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Using machine learning algorithms to estimate stand volume growth of Larix and Quercus forests based on national-scale Forest Inventory data in China

Huiling Tian Changfu Liu Wenfa Xiao Jianhua Zhu Xiao He Xinyun Chen Zunji Jian Chenyu Li Qiangxin Ou Qi Li Guosheng Huang

森林生态系统（英文版）2022，Vol.9Issue(3)：396-406,11.
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森林生态系统（英文版）2022，Vol.9Issue(3)：396-406,11.

Using machine learning algorithms to estimate stand volume growth of Larix and Quercus forests based on national-scale Forest Inventory data in China

Using machine learning algorithms to estimate stand volume growth of Larix and Quercus forests based on national-scale Forest Inventory data in China

Huiling Tian 1Changfu Liu 1Wenfa Xiao 2Jianhua Zhu 1Xiao He 2Xinyun Chen 1Zunji Jian 2Chenyu Li 3Qiangxin Ou 2Qi Li 1Guosheng Huang1

作者信息

  • 1. Ecology and Nature Conservation Institute,Chinese Academy of Forestry,Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration,Beijing,100091,China
  • 2. Co-Innovation Center for Sustainable Forestry in Southern China,Nanjing Forestry University,Nanjing,210037,China
  • 3. Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Key Laboratory of Forest Management and Growth Modeling,National Forestry and Grassland Administration,Beijing 100091,China
  • 折叠

摘要

关键词

Stand volume growth/Stand origin/Plant functional type/National forest inventory data/Random forest algorithms

Key words

Stand volume growth/Stand origin/Plant functional type/National forest inventory data/Random forest algorithms

引用本文复制引用

Huiling Tian,Changfu Liu,Wenfa Xiao,Jianhua Zhu,Xiao He,Xinyun Chen,Zunji Jian,Chenyu Li,Qiangxin Ou,Qi Li,Guosheng Huang..Using machine learning algorithms to estimate stand volume growth of Larix and Quercus forests based on national-scale Forest Inventory data in China[J].森林生态系统（英文版）,2022,9(3):396-406,11.

基金项目

This work was supported by the Major Program of the National Natural Science Foundation of China(No.32192434),the Fundamental Research Funds of Chinese Academy of Forestry(No.CAFYBB2019ZD001)and the National Key Research and Development Program of China(2016YFD060020602).We thank our colleagues,Yanyan Ni,Yu Tian,for their assistance in providing relevant factor data and data sorting.We thank Shuyi Guo,Rui Wang,staff of the Academy of Forest Inventory and Planning,National Forestry and Grassland Admin-istration,for help with data provision.We also thank the Zigui Forest Ecosystem Research Station for their help. （No.32192434）

森林生态系统（英文版）

OACSCDCSTPCDSCI

2095-6355

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