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Structural Complexity Biases Vegetation Greenness MeasuresVegetation ‘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.
Document ID
20230013996
Acquisition Source
Ames Research Center
Document Type
Reprint (Version printed in journal)
Authors
Yelu Zeng ORCID
(University of Wisconsin–Madison Madison, United States)
Dalei Hao ORCID
(Pacific Northwest National Laboratory Richland, United States)
Taejin Park ORCID
(Bay Area Environmental Research Institute Petaluma, United States)
Peng Zhu
(University of Hong Kong Hong Kong, Hong Kong)
Alfredo Huete ORCID
(University of Technology Sydney Sydney, New South Wales, Australia)
Ranga Myneni
(Boston University Boston, United States)
Yuri Knyazikhin
(Boston University Boston, United States)
Jianbo Qi
(Centre d'Études Spatiales de la Biosphère Toulouse, France)
Ramakrishna R Nemani
(Ames Research Center Mountain View, United States)
Fa Li ORCID
(University of Wisconsin–Madison Madison, United States)
Jianxi Huang ORCID
(China Agricultural University Beijing, China)
Yongyuan Gao ORCID
(China Agricultural University Beijing, China)
Baoguo Li
(China Agricultural University Beijing, China)
Fujiang Ji ORCID
(University of Wisconsin–Madison Madison, United States)
Philipp Köhler ORCID
(European Organisation for the Exploitation of Meteorological Satellites Darmstadt, Germany)
Christian Frankenberg ORCID
(California Institute of Technology Pasadena, United States)
Joseph A Berry ORCID
(Carnegie Institution for Science Washington, United States)
Min Chen ORCID
(University of Wisconsin–Madison Madison, United States)
Date Acquired
September 27, 2023
Publication Date
September 14, 2023
Publication Information
Publication: Nature Ecology & Evolution
Publisher: Nature Research
Volume: 7
Issue: 11
Issue Publication Date: November 1, 2023
e-ISSN: 2397-334X
Subject Category
Earth Resources and Remote Sensing
Funding Number(s)
CONTRACT_GRANT: 1027576
CONTRACT_GRANT: 15053347
CONTRACT_GRANT: NNX12AD05A
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
External Peer Committee
Keywords
Vegetation indices
Solar-induced chlorophyll fluorescence
Shadow impacts
Phenology
Ecosystem ecology
vegetation greenness
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