Vegetation parameterizations in studies of the urban thermal environment: a review.

Wang Ying, Wu Zhifeng, Ren Yin

Journal of Nanjing Forestry University (Natural Sciences Edition） ›› 0

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南京林业大学学报（自然科学版）
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Journal of Nanjing Forestry University (Natural Sciences Edition） ›› 0 DOI: 10.12302/j.issn.1000-2006.202501044

Vegetation parameterizations in studies of the urban thermal environment: a review.

  • Wang Ying1,2, Wu Zhifeng1, Ren Yin1,*
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Abstract

Vegetation significantly mitigates urban thermal environment through shading and transpiration, making its rational planning and management a crucial strategy for alleviating the urban heat island effect. A core challenge in relevant research lies in accurately quantifying the complex structure and functions of vegetation. This paper systematically reviews vegetation parameterization methods in urban thermal environment studies across three primary pathways: in-situ observation, remote sensing monitoring, and numerical modeling, elaborating on the application principles, functional advantages, and limitations of key parameters such as leaf area index (LAI), vegetation indices (VI), and leaf area density (LAD). Key findings indicate that in-situ observation (e.g., LAI, LAD, sap flow measurements) provides a high-precision foundation for validating ecophysiological mechanisms but struggles with scalability; remote sensing (e.g., NDVI, landscape metrics) enables large-scale pattern monitoring but is constrained by spectral saturation and a lack of three-dimensional structural information; while numerical modeling (e.g., Urban Canopy Models, Computational Fluid Dynamics) can resolve interactions between vegetation and buildings, yet its accuracy is critically dependent on the veracity of input parameters. Current parameterizations reveal notable limitations: LAI merely reflects two-dimensional greenness and fails to characterize vertical canopy heterogeneity, and traditional urban canopy models often simplify vegetation into "big leaves" or planar patches, overlooking three-dimensional interactions with buildings (e.g., multiple reflections, wind obstruction). Furthermore, the reliance on static parameters neglects the temporal impacts of phenology, water stress, and anthropogenic management (e.g., irrigation) on transpiration efficiency, leading to discrepancies between simulated and actual thermal effects. Future directions include multi-source data fusion, advocating for a full-scale observation system integrating "ground-based IoT, airborne LiDAR, and spaceborne hyperspectral" data, and utilizing machine learning algorithms (e.g., GAN, CNN) to retrieve novel three-dimensional vegetation indices with clear biophysical meaning; model coupling and optimization, proposing the development of "physio-structural" integrated vegetation modules that couple dynamic LAI growth models and stomatal conductance models with CFD/UCM frameworks to achieve cross-scale simulations from individual tree physiology to neighborhood microclimates; and standardization, necessitating the establishment of vertical LAD profile maps and physiological parameter libraries for typical urban tree species (especially street trees) to reduce arbitrary empirical assumptions and enhance inter-study comparability. This study provides methodological references for the precise configuration of urban vegetation and climate-adaptive planning aimed at improving the thermal environment.

Key words

urban thermal environment / vegetation parameterization / in-situ observation / remote sensing / numerical modeling / cooling effect / methodological review

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Wang Ying, Wu Zhifeng, Ren Yin. Vegetation parameterizations in studies of the urban thermal environment: a review.[J]. Journal of Nanjing Forestry University (Natural Sciences Edition）. 0 https://doi.org/10.12302/j.issn.1000-2006.202501044

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