干旱区生态环境知识资源中心(Arid): Precise vegetation restoration in arid regions based on potential natural vegetation and potential normalized difference vegetation index

Arid

DOI	10.1111/rec.13967
	Precise vegetation restoration in arid regions based on potential natural vegetation and potential normalized difference vegetation index
	Qu, Jia; Liu, Qi; Gui, Dongwei; Feng, Xinlong; Wang, Haolin; Zhao, Jianping; Wang, Guangyan; Wei, Guanghui
通讯作者	Feng, XL
来源期刊	RESTORATION ECOLOGY
ISSN	1061-2971
EISSN	1526-100X
出版年	2024
卷号	32 期号:2
英文摘要	Precise vegetation restoration is critical in drylands, as some inappropriate restoration attempts have even increased water scarcity and degradation in afforestation areas. Potential natural vegetation (PNV) is widely used to provide a reference for the appropriate location and vegetation type of restoration programs while the appropriate restored areas remain unknown. Therefore, we proposed a PNV-potential normalized difference vegetation index (PNDVI) coupling framework based on multiple machine learning (ML) algorithms for precise dryland vegetation restoration. Taking the lower Tarim River Basin (LTRB) with a total area of 1,182 km(2) as a case study, its present suitable restoration locations, area, and appropriate planting species were quantitatively estimated. The results showed that the model developed by incorporating PNDVI into PNV with easily measurable and available data such as temperature and soil properties can accurately identify dryland restoration patterns. In LTRB, the potentially suitable habitats of trees and grass are closer to the riverbank, while shrubby habitats are further away from the course, covering 1.88, 2.96, and 25.12 km(2), respectively. There is still enormous land potential for further expansion of the current trees and grass in the LTRB, with 2.56 and 1.54% of existing land supposed to be trees and grass, respectively. This study's novel aspect is combining PNV and PNDVI to quantify and estimate precise restoration patterns through multiple ML algorithms. The model developed here can be used to evaluate the suitable reforestation locations, area, and vegetation types in drylands and to provide a basis for precise vegetation restoration.
英文关键词	arid region ecosystem deterioration machine learning potential natural vegetation potential normalized difference vegetation index reforestation
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001023593100001
WOS关键词	LOWER TARIM RIVER ; LOWER REACHES ; WATER DIVERSION ; GROUNDWATER ; RIPARIAN ; CLASSIFICATION ; DISTRIBUTIONS ; AVAILABILITY ; FLOODPLAIN ; XINJIANG
WOS类目	Ecology
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/405342
推荐引用方式 GB/T 7714	Qu, Jia,Liu, Qi,Gui, Dongwei,et al. Precise vegetation restoration in arid regions based on potential natural vegetation and potential normalized difference vegetation index[J],2024,32(2).
APA	Qu, Jia.,Liu, Qi.,Gui, Dongwei.,Feng, Xinlong.,Wang, Haolin.,...&Wei, Guanghui.(2024).Precise vegetation restoration in arid regions based on potential natural vegetation and potential normalized difference vegetation index.RESTORATION ECOLOGY,32(2).
MLA	Qu, Jia,et al."Precise vegetation restoration in arid regions based on potential natural vegetation and potential normalized difference vegetation index".RESTORATION ECOLOGY 32.2(2024).