ORIGINAL RESEARCH article
Front. For. Glob. Change
Sec. People and Forests
This article is part of the Research TopicSustainable Urban Living with Adaptation Measures in Anticipation Against Climate Change: Volume 2View all 4 articles
Urban tree planting should consider local characteristics: Assessing spatial heterogeneity in canopy cooling effects on land surface temperature using Bayesian spatially varying coefficient models
Provisionally accepted
- University of Malaga, Malaga, Spain
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Urban trees play a key role in mitigating elevated temperatures, prompting many cities worldwide to implement large-scale urban tree planting initiatives. The cooling potential of tree canopy coverage is often estimated as a constant value across the study area. However, temperature reductions depend on local characteristics, including tree traits and urban geometry. In this study, we evaluate the ability of Bayesian Spatially Varying Coefficient (SVC) models to capture spatial variations in the cooling potential of urban tree canopy to capture local variability in the cooling potential of urban trees, leveraging the ability of SVCs to estimate spatially structured heterogeneity among covariates. The model was implemented in R-INLA and integrates Landsat 8 and 9 imageries Land Surface Temperature (LST) with aerial LiDAR data. Based on validation metrics obtained through a 10-fold spatial cross validation, the model did not outperform simpler spatio temporal approaches. Nevertheless, the spatial distribution of local canopy cooling capacity on LST, defined as the change in LST associated with a 10% increase in tree canopy cover under ceteris paribus conditions, reveals substantial spatial variability, with average estimated values of −0.28 °C in vacant lands and −0.09 °C in wooded areas. By providing local estimates, the model underscores how the cooling capacity of tree canopy in built-up environments can vary substantially across space, and it serves as an example of a modeling approach that integrates both local scale variability in canopy cooling capacity and spatial extent. This study aims to highlight the importance of accounting for local environmental characteristics in urban planning, encouraging policymakers to adopt context-specific strategies for urban tree planting initiatives.
Keywords: Bayesian, Ecosystem-services, Nature-based solutions, Remote-sensing, urban-greening, Urban-forestry
Received: 10 Jun 2025; Accepted: 05 Nov 2025.
Copyright: © 2025 Ruiz-Valero, Pereña-Ortiz and Salvo-Tierra. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jaime Pereña-Ortiz, jperena@uma.es
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