干旱区生态环境知识资源中心(Arid): A new global land productivity dynamic product based on the consistency of various vegetation biophysical indicators

Arid

DOI	10.1080/20964471.2021.2018789
	A new global land productivity dynamic product based on the consistency of various vegetation biophysical indicators
	Cui, Yuran; Li, Xiaosong
通讯作者	Li, XS (corresponding author)，Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China.
来源期刊	BIG EARTH DATA
ISSN	2096-4471
EISSN	2574-5417
出版年	2022-01
英文摘要	Changes in land productivity have been endorsed by the Inter Agency Expert Group on Sustainable Development Goals (IAEG-SDGs) as key indicators for monitoring SDG 15.3.1. Multiple vegetation parameters from optical remote sensing techniques have been widely utilized across different land productivity decline processes and scales. However, there is no consensus on indicator selection and their effectiveness at representing land productivity declining at different scales. This study proposes a fusion framework that incorporates the trends and consistencies within the four commonly used remote sensing-based vegetation indicators. We analyzed the differences among the four vegetation parameters in different land cover and climate zones, finally producing a new global land productivity dynamics (LPD) product with confidence level degrees. The LPD classes indicated by the four vegetation indicators(VIs) showed that all three levels (low, medium, and high confidence) of increasing area account for 23.99% of the global vegetated area and declining area account for 7.00%. The Increase high-confidence(HC) area accounted for 2.77% of the total area, and the Decline-HC accounted for 0.35% of the total area. This study demonstrates the accuracy of the high-confidence (HC) area for the evaluation of land productivity decline and increase. The forest landcover type and humid climate zone had the largest increasing and declining area but had the lowest high-confidence proportion. The data product provides an important and optional reference for the assessment of SDG 15.3.1 at global and regional scales according to the specific application target. The Global Land Productivity Dynamic dataset is available in the Science Data Bank at http://www.doi.org/10.11922/sciencedb.j00076.00084.
英文关键词	Sustainable development goals SDG 15.3.1 vegetation parameters confidence level google Earth engine
类型	Article ; Data Paper ; Early Access
语种	英语
开放获取类型	gold
收录类别	ESCI
WOS记录号	WOS:000746754700001
WOS关键词	NET PRIMARY PRODUCTION ; KENDALL TREND TEST ; LOESS PLATEAU ; ECO-ENVIRONMENT ; CENTRAL-ASIA ; CONSERVATION ; DEGRADATION ; GROSS ; DESERTIFICATION ; PATTERNS
WOS类目	Computer Science, Information Systems ; Geosciences, Multidisciplinary ; Remote Sensing
WOS研究方向	Computer Science ; Geology ; Remote Sensing
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/377205
作者单位	[Cui, Yuran; Li, Xiaosong] Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing, Peoples R China; [Cui, Yuran; Li, Xiaosong] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Cui, Yuran,Li, Xiaosong. A new global land productivity dynamic product based on the consistency of various vegetation biophysical indicators[J],2022.
APA	Cui, Yuran,&Li, Xiaosong.(2022).A new global land productivity dynamic product based on the consistency of various vegetation biophysical indicators.BIG EARTH DATA.
MLA	Cui, Yuran,et al."A new global land productivity dynamic product based on the consistency of various vegetation biophysical indicators".BIG EARTH DATA (2022).