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Shortcomings of the normalized difference vegetation index as an exposure metric

Nature Plants volume 8, pages 617–622 (2022)Cite this article

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Abstract

The health benefits of exposure to trees and plants is a rapidly expanding field of study. Research has shown that exposure is associated with improvements in a wide range of health outcomes including cardiovascular disease, birth outcomes, respiratory disease, cancer, mental health and all-cause mortality1. One of the challenges that these studies face is characterizing participants’ exposure to trees and plants. A common approach is to use the normalized difference vegetation index, a greenness index typically derived from satellite imagery. Reliance on the normalized difference vegetation index is understandable; for decades, the imagery required to calculate the normalized difference vegetation index has been available for the entire Earth’s surface and is updated at regular intervals. However, the normalized difference vegetation index may do a poor job of fully characterizing the human experience of being exposed to trees and plants, because scenes with the same normalized difference vegetation index value can appear different to the human eye. We demonstrate this phenomenon by identifying sites in Portland, Oregon that have the same normalized difference vegetation index value as a large, culturally significant elm tree. These sites are strikingly different aesthetically, suggesting that use of the normalized difference vegetation index may lead to exposure misclassification. Where possible, the normalized difference vegetation index should be supplemented with other exposure metrics.

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Fig. 1: Elm tree in Portland, Oregon.
Fig. 2: Nine scenes with the same mean NDVI as heritage elm tree.
Fig. 3: Nine scenes with the same NDVI (mean and SD) as heritage elm tree.
Fig. 4: a. LiDAR point cloud of heritage elm tree. b. Heritage elm tree superimposed on NDVI raster.

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Data availability

High-density Oregon Department of Geology and Mineral Industries (DOGAMI) LiDAR data were obtained from ftp://lidar.engr.oregonstate.edu/OREGON LIDAR CONSORTIUM PROJECT DATA/OLC METRO 2014/ Landsat 8 data were obtained from Google Earth Engine36. The 3-m multispectral, satellite imagery was obtained from Planet37.

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Acknowledgements

This work utilized data made available through the NASA Commercial Smallsat Data Acquisition (CSDA) Program.

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Authors and Affiliations

  1. USDA Forest Service, PNW Research Station, Portland, OR, USA

    Geoffrey H. Donovan & Demetrios Gatziolis

  2. USDA Forest Service, PNW Research Station, Seattle, WA, USA

    Monika Derrien

  3. Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA

    Yvonne L. Michael

  4. USDA Forest Service, Southern Research Station, Research Triangle Park, NC, USA

    Jeffrey P. Prestemon

  5. Centre for Public Health Research, Massey University, Wellington, New Zealand

    Jeroen Douwes

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  1. Geoffrey H. Donovan
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Contributions

G.H.D., D.G., M.D. and J.D. developed the original idea. G.H.D. and D.G. conducted the analysis. G.H.D., D.G., M.D., Y.L.M., J.P.D. and J.D. wrote and edited the paper.

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Correspondence to Geoffrey H. Donovan.

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Nature Plants thanks Peter James and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Figs. 1 and 2.

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Donovan, G.H., Gatziolis, D., Derrien, M. et al. Shortcomings of the normalized difference vegetation index as an exposure metric. Nat. Plants 8, 617–622 (2022). https://doi.org/10.1038/s41477-022-01170-6

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