Land use regression modeling of microscale urban air temperatures in greater Vancouver, Canada

2020 
Abstract Background Extreme heat events have been associated with excess morbidity and mortality worldwide. Previous research mainly evaluated extreme heat exposures at the municipal and local scales, but individuals are exposed in much smaller areas. The goal of this study was to assess whether land use regression (LUR) models could be developed for air temperature using measurements collected by a pedestrian. Methods Microscale air temperature ( Results The most predictive LUR variables were Distance to Large Water Body, Distance to Major Road, Normalized Difference Water Index (NDWI), and Sky-View Factor (SVF). On average, the best individual route models explained 39% of the variation in microscale air temperatures for the 20 routes. The overall model explained only 10% of the variation in the 20 combined routes. Conclusion Mobile air temperatures were associated with geographic and built environment features at the microscale. The collected data were used to build moderately predictive LUR models for some locations, but could not be used to successfully model the entire study area.
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