Evaluating cooling effect of blue-green infrastructure on urban thermal environment in a metropolitan city: Using geospatial and machine learning techniques

Abstract

Urban blue-green infrastructures (BGIs) have a considerable cooling effect, reducing the urban heat island effect. Therefore, this study aims to evaluate the cooling effects of BGIs and role of the influencing factors on urban thermal environment in Kolkata city, which is one of the largest mega cities of India. An integrated radius and non-linear regression approach was used to determine the maximum distance over which cooling is effective. Further, the relationship between cooling effects of BGIs and influencing factors was analysed using Random Forest based Explainable artificial intelligence model. The result shows that for most of the BGIs, the range of maximum cooling distance varies from 210 to 240 m from the boundary of BGIs. The average PCA value ranges from 6.12 to 16.77 hectares and PCE value ranges from 1.62 to 2.87 depending of BGIs. The results of PCA, PCE and maximum cooling distance indicate that the spatial configurations of BGIs and landscape pattern within and surrounding of BGIs sites strongly influence the cooling effects. The outcomes of this study provide valuable insights for the policymakers and urban planner about the intervention of blue-green infrastructures for the better urban environmental conditions and heat mitigation in mega cities and other urban areas.