Li et al. (2026) Carbon Storage Patterns and Sequestration Enhancement Strategies of Urban Green Spaces in High-Density Urban Areas: Insights from Beijing Within the 5th Ring Road

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Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-09-24
• Authors: Bin Li, Na Zhao, Man Wang, Hongyu Wang, Shaowei Lu, Xu Liu, Xiaotian Xu, Shaoning Li
• DOI: 10.3390/rs18193308

Research Groups

• Beijing Normal University, State Key Laboratory of Remote Sensing Science
• Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences

Short Summary

This study developed machine learning models to estimate carbon stocks in urban green spaces using remote sensing data and field observations, with a focus on the Fifth Ring Road area in Beijing. The results show that canopy height is the dominant factor influencing carbon storage variation.

Objective

• Investigate the relationship between urban green space characteristics and carbon cycling

Study Configuration

• Spatial Scale: Urban scale (Fifth Ring Road area, 666.5 km2)
• Temporal Scale: Not specified

Methodology and Data

• Models used: Random Forest (RF), Extreme Gradient Boosting (XGBoost), Gradient Boosting Decision Tree (GBDT), Backpropagation neural network (BP neural network)
• Data sources: GF-7 sub-meter remote sensing imagery, field data from 750 sampling plots

Main Results

• Canopy height dominated carbon storage variation (SHAP contribution: 0.321, 31.7% explanatory rate)
• XGBoost model with Boruta-selected feature set achieved robust performance (R2 = 0.83, RMSE = 1.79 kg/m2, MAE = 1.13 kg/m2)
• Deciduous trees contributed the largest share (80.61%) of total above-ground carbon stock
• Raising canopy height by 1 m could increase above-ground carbon storage by 21.38% within tree-covered areas

Contributions

• Developed a machine learning framework for estimating urban green space carbon stocks using remote sensing data and field observations
• Identified the dominant factor influencing carbon storage variation in urban green spaces (canopy height)

Funding

• Not specified

Citation

@article{Li2026Carbon,
  author = {Li, Bin and Zhao, Na and Wang, Man and Wang, Hongyu and Lu, Shaowei and Liu, Xu and Xu, Xiaotian and Li, Shaoning},
  title = {Carbon Storage Patterns and Sequestration Enhancement Strategies of Urban Green Spaces in High-Density Urban Areas: Insights from Beijing Within the 5th Ring Road},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18193308},
  url = {https://doi.org/10.3390/rs18193308}
}