO2-flux data is commonly used to up-scale the C-exchange signal from point to regional scale across global ecosystems. Low spatial resolution products like MODIS limit their applicability and accuracy to larger homogeneous areas involving a high degree of uncertainty rather than detecting and tracing highly dynamic (farm-)field scale CO2-fluxes from space. We are using eddy-covariance CO2-flux data of an arable field in conjunction with Sentinel-2 derived vegetation indices (VI) to assess the ability of the satellite data to monitor daily net-ecosystem exchange (NEE), gross-primary productivity (GPP) and ecosystem respiration (Reco) based on a matched footprint. Simple linear regression models are built to test the ability of a range of VIs (NDVI, GNDVI, EVI, EVI2, SAVI, MNDWI, NDWI, SR, S2REP) to monitor and predict CO2-exchange for croplands. We analyze the correlation between measured CO2-fluxes and VIs over the course of the growing seasons to assess the suitability and accuracy of the VIs along the phenological year. We present a single site analysis to zoom into short-comings of this approach and how the satellite signal relates to vegetation CO2-exchange. VIs generally show a high variability in their predictive power. Still, results suggest a similarly high accuracy as mechanistic modelling approaches for suitable VIs, e.g. the cumulative C-exchange (NEE) of winter wheat of one growing season based on NDVI and GNDVI is over- and under-estimated by only 33 (15%) and 41 (18%) g C m-2 respectively.

How to cite: Gottschalk, P., Kalhori, A., Li, Z., Wille, C., and Sachs, T.: Monitoring daily cropland CO2-exchange at field scale with Sentinel-2 satellite imagery, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11596,, 2023.