Multi-Scale Analysis of Plant Landscape and Its Regulatory Effect on Urban Microclimate

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Horticultural Science and Ornamental Plants".

Deadline for manuscript submissions: 28 February 2027 | Viewed by 206

Editors

College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Interests: green space; microclimate; carbon sink; heat island; ecological restoration
College of Architecture and Urban Planning, Fujian University of Technology, 69 Xuefunan Rd, Fuzhou 350118, China
Interests: climate change and adaptive planning; urban green space; air pollution; urban thermal environment; remote sensing
Special Issues, Collections and Topics in MDPI journals
College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Interests: urban biodiversity; spontaneous plants; urban flora composition; biotic homogenization; plant functional traits
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Rapid urbanization and climate change have intensified urban heat islands and extreme heat events, posing serious risks to human health, energy consumption, and ecological sustainability. Plant landscapes—ranging from street trees and green roofs to urban parks and peri-urban forests—offer a nature-based solution to mitigate adverse microclimates through shading, evapotranspiration, and windflow modification. However, the regulatory effect of vegetation on urban microclimate is inherently multi-scale, spanning leaf-level processes (e.g., stomatal conductance), canopy-layer exchanges, neighbourhood airflow patterns, and city-wide thermal belts. Despite growing research, integrating these scales into a coherent analytical framework remains a challenge, limiting the practical application of plant landscape design for climate-resilient cities. Recent advances in remote sensing (e.g., UAV/LiDAR, thermal imagery), high-resolution climate modelling (e.g., ENVI-met, PALM), and distributed sensor networks have enabled unprecedented multi-scale investigation. This Special Issue responds to the urgent need for cross-scale understanding, bridging plant ecophysiology, urban climatology, and landscape planning to support evidence-based greening strategies.

This Special Issue aims to present and disseminate the most recent advances related to multi-scale analysis of plant landscape characteristics and their regulatory effects on urban microclimate. We consider contributions addressing theoretical developments, empirical case studies, modelling simulations, and design applications.

Topics of interest for publication include, but are not limited to, the following:

(1) Multi-scale modelling (leaf to canopy to city) of plant-microclimate interactions;
(2) Field measurements and long-term monitoring of vegetation effects on the urban thermal environment;
(3) Remote sensing and GIS-based assessment of plant landscape patterns and cooling efficiency;
(4) Influence of species composition, canopy structure, and spatial configuration on thermal environment;
(5) Coupling of plant physiological processes (e.g., transpiration, albedo) with microclimate models;
(6) Nature-based solutions and green infrastructure for heat mitigation under different urban morphologies;
(7) Multi-scale optimization of plant landscape layouts for climate adaptation and energy saving;
(8) Integration of plant landscape analysis with urban planning regulations and design guidelines.

Dr. Ming Chen
Dr. Xiong Yao
Dr. Weicong Fu
Guest Editors

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Keywords

  • urban microclimate
  • plant landscape
  • multi-scale analysis
  • heat mitigation
  • thermal comfort
  • nature-based solutions
  • remote sensing
  • urban green infrastructure
  • microclimate modelling
  • landscape planning

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Published Papers (1 paper)

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Research

36 pages, 14890 KB  
Article
Street-Scale Nonlinear Associations Between 2D and 3D Plant Morphology and Land Surface Temperature
by Yufei Zhang, Shenghua Zhang, Yangyang Xu, Ming Chen and Yunxiao Guan
Plants 2026, 15(17), 2561; https://doi.org/10.3390/plants15172561 - 23 Aug 2026
Abstract
Urban streets are important heat-exposure environments, yet the relationships of two-dimensional (2D) planar plant morphology and three-dimensional (3D) vegetation structure with land surface temperature (LST) remain insufficiently integrated at a continuous street scale. We analyzed 42,603 street-scale study units in the central urban [...] Read more.
Urban streets are important heat-exposure environments, yet the relationships of two-dimensional (2D) planar plant morphology and three-dimensional (3D) vegetation structure with land surface temperature (LST) remain insufficiently integrated at a continuous street scale. We analyzed 42,603 street-scale study units in the central urban area of Wuhan, defined at 50 m sampling intervals with a 150 m radius. The 2D variables comprised green-space area (A), mean patch perimeter (P_mean), and perimeter–area ratio (P_A), while the 3D variables comprised green view index (GVI), mean 3D green volume (NV_mean), mean canopy height (CH_mean), and canopy-height variability (CH_sd). Anselin Local Moran’s I identified High–High (HH) and Low–Low (LL) zones; linear regression (LR), random forest (RF), and SHAP characterized linear, nonlinear, and model-based contributions; and buffered spatial cross-validation and spatial resampling evaluated robustness. Under the original random 80–20% train–test split, LR/RF R2 values were 0.2153/0.4002 for the overall study area, 0.1940/0.3539 for the HH zone, and 0.0488/0.4853 for the LL zone. Under five-fold buffered spatial cross-validation, the corresponding pooled out-of-fold R2 values were 0.1940/0.2237, 0.1427/0.0965, and −0.0942/−0.0231, showing that the RF advantage weakened after spatial separation and did not persist in the HH and LL zones. In the original fitted RF models, A, P_mean, and NV_mean had the largest mean absolute SHAP contributions overall; A, P_A, and P_mean ranked highest in the HH zone; and GVI, CH_sd, and CH_mean ranked highest in the LL zone. Repeated buffered spatial validation showed no stable overall 2D predominance because the median 2D share of 52.1% had a 46.5–58.8% percentile range, but it supported stable 2D relative predominance in the HH zone (61.0% [55.5–66.7%]) and stable grouped 3D relative predominance in the LL zone (61.9% [52.3–70.3%]), despite unstable LL variable-level rankings. SHAP relationships were nonlinear and zone-dependent: A and P_mean showed clearer directional transitions overall and in the HH zone, whereas the LL zone and most 3D variables exhibited multiple directional changes. Spatial-block bootstrap analysis examined 40 full-sample zero-crossing candidates, of which 39 met the predefined stability criteria; these ranges represent model-derived directional transitions rather than ecological thresholds or causal planning standards. The findings demonstrate thermal-context-dependent, model-based associations between 2D and 3D plant morphology and street-scale LST, while emphasizing that model performance and some importance rankings are spatially sensitive and require local validation. Full article
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