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

通信作者：Sun, XM[1]

机构：[1]Chinese Acad Forestry, Res Inst Forestry, State Key Lab Tree Genet & Breeding, Key Lab Tree Breeding & Cultivat State Forestry, Beijing 100091, Peoples R China;[2]Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess Pl, Yangling 712100, Shaanxi, Peoples R China;[3]Zhejiang Univ Finance & Econ, Inst Land & Urban Rural Dev, Hangzhou 310018, Peoples R 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);WOS:【SCI-EXPANDED(收录号:WOS:001523624400001)】；

基金：This work is supported by the Fundamental Research Funds of CAF (CAFYBB2023QA001), National Natural Science Foundation of China (General Program) (32371862), State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A & F University, Yangling 712100 Shaanxi, P.R. China (F2010121002-202429), The National Key Research and Development Program of China (2023YFD2200801). We appreciate the comments and suggestions given by all anonymous reviewers of this study.

语种：英文

外文关键词：3D visualization; Point cloud data; LiDAR and UAVs; Intelligent recognition algorithm; Carbon sequestration; Photosynthetic efficiency

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 decisionmaking 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.