Correlation Analysis between Urban Green Space and Land Surface Temperature from the Perspective of Spatial Heterogeneity: A Case Study within the Sixth Ring Road of Beijing

Urban greening has been widely regarded as the most effective, lasting, and economical strategy for alleviating effects of urban heat islands (UHIs). Previous studies on cooling effect green spaces (UGSs) tend to analyze correlation between landscape metrics land-surface temperature (LST) based a global parameter estimation, while ignoring heterogeneity autocorrelation. This study focuses sixth ring road Beijing uses Landsat 8 imagery retrieve LST extract position UGSs. We propose new approach optimize selection metrics, identify least effective establish geographically weighted regression (GWR) model, plot distribution local coefficients investigate spatially heterogeneous greenspaces. The UGS differs according spatial location; method enhances our understanding configuration UHIs better guides planning construction future