文献类型：期刊文献

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

作者：Wu, Chunyan[1,2] Cheng, Min[3] Chen, Dongsheng[1] Zhang, Shougong[1] Sun, Xiaomei[1]

第一作者：吴春燕;Wu, Chunyan

机构：[1] State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China; [2] State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Shaanxi, Yangling, 712100, China; [3] Institute of Land and Urban-Rural Development, Zhejiang University of Finance and Economics, Hangzhou, 310018, China

年份：2025

卷号：178

外文期刊名：Ecological Indicators

收录：EI(收录号：20252718701714);Scopus(收录号：2-s2.0-105009359989)

语种：英文

外文关键词：3D reconstruction - Carbon - Carbon cycle - Carbon Economy - Carbon sequestration - Conservation - Data visualization - Decision making - Drought - Ecosystems - Forest ecology - Forestry - Optimization - Photosynthesis - Physiological models - Three dimensional computer graphics - Trees (mathematics) - Visualization

摘要：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. ? 2025 The Authors