ArticleNature ecology & evolution2023
Structural complexity biases vegetation greenness measures.
Article in Nature ecology & evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Widespread carbon accumulation in mature forests remains underestimated by satellite observations.Nature ecology & evolution · 2026Article
- Article
- ENSO amplifies global vegetation resilience variability in a changing climate.Nature communications · 2025Article
- Canopy Structure Exhibits Linear and Nonlinear Links to Biome-Level Maximum Light Use Efficiency.Ecology letters · 2025Article
- Retrieving the chlorophyll content of individual apple trees by reducing canopy shadow impact via a 3D radiative transfer model and UAV multispectral imagery.Plant phenomics (Washington, D.C.) · 2025Article
- Exacerbating risk in human-ignited large fires over western United States due to lower flammability thresholds and greenhouse gas emissions.PNAS nexus · 2025Article
- Assessing Vegetation Canopy Growth Variations in Northeast China.Plants (Basel, Switzerland) · 2025Article
- Thermal, water, and land cover factors led to contrasting urban and rural vegetation resilience to extreme hot months.PNAS nexus · 2024Article
- Ground-Based NDVI Network: Early Validation Practice with Sentinel-2 in South Korea.Sensors (Basel, Switzerland) · 2024Article
- A 30-m annual corn residue coverage dataset from 2013 to 2021 in Northeast China.Scientific data · 2024Article
Corrections and comments
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.