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Published September 14, 2023 | in press
Journal Article Open

Structural complexity biases vegetation greenness measures

Abstract

Vegetation 'greenness' characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. Our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

Copyright and License

© The Author(s), under exclusive licence to Springer Nature Limited 2023.

Acknowledgement

Support for this research was provided by the Office of the Vice Chancellor for Research and Graduate Education, University of Wisconsin-Madison, with funding from the Wisconsin Alumni Research Foundation. D.H. acknowledges support from the Earth System Model Development programme area, Office of Biological and Environmental Research, Office of Science, US Department of Energy, as part of the Climate Process Team projects. T.P. acknowledges support from the Earth Science Division of NASA. Y.G. acknowledges support from Universities Scientific Fund (15053347). M.C. acknowledges support from a McIntire–Stennis grant (1027576) from the National Institute of Food and Agriculture, US Department of Agriculture. We acknowledge PhenoCam for providing the site imagery at Tapajos and Mead1; the latter was a contribution of the Long-Term Agroecosystem Research network, supported by the US Department of Agriculture. We also thank G. Badgley for fruitful discussions on SIF.

Contributions

These authors contributed equally: Yelu Zeng, Dalei Hao, Taejin Park. 

Y.Z., M.C., D.H. and T.P. conceptualized the study, designed the research and methodology, and wrote the initial draft of the paper. P.Z., A.H., R.M., Y.K., R.N., P.K., C.F., J.B., F.L., Y.G. and F.J. contributed to the data collection and result interpretation. J.Q., J.H., B.L. and F.J. contributed to the 3D ray-tracing model simulation and sensitivity analysis. F.L., Y.G. and F.J. drew and polished the figures. All authors reviewed and edited the paper and made substantial contributions to the improvement of the paper.

Data Availability

The data are available through figshare56 at https://doi.org/10.6084/m9.figshare.23677407.v1.

Code Availability

The source code is available through figshare57 at https://doi.org/10.6084/m9.figshare.23677260.v1.

Conflict of Interest

The authors declare no competing interests.

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Additional details

Created:
September 27, 2023
Modified:
September 27, 2023