欢迎访问林草资源研究

Method and Enlightenment of 2020 Global Forest Resources Assessment Remote Sensing Survey

  • Wei WANG ,
  • Jing YANG ,
  • Xianlian GAO ,
  • Weisheng ZENG
Expand
  • 1. Academy of Inventory and Planning,National Forestry and Grassland Administration,Beijing 100714,China
    2. Department of Forest Resources Management,National Forestry and Grassland Administration,Beijing 100714,China

Received date: 2021-10-29

  Revised date: 2021-11-15

  Online published: 2022-01-12

Abstract

From 2019 to 2020,China participated in the 2020 Global Forest Resources Assessment Remote Sensing Survey (FRA2020 RSS) organized by the United Nations Food and Agriculture Organization(FAO),and completed the tasks within China. This article described the development process of the global forest resources assessment,introduced the system framework and technical methods of FRA2020 RSS,and analyzed the reflection and enlightenment of FRA2020 RSS on the construction of an integrated forest resources monitoring system in China.

Cite this article

Wei WANG , Jing YANG , Xianlian GAO , Weisheng ZENG . Method and Enlightenment of 2020 Global Forest Resources Assessment Remote Sensing Survey[J]. Forest and Grassland Resources Research, 2021 , 0(6) : 1 -5 . DOI: 10.13466/j.cnki.lyzygl.2021.06.001

References

[1] D'Annunzio R, Lindquist E, Macdicken K. Global forest land-use change from 1990 to 2010:an update to a global remote sensing survey of forests[M]. Rome:Food and Agriculture Organization of the United Nations, 2014.
[2] 陈雪峰, 黄国胜, 夏朝宗, 等. 全球森林资源评估方法与启示[J]. 林业资源管理, 2005(4):24-29.
[3] Nesha M K, Herold M, De Sy V, et al. An assessment of data sources,data quality and changes in national forest monitoring capacities in the Global Forest Resources Assessment 2005-2020[J]. Environmental Research Letters, 2021, 16(5).DOI: 10.1088/1748-9326/abd81b.
[4] FRA2020 Remote Sensing Survegs Course[EB/OL].[2021-11-16]. https://rise.articulate.com/share/h2g6UBw1gfpVosaZMI9_TAhRmheGORnn#/ , 2020-10-01.
[5] 张敏, 夏朝宗, 黄国胜, 等. 2010年全球森林资源评估特点与启示[J]. 林业资源管理, 2011(1):1-6.
[6] Tyukavina A, Hansen M C, Potapov P, et al. Congo Basin forest loss dominated by increasing smallholder clearing[J]. Science Advances, 2018, 4(11).DOI: 10.1126/sciadv.aat2993.
[7] Olofsson P, Foody G M, Herold M, et al. Good practices for estimating area and assessing accuracy of land change[J]. Remote Sensing of Environment, 2014, 148:42-57.
[8] FAO. Global Forest Resources Assessment Report China[M]. Rome:Food and Agriculture Organization of the United Nations, 2020.
[9] 王雪军, 马炜, 黄国胜, 等. 基于遥感大样地抽样调查的森林面积监测[J]. 北京林业大学报, 2015, 37(11):1-9.
[10] 黄国胜, 曾伟生, 党永峰, 等. 全国森林资源宏观监测抽样设计改进方案探索[J]. 林业资源管理, 2017(1):7-11.
[11] 曾伟生, 黄国胜, 党永峰, 等. 全国森林资源宏观监测的抽样设计与估计方法探索[J]. 林业资源管理, 2016(3):1-6.
Outlines

/