首页|期刊导航|森林生态系统(英文版)|Leveraging missing-data remote sensing for forest inventory

Leveraging missing-data remote sensing for forest inventoryOA

Leveraging missing-data remote sensing for forest inventory

Qiling Wang;Qing Xu;Liuyuan Huang;Weisheng Zeng;Bo Li;Timo Tokola;Ronald E.McRoberts;Zhengyang Hou

The Key Laboratory for Silviculture and Conservation of Ministry of Education,Beijing Forestry University,Beijing 100083,China||Ecological Observation and Research Station of Heilongjiang Sanjiang Plain Wetlands,National Forestry and Grassland Administration,Shuangyashan 155600,ChinaKey Laboratory of National Forestry and Grassland Administration/Beijing for Bamboo & Rattan Science and Technology,International Center for Bamboo and Rattan,Beijing 100102,ChinaThe Key Laboratory for Silviculture and Conservation of Ministry of Education,Beijing Forestry University,Beijing 100083,China||Ecological Observation and Research Station of Heilongjiang Sanjiang Plain Wetlands,National Forestry and Grassland Administration,Shuangyashan 155600,ChinaAcademy of Forest and Grassland Inventory and Planning,National Forestry and Grassland Administration,Beijing 100714,ChinaDepartment of Statistics and Data Science,Washington University in St.Louis,St.Louis,MO 63130,USASchool of Forest Sciences,University of Eastern Finland,Joensuu FIN-80100,FinlandDepartment of Forest Resources,University of Minnesota,St.Paul,MN 55101,USAThe Key Laboratory for Silviculture and Conservation of Ministry of Education,Beijing Forestry University,Beijing 100083,China||Ecological Observation and Research Station of Heilongjiang Sanjiang Plain Wetlands,National Forestry and Grassland Administration,Shuangyashan 155600,China

Forest managementMissing valuesSurvey samplingModel-based inferenceUncertainty assessment

Forest managementMissing valuesSurvey samplingModel-based inferenceUncertainty assessment

《森林生态系统(英文版)》 2026 (1)

95-108,14

This work was supported by the National Key R&D Program of China(No.2023YFF1304002-05),the National Social Science Fund of China(No.22BTJ005),and the National Natural Science Foundation of China(No.32572049).

10.1016/j.fecs.2025.100399

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