Estimating Carbon Sequestration of Urban Street Trees Using UAV-Derived 3D Green Quantity and the Simpson Model

Abstract

Accurately measuring the three-dimensional green quantity (3DGQ) of urban trees is crucial for quantifying carbon sequestration benefits (CSB) in high-density cities. In this study, 540 street trees across 18 species (30 per species) in Shanghai were analyzed to evaluate an Improved Simpson Model (ISM) for UAV-derived crown volume estimation against a traditional Approximate Geometry Model (AGM) and a LiDAR-based point cloud method (PCM). The ISM integrates UAV imagery, edge-based canopy profiling, and Simpson’s numerical integration to account for irregular crown shapes and internal leaf-stem gaps. Results show that ISM achieved consistently lower estimation errors than the benchmark methods. Overall, ISM’s 3DGQ estimates had a root mean square error (RMSE) of approximately 5.2 m3 and a mean absolute error (MAE) of about 4.1 m3, indicating a close match with PCM reference values. This represents a dramatic error reduction, on the order of 90%–95% improvement in RMSE, compared to the conventional AGM approach. Broadleaf species with dense, regular canopies (e.g., Cinnamomum camphora and Platanus × acerifolia) exhibited the highest accuracy, with ISM-predicted volumes deviating only ~1%–2% from field measurements. Even for species with more irregular or porous crowns, the ISM maintained robust performance, yielding smaller errors than AGM and nearly matching the LiDAR-based PCM “ground truth.” These findings demonstrate that the proposed ISM can provide highly accurate 3D crown volume and carbon sequestration estimates in complex urban environments, outperforming existing geometric models and offering a practical, efficient alternative to labor-intensive LiDAR surveys.

Plant phenotyping relevance

UAV画像から樹冠の3次元緑量・体積という植物形質を推定する新手法を開発し、既存モデルおよびLiDARと比較検証しており、フェノタイピング手法が中心である。

Code and data availability

The paper's phenotyping inputs (16,200 UAV images of 540 trees, the DBInfo tree database, and OpenCV-based ISM analysis code) are not deposited publicly. The Data Availability Statement only offers contact with the corresponding author, and no authors' public URL for data or code is provided. The allowed URLs (DOI, DJI

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