Relationship between land cover patterns and surface temperature in urban areas

Abstract

The relationship between land cover patterns and surface temperature was examined using random forest as well as simple linear regression for two urban sites in Denver, Colorado, USA. Among four land cover types of buildings, trees, grass, and roads and parking lots, only trees and roads and parking lots show significant spatial metrics affecting surface temperature using both the methods. For trees, total class area seems the most important factor affecting surface temperature (R2 = 0.47; percentage of increased mean standard error when mean patch area is excluded %IncMSE = 5.35 for Site B in July), followed by aggregation metrics measuring physical connectedness (R2 for patch cohesion index = 0.42) and patch isolation (%IncMSE for mean Euclidean nearest neighbor distance = 6.01 for Site A in July). For roads and parking lots, the existence of dominantly large patches is the most important factor (R2 for range in patch area = 0.40, for largest patch index = 0.40, for Site B in July), followed by total class area (R2 = 0.39 for Site B in July). Despite some limitations, the findings of this study provide useful information for alleviating urban heat stress especially during summer and reducing adverse impacts of urban drought.