Quantifying Residential Access and Exposure to Greenspace Using High-Resolution Remotely Sensed Data: A Case Study of Metro Vancouver, British Columbia

Despite growing evidence demonstrating the health benefits of greenspaces, the potential differences in effect depending on type of greenspace exposure remain relatively unexplored. The present research aims to develop a methodology to (1) identify greenspace using remotely sensed data and (2) model residential access and exposure to greenspace and the relative difference in vegetation type.Methods:2014 RapidEye satellite imagery and LiDAR datasets from 2008-2015 were combined in eCognition for object-based segmentation, and then classified using Random Forest in R to produce a high-resolution (5m) land cover map of Metro Vancouver, Canada. The land cover map includes 14 classes – covering, for example, coniferous, deciduous, shrub, and grass-herb vegetation. Using the land cover map, greenspace access was calculated as the presence of a public park, recreation area or reserve (≥ 1 hectare) within 300m of residential postal codes and greenspace exposure was calculated as the proportion of gree...