Mapping urban heat: Unveiling nature-based solutions in Sari City, Iran.

Abstract

Amidst growing concerns surrounding escalating temperatures and the rapid expansion of urban areas, researchers are delving into the intricate interplay between urban morphology, the intensifying Urban Heat Island (UHI) effect, and the efficacy of Nature-based Solutions (NbS). Despite sustained research efforts, a critical knowledge gap persists in precise modeling and predicting UHI mitigation through NbS interventions. This gap is primarily attributed to nuanced spatial variations at the neighborhood level, where these interventions are commonly implemented. This study addressed the challenge by employing a comprehensive grid structure consisting of 699 cells, covering the entirety of Sari City, Iran, as the spatial scale. The investigation identified five hot zones within the study area. To scrutinize the relationships between the UHI effect and various influencing factors of neighborhood morphology, diverse models such as Ordinary Least Squares (OLS), Random Forest Regression (RFR), Geographically Weighted Regression (GWR), and Mixed Geographically Weighted Regression (MGWR) were applied. Remarkably, the modeling fit for simulated data experienced a significant enhancement with the implementation of MGWR models. Five NbS scenarios were created and simulated using model outputs. The analysis revealed diverse responses across different segments. Notably, green roofs emerged as the most effective mid-term scenario for mitigating the UHI effect.