Sustainable Estimation of Tree Biomass and Volume Using UAV Imagery: A Comprehensive Review

Abstract

Accurate estimation of tree biomass and volume is essential for sustainable forest management, climate change mitigation, and ecosystem service assessment. Recent advances in unmanned aerial vehicle (UAV) technology enable the acquisition of ultra-high-resolution optical and three-dimensional data, providing a resource-efficient alternative to traditional field-based inventories. This review synthesizes 181 peer-reviewed studies on UAV-based estimation of tree biomass and volume across forestry, agricultural, and urban ecosystems, integrating bibliometric analysis with qualitative literature review. The results reveal a clear methodological shift from early structure-from-motion photogrammetry toward integrated frameworks combining three-dimensional canopy metrics, multispectral or LiDAR data, and machine learning or deep learning models. Across applications, tree height, crown geometry, and canopy volume consistently emerge as the most robust predictors of biomass and volume, enabling accurate individual-tree and plot-level estimates while substantially reducing field effort and ecological disturbance. UAV-based approaches demonstrate particularly strong performance in orchards, plantation forests, and urban environments, and increasing applicability in complex systems such as mangroves and mixed forests. Despite significant progress, key challenges remain, including limited methodological standardization, insufficient uncertainty quantification, scaling constraints beyond local extents, and the underrepresentation of biodiversity-rich and structurally complex ecosystems. Addressing these gaps is critical for the operational integration of UAV-derived biomass and volume estimates into sustainable land management, carbon accounting, and climate-resilient monitoring frameworks.

Plant phenotyping relevance

UAV画像・3Dデータによる樹木のバイオマス、体積、樹高、樹冠形状などの植物形質推定手法を181研究から体系的にレビューしており、フェノタイピング手法が中心です。

Code and data availability

This is a review article synthesizing 181 prior studies on UAV-based tree biomass/volume estimation. The supplied blocks contain no public phenotype datasets, plant/sensor imagery, author analysis code, trained models, or supplements with paper-specific assets. The bibliometric workflow (VOSviewer, Excel, Geochart) is

No evidence-backed public reproduction asset is currently recorded.