The potential of the satellite derived green chlorophyll index for estimating midday light use efficiency in maize, coniferous forest and grassland

Light use efficiency (LUE) is an important variable in carbon cycle and climate change research. We present an investigation of remotely estimating midday LUE using the green chlorophyll index (CI_green) derived from the cloud-free Moderate Resolution Imaging Spectroradiometer (MODIS) images in maize, coniferous forest and grassland. Similar temporal patterns are observed in both canopy chlorophyll content and midday LUE which indicates that the chlorophyll content in the maize canopy servers as a proxy of midday LUE (R² = 0.736, p < 0.001). Therefore, the CI_green, tested as a good indicator of canopy chlorophyll content (R² = 0.840, p < 0.001), has been demonstrated to be a reliable candidate in providing reasonable estimates of midday LUE with determination coefficient R² equals to 0.820 and a root mean square error (RMSE) of 0.002 mol CO₂ per mol incident photosynthetic photon flux density (PPFD). Further validation of the prediction model derived from the maize site demonstrates that the CI_green has potential to be applied in the coniferous forest and grassland ecosystems with RMSE of 0.005 and 0.004 mol CO₂ mol⁻¹ PPFD, respectively. A comparison analysis between different vegetation types is included and these results could be helpful in the development of future LUE and terrestrial models.