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Cross-classes domain inference with network sampling for natural resource inventory

Zhengyang Hou Ronald E.McRoberts Chunyu Zhang G?ran St?hl Xiuhai Zhao Xuejun Wang Bo Li Qing Xu

森林生态系统(英文版)2022,Vol.9Issue(3):311-322,12.
森林生态系统(英文版)2022,Vol.9Issue(3):311-322,12.

Cross-classes domain inference with network sampling for natural resource inventory

Cross-classes domain inference with network sampling for natural resource inventory

Zhengyang Hou 1Ronald E.McRoberts 2Chunyu Zhang 1G?ran St?hl 3Xiuhai Zhao 1Xuejun Wang 4Bo Li 5Qing Xu6

作者信息

  • 1. The Key Laboratory for Silviculture and Conservation of Ministry of Education,Beijing Forestry University,Beijing,China
  • 2. Department of Forest Resources,University of Minnesota,Saint Paul,MN,United States
  • 3. Department of Forest Resource Management,Swedish University of Agricultural Sciences,Ume?,Sweden
  • 4. Office of the National Forestry and Grassland Administrations Forest Resources Supervision Commissioner in Beijing,Beijing,China
  • 5. Department of Statistics,University of Illinois at Urbana-Champaign,Champaign,IL,United States
  • 6. Key Laboratory on the Science and Technology of Bamboo and Rattan,International Centre for Bamboo and Rattan,Beijing,China
  • 折叠

摘要

关键词

Cross-classes domain estimation/Design-based inference/Network sampling/Generalized systematic adaptive cluster sampling/Forest inventory

Key words

Cross-classes domain estimation/Design-based inference/Network sampling/Generalized systematic adaptive cluster sampling/Forest inventory

引用本文复制引用

Zhengyang Hou,Ronald E.McRoberts,Chunyu Zhang,G?ran St?hl,Xiuhai Zhao,Xuejun Wang,Bo Li,Qing Xu..Cross-classes domain inference with network sampling for natural resource inventory[J].森林生态系统(英文版),2022,9(3):311-322,12.

基金项目

This work was supported by(1)the Fundamental Research Funds for the Central Universities(Grant No.2021ZY04),(2)the National Natural Science Foundation of China(Grant No.32001252),and(3)the International Center for Bamboo and Rattan(Grant No.1632020029). (1)

森林生态系统(英文版)

OACSCDCSTPCDSCI

2095-6355

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