Modelling and mapping eye-level greenness visibility exposure using multi-source data at high spatial resolutions

The visibility of natural greenness is associated with several health benefits along multiple pathways, including stress recovery and attention restoration mechanisms. However, existing methodologies are inadequate for capturing eye-level greenness visibility exposure at high spatial resolutions for observers located on the ground. As a response, we developed an innovative methodological approach to model and map eye-level greenness visibility exposure for 5 m interval locations within a large study area. We used multi-source spatial data and applied viewshed analysis in conjunction with a distance decay model to compute a novel Viewshed Greenness Visibility Index (VGVI) at more than 86 million observer locations. We compared our eye-level visibility exposure map with traditional top-down greenness exposure metrics such as Normalised Differential Vegetation Index (NDVI) and a Street view based Green View Index (SGVI). Furthermore, we compared greenness visibility at street-only locations with total neighbourhood greenness visibility. We found strong to moderate correlations (r = 0.65-0.42, p < 0.05) between greenness visibility and mean NDVI, with a decreasing trend in correlation strength at increasing buffer distances from observer locations. Our findings suggest that top-down and eye-level measurements of greenness are two distinct metrics for assessing greenness exposure. Additionally, VGVI showed a strong correlation (r = 0.481, p < 0.01) with SGVI. Although the new VGVI has good agreement with existing street view based measures, we found that street-only greenness visibility values are not wholly representative of total neighbourhood visibility due to the under-representation of visible greenness in locations such as backyards and community parks. Our new methodology overcomes such underestimations, is easily transferable, and offers a computationally efficient approach to assessing eye-level greenness exposure.

• Tipo de recurso: Article of investigation
• Fecha de publicación: 2020
• Institución: Universidad de Bogotá Jorge Tadeo Lozano
• Repositorio: Expeditio: repositorio UTadeo
• Idioma: eng
• OAI Identifier: oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/14675
• Acceso en línea: https://doi.org/10.1016/j.scitotenv.2020.143050; http://hdl.handle.net/20.500.12010/14675
• Palabra clave: Greenspace; Eye level greenness visibility; Environmental exposure; Geographic Information Systems; Urban health; Síndrome respiratorio agudo grave; COVID-19; SARS-CoV-2; Coronavirus
• License: Abierto (Texto Completo)