Advanced intelligent recognition algorithm for tree canopy carbon sequestration capacity based on 3D visualization: application in Larch plantations under drought stress

•Developed an intelligent 3D canopy recognition algorithm integrating LiDAR, UAV, and deep learning techniques.•Quantified drought-induced changes in LAI, light penetration, and canopy architecture in Larix kaempferi plantations.•Demonstrated how optimized leaf arrangement enhances photosynthetic ef...

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Veröffentlicht in:Ecological indicators Jg. 178; S. 113780
Hauptverfasser: Wu, Chunyan, Cheng, Min, Chen, Dongsheng, Zhang, Shougong, Sun, Xiaomei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.09.2025
Elsevier
Schlagworte:
3D visualization
Carbon sequestration
Intelligent recognition algorithm
LiDAR and UAVs
Photosynthetic efficiency
Point cloud data
Photosynthetic efficiency
3D visualization
LiDAR and UAVs
Point cloud data
Intelligent recognition algorithm
Carbon sequestration
ISSN:1470-160X
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Zusammenfassung:•Developed an intelligent 3D canopy recognition algorithm integrating LiDAR, UAV, and deep learning techniques.•Quantified drought-induced changes in LAI, light penetration, and canopy architecture in Larix kaempferi plantations.•Demonstrated how optimized leaf arrangement enhances photosynthetic efficiency under water stress.•Achieved accurate, real-time carbon sequestration estimates using structural and physiological integration.•Provided a scalable framework for adaptive forest carbon management under diverse climate scenarios. This study presents an advanced 3D visualization-based intelligent algorithm to assess and enhance Larix kaempferi carbon sequestration under drought stress. This approach addresses the critical impacts of drought on canopy structure and photosynthetic efficiency, significantly reducing carbon gain in larch plantations. Our research utilizes high-precision 3D canopy models combined with detailed physiological data to reveal the negative effects of drought on the cumulative leaf area index (cLAI) and maximum photosynthetic efficiency (Amax). The findings demonstrate that while drought stress reduces overall leaf area, the optimized leaf arrangement and minimized ineffective leaf area enable trees to more efficiently utilize water for photosynthesis, thereby preserving or even enhancing their carbon sequestration capacity. By leveraging 3D reconstruction technology, this study provides real-time, accurate data that significantly improves our understanding of forest ecosystem dynamics under extreme climatic conditions. The intelligent algorithm developed offers a robust tool for predicting and optimizing forest carbon sequestration, presenting new opportunities for forest management and conservation. The application of advanced 3D visualization and intelligent algorithms enhances decision-making processes for forest managers and stakeholders, promoting scientifically sound strategies for climate adaptation. This study underscores the transformative potential of cutting-edge 3D modeling technologies in advancing forest conservation and management practices.
ISSN:1470-160X
DOI:10.1016/j.ecolind.2025.113780