In the field of global change ecology and Earth system science, understanding vegetation greenness changes is crucial. Spectral vegetation indices (VIs) have been widely used for this purpose, but they are susceptible to artifacts, as highlighted in recent studies. Our research introduces a groundbreaking discovery: the influence of vegetation structural complexity on VI-based analyses, a factor previously overlooked.
We observed that VIs show higher values over the US Corn Belt compared to the Amazon rainforest, despite the latter having more leaf area. This discrepancy is attributed to differences in structural complexity. Using advanced satellite observations and radiative transfer models, we explore how complex forest structures cast macroscale shadows, resulting in lower spectral greenness compared to simpler crops.
This research has global implications, especially in the context of future land-use changes, and it emphasizes the importance of accounting for shadow impacts when interpreting vegetation changes using VIs.
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Zeng, Y., Hao, D., Park, T., Zhu, P., Huete, A., Myneni, R., Knyazikhin, Y., Qi, J., Nemani, R. R., Li, F., Huang, J., Gao, Y., Li, B., Ji, F., Köhler, P., Frankenberg, C., Berry, J. A., & Chen, M. Structural complexity biases vegetation greenness measures. Nature Ecology & Evolution (2023). https://doi.org/10.1038/s41559-023-02187-6