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  • Technical Review
  • Published:

Optical vegetation indices for monitoring terrestrial ecosystems globally

Nature Reviews Earth & Environment volume 3, pages 477–493 (2022)Cite this article

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Abstract

Vegetation indices (VIs), which describe remotely sensed vegetation properties such as photosynthetic activity and canopy structure, are widely used to study vegetation dynamics across scales. However, VI-based results can vary between indices, sensors, quality control measures, compositing algorithms, and atmospheric and sun–target–sensor geometry corrections. These variations make it difficult to draw robust conclusions about ecosystem change and highlight the need for consistent VI application and verification. In this Technical Review, we summarize the history and ecological applications of VIs and the linkages and inconsistencies between them. VIs have been used since the early 1970s and have evolved rapidly with the emergence of new satellite sensors with more spectral channels, new scientific demands and advances in spectroscopy. When choosing VIs, the spectral sensitivity and features of VIs and their suitability for target application should be considered. During data analyses, steps must be taken to minimize the impact of artefacts, VI results should be verified with in situ data when possible and conclusions should be based on multiple sets of indicators. Next-generation VIs with higher signal-to-noise ratios and fewer artefacts will be possible with new satellite missions and integration with emerging vegetation metrics such as solar-induced chlorophyll fluorescence, providing opportunities for studying terrestrial ecosystems globally.

Key points

  • Optical vegetation indices (VIs) derived from space-borne Earth observations are widely used for monitoring terrestrial ecosystems and tracking plant biophysical, biochemical and physiological properties, vegetation dynamics and environmental stresses.

  • Sensor and calibration effects, quality assurance and quality control, bidirectional reflectance distribution function, atmospheric and topographic effects, and snow and soil background effects are among important uncertainty sources of VIs.

  • Potential artefacts must be carefully considered to avoid biased interpretations of the underlying ecological processes resulting from the improper use of VIs.

  • VIs based on reflectance ratios such as the normalized difference vegetation index can help reduce sensor calibration, bidirectional effects, atmospheric and topographic effects, but could be sensitive to snow and soil background and scale effects.

  • Mathematical analysis shows intrinsic similarity among several widely used VIs, including near-infrared reflectance of vegetation, enhanced vegetation index, two-band version of the enhanced vegetation index and difference vegetation index, whereas the ratio-based normalized difference vegetation index behaves differently.

  • Identifying key sensitive wavelengths for target application is the first step towards the optimal use of VIs, followed by an understanding of potential uncertainty sources in the specific ecosystem.

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Fig. 1: Timeline of widely used satellites with the capability to derive vegetation indices.
Fig. 2: Satellite sensors, the vegetation and the soil spectrum across wavelengths.
Fig. 3: The taxonomy, physical meaning and similarity of vegetation indices.
Fig. 4: Vegetation indices artefacts and uncertainties.

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Acknowledgements

Y.Z. and M.C. acknowledges support from the National Aeronautics and Space Administration (NASA) through Remote Sensing Theory and Terrestrial Ecology programmes 80NSSC21K0568 and 80NSSC21K1702. M.C. also acknowledges support by a McIntire–Stennis grant (1027576) from the National Institute of Food and Agriculture (NIFA), United States Department of Agriculture (USDA). B.D. acknowledges support by sDiv, the Synthesis Centre of iDiv (DFG FZT 118, 202548816). J.X. was supported by the National Science Foundation (NSF) (Macrosystems Biology and NEON-Enabled Science programme: DEB-2017870). Y.R. was supported by the National Research Foundation of Korea (NRF-2019R1A2C2084626). The authors thank G. Badgley for fruitful discussions on vegetation indices and P. Köhler for the TROPOMI far-red daily SIF dataset.

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Authors and Affiliations

  1. Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, USA

    Yelu Zeng & Min Chen

  2. Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA

    Dalei Hao

  3. School of Life Sciences, University of Technology Sydney, Sydney, New South Wales, Australia

    Alfredo Huete

  4. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany

    Benjamin Dechant

  5. Leipzig University, Leipzig, Germany

    Benjamin Dechant

  6. Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA

    Joe Berry

  7. Department of Geography and Program in Planning, University of Toronto, Toronto, Ontario, Canada

    Jing M. Chen

  8. NASA Goddard Space Flight Center, Greenbelt, MD, USA

    Joanna Joiner

  9. Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA

    Christian Frankenberg

  10. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA

    Christian Frankenberg

  11. Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA

    Ben Bond-Lamberty

  12. Department of Landscape Architecture and Rural Systems Engineering, Seoul National University, Seoul, South Korea

    Youngryel Ryu

  13. Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA

    Jingfeng Xiao

  14. Universities Space Research Association, Columbia, MD, USA

    Ghassem R. Asrar

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Y.Z., M.C., D.H. and A.H. wrote the initial draft of the manuscript. All authors reviewed and edited the manuscript and made substantial contributions to the improvement of the manuscript.

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Zeng, Y., Hao, D., Huete, A. et al. Optical vegetation indices for monitoring terrestrial ecosystems globally. Nat Rev Earth Environ 3, 477–493 (2022). https://doi.org/10.1038/s43017-022-00298-5

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