dc.creatorLabib, S.M.
dc.creatorHuck, Jonny J.
dc.creatorLindley, Sarah
dc.date.accessioned2020-10-21T20:30:39Z
dc.date.accessioned2022-09-23T18:39:37Z
dc.date.available2020-10-21T20:30:39Z
dc.date.available2022-09-23T18:39:37Z
dc.date.created2020-10-21T20:30:39Z
dc.identifier0048-9697
dc.identifierhttps://doi.org/10.1016/j.scitotenv.2020.143050
dc.identifierhttp://hdl.handle.net/20.500.12010/14675
dc.identifierhttps://doi.org/10.1016/j.scitotenv.2020.143050
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3505050
dc.description.abstractThe 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.
dc.languageeng
dc.publisherScience of the Total Environment
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAbierto (Texto Completo)
dc.sourcereponame:Expeditio Repositorio Institucional UJTL
dc.sourceinstname:Universidad de Bogotá Jorge Tadeo Lozano
dc.subjectGreenspace
dc.subjectEye level greenness visibility
dc.subjectEnvironmental exposure
dc.subjectGeographic Information Systems
dc.subjectUrban health
dc.titleModelling and mapping eye-level greenness visibility exposure using multi-source data at high spatial resolutions


Este ítem pertenece a la siguiente institución