Wang et al. (2026) Evolution of Urban Spatial Structure and Its Impact on the Thermal Environment Based on Local Climate Zones (LCZ): A Case Study of Qingdao

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Atmosphere
• Year: 2026
• Date: 2026-09-27
• Authors: Yanjun Wang, Jiaxin Li, Kaipeng Huo, Jinqiao Ren, Yi Bian, Yan Gao, Mingshuo Pan
• DOI: 10.3390/atmos17100940

Research Groups

[Information not explicitly provided in the paper text.]

Short Summary

This study investigates the nonlinear and scale-dependent responses of Local Climate Zones (LCZs) and their spatial extents to urban thermal environments in Qingdao, China, revealing that the relationship between LCZ area and Wet-Bulb Globe Temperature (WBGT) is complex, with distinct critical scales and response reversals for different LCZ types.

Objective

• To understand the nonlinear responses of different Local Climate Zones (LCZs) and their spatial extents to urban thermal environments.

Study Configuration

• Spatial Scale: Central urban area of Qingdao, China, with a finest simulation resolution of 0.333 km.
• Temporal Scale: 24-hour near-surface meteorological conditions; Sentinel-2A imagery from 2016, 2020, and 2025.

Methodology and Data

• Models used: WRF 4.7–SLUCM (Weather Research and Forecasting model coupled with the Single-Layer Urban Canopy Model), improved Random Forest algorithm, LightGBM (Light Gradient Boosting Machine), SHAP (SHapley Additive exPlanations).
• Data sources: 10 m resolution Sentinel-2A imagery, Google Earth Engine (GEE) platform.

Main Results

• The overall classification accuracy for the 17-class LCZ maps ranged from 74.4% to 75.0%, with Kappa coefficients from 0.7333 to 0.7446.
• SHAP analysis identified four distinct response patterns between LCZ area and Wet-Bulb Globe Temperature (WBGT): negative-to-positive, positive-to-negative, consistently negative, and consistently positive.
• Different LCZ types exhibited distinct area thresholds, with some showing a reversal in their thermal-environment response after exceeding a critical spatial scale.
• The relationship between LCZ and WBGT is a scale-dependent nonlinear statistical association, jointly shaped by land-cover type and patch size.

Contributions

• Established an integrated analytical framework for urban thermal environments by coupling remote sensing-based classification, numerical simulation (WRF–SLUCM), and interpretable machine learning (LightGBM with SHAP).
• Quantified the nonlinear and scale-dependent statistical responses between LCZ area and urban thermal environments (WBGT), identifying critical scales for different LCZ types.
• Provided methodological support for quantitative and fine-scale analysis of urban thermal environments, particularly in coastal hilly cities.

Funding

[Information not explicitly provided in the paper text.]

Citation

@article{Wang2026Evolution,
  author = {Wang, Yanjun and Li, Jiaxin and Huo, Kaipeng and Ren, Jinqiao and Bian, Yi and Gao, Yan and Pan, Mingshuo},
  title = {Evolution of Urban Spatial Structure and Its Impact on the Thermal Environment Based on Local Climate Zones (LCZ): A Case Study of Qingdao},
  journal = {Atmosphere},
  year = {2026},
  doi = {10.3390/atmos17100940},
  url = {https://doi.org/10.3390/atmos17100940}
}