Urban Heat and Spatial Statistics, Toward Sustainable Cities and Society: A <scp>PRISMA</scp> ‐Based Systematic Review and Empirical Assessment (2020–2025)

ABSTRACT Over the past few decades, the intensification of global warming has brought increased attention to urban thermal dynamics, particularly regarding Land Surface Temperature (LST) and the Urban Surface Heat Island (SUHI) effect. This study conducts a systematic literature review alongside a bibliometric analysis of 123 peer‐reviewed articles published between 2020 and 2025, examining how these phenomena relate to environmental variables. Using the PRISMA framework and VOSviewer software, we mapped thematic trends, methodological approaches, and key research gaps, classifying studies by publication year. Additionally, we conducted an empirical assessment using a case study dataset to compare several statistical techniques—including Pearson's correlation, ordinary least squares regression (OLS), geographically weighted regression (GWR), and spatial models such as SEM and SAR—to evaluate their explanatory power. Findings reveal that although conventional methods like Pearson and OLS remain dominant, spatial techniques are gaining traction, offering improved residual independence and better model performance. Drawing from this, we propose a practical methodological guide for researchers, reviewers, and editors to support the selection of appropriate statistical tools according to the spatial characteristics of the data. Ultimately, the study aims to encourage the inclusion of spatial reasoning in urban thermal analysis and to foster more accurate, context‐sensitive interpretations.