气候变化领域集成服务门户(CCPortal): Changes in the Fine Composition of Global Forests from 2001 to 2020

CCPortal

DOI	10.34133/remotesensing.0119
	Changes in the Fine Composition of Global Forests from 2001 to 2020
	Xu, Hongtao; He, Bin; Guo, Lanlan; Yan, Xing; Dong, Jinwei; Yuan, Wenping; Hao, Xingming; Lv, Aifeng; He, Xiangqi; Li, Tiewei
发表日期	2024
EISSN	2694-1589
起始页码	4
卷号	4
英文摘要	Knowledge of forest management types is key to sustainable forest restoration practices, forest biomass assessment, and carbon accounting. However, there are no available global forest-management maps because of the spectral similarity of different forest management types. As such, we applied random forest and change detection algorithms to generate annual maps of 6 forest management types at a spatial resolution of 250 m from 2001 to 2020 including naturally regenerated forest (unmanaged and managed), planted forest (rotation of >15 years and <= 15 years), oil palm plantation, and agroforestry. In general, validation results on a point scale show that the overall accuracy is 86.82% +/- 9.14%, indicating that our annual maps accurately represent global spatiotemporal variations in forest management types. Furthermore, we estimated the annual biomass carbon stock of different forest management types. The net expanded areas of planted forest, oil palm plantation, and agroforestry offset 59.56% of the loss of forest area and 77.13% of the loss of biomass carbon stock due to the decrease in the naturally regenerated forest. The decrease of managed natural regeneration forests, the expansion of planted forests with a rotation period of more than 15 years, and agroforestry resulted from reforestation practices, while the expansion of planted forests with a rotation period of less than 15 years and oil palm plantations resulted from the removal of part of agroforestry. Moreover, the expansion of planted forests with a rotation of less than 15 years (72.73%) dominates the global expansion of planted forests, and China has contributed 42.20% of this expansion. Our results are beneficial for nature solution-based climate change mitigation.
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:001235960000001
来源期刊	JOURNAL OF REMOTE SENSING
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/299780
作者单位	Beijing Normal University; Beijing Normal University; Chinese Academy of Sciences; Institute of Geographic Sciences & Natural Resources Research, CAS; Peking University; Chinese Academy of Sciences; Xinjiang Institute of Ecology & Geography, CAS; Chinese Academy of Sciences; Institute of Geographic Sciences & Natural Resources Research, CAS
推荐引用方式 GB/T 7714	Xu, Hongtao,He, Bin,Guo, Lanlan,et al. Changes in the Fine Composition of Global Forests from 2001 to 2020[J],2024,4.
APA	Xu, Hongtao.,He, Bin.,Guo, Lanlan.,Yan, Xing.,Dong, Jinwei.,...&Li, Tiewei.(2024).Changes in the Fine Composition of Global Forests from 2001 to 2020.JOURNAL OF REMOTE SENSING,4.
MLA	Xu, Hongtao,et al."Changes in the Fine Composition of Global Forests from 2001 to 2020".JOURNAL OF REMOTE SENSING 4(2024).