Innovative use of spatial regression models to predict the effects of green infrastructure on land surface temperatures

Abstract Understanding the complex and dynamic interplay and cumulative effects of green infrastructure (GI) and urban form on land surface temperatures (LST) is important to design and implement heat mitigation strategies. Past research has mostly employed two-dimensional (2D) indicators, simple correlations and conventional regression models using coarse-level analytical approaches that obviate spatial autocorrelation effects. For the first time, this study applies a holistic approach to evaluate GI and urban settings as complex dynamic systems. The objectives of this paper are to: (1) develop novel ‘spatially-based’ predictive models that account for spatial dependencies; (2) implement a fine-scale analytical unit (