The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological
Amy Mizen1, Daniel A Thompson2, Alan Watkins2
1Swansea University Medical School, Swansea University, Swansea, UK. a.r.mizen@swansea.ac.uk.
Background:
Exposure to green space can protect against poor health through a variety of mechanisms. However, there is heterogeneity in methodological approaches to exposure assessments which makes creating effective policy recommendations challenging.
Objective:
Critically evaluate the use of a satellite-derived exposure metric, the Enhanced Vegetation Index (EVI), for assessing access to different types of green space in epidemiological studies.
Methods:
We used Landsat 5-8 (30 m resolution) to calculate average EVI for a 300 m radius surrounding 1.4 million households in Wales, UK for 2018. We calculated two additional measures using topographic vector data to represent access to green spaces within 300 m of household locations. The two topographic vector-based measures were total green space area stratified by type and average private garden size. We used linear regression models to test whether EVI could discriminate between publicly accessible and private green space and Pearson correlation to test associations between EVI and green space types.
Results:
Mean EVI for a 300 m radius surrounding households in Wales was 0.28 (IQR = 0.12). Total green space area and average private garden size were significantly positively associated with corresponding EVI measures (β = < 0.0001, 95% CI: 0.0000, 0.0000; β = 0.0001, 95% CI: 0.0001, 0.0001 respectively). In urban areas, as average garden size increases by 1 m2, EVI increases by 0.0002. Therefore, in urban areas, to see a 0.1 unit increase in EVI index score, garden size would need to increase by 500 m2. The very small β values represent no 'measurable real-world' associations. When stratified by type, we observed no strong associations between greenspace and EVI.
Impact:
It is a widely implemented assumption in epidiological studies that an increase in EVI is equivalent to an increase in greenness and/or green space. We used linear regression models to test associations between EVI and potential sources of green reflectance at a neighbourhood level using satellite imagery from 2018. We compared EVI measures with a 'gold standard' vector-based dataset that defines publicly accessible and private green spaces. We found that EVI should be interpreted with care as a greater EVI score does not necessarily mean greater access to publicly available green spaces in the hyperlocal environment.
