干旱区生态环境知识资源中心(Arid): Monitoring the Spatiotemporal Dynamics of Aeolian Desertification Using Google Earth Engine

Arid

DOI	10.3390/rs13091730
	Monitoring the Spatiotemporal Dynamics of Aeolian Desertification Using Google Earth Engine
	Chen, Ang; Yang, Xiuchun; Xu, Bin; Jin, Yunxiang; Guo, Jian; Xing, Xiaoyu; Yang, Dong; Wang, Ping; Zhu, Libo
通讯作者	Yang, XC (corresponding author), Beijing Forestry Univ, Sch Grassland Sci, Beijing 100081, Peoples R China.
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2021
卷号	13 期号:9
英文摘要	Northern China has been long threatened by aeolian desertification. In recent years, all levels of the Chinese government have performed a series of ecological protection and sand control projects. To grasp the implementation effects of these projects and adjust policies in time, it is necessary to understand the process of aeolian desertification quickly and accurately. Remote sensing technologies play an irreplaceable role in aeolian desertification monitoring. In this study, the Zhenglan Banner, which is in the hinterland of the Hunshandake Sandy Land, was considered as the research area. Based on unmanned aerial vehicle (UAV) images, ground survey data, and Landsat images called in Google Earth Engine (GEE), the aeolian desertified land (ADL) in 2000, 2004, 2010, 2015, and 2019 was extracted using spectral mixture analysis. A desertification index (DI) was constructed to evaluate the spatial and temporal dynamics of the ADL in the Zhenglan Banner. Finally, a residual analysis explored the driving forces of aeolian desertification. The results showed that (1) the ADL area in the Zhenglan Banner has been trending downwards over the past 20 years but rebounded from 2004 to 2010; (2) over the past 20 years, the area of slightly, moderately, and severely desertified land has decreased at annual rates of 0.4%, 2.7%, and 3.4%, respectively; (3) human activities had significantly positive and negative impacts on the aeolian desertification trend for 20.0% and 21.0% of the study area, respectively, but not for the rest. This paper explored new techniques for rapid aeolian desertification monitoring and is of great significance for controlling and managing aeolian desertification in this region.
英文关键词	aeolian desertification Google Earth Engine (GEE) unmanned aerial vehicle (UAV) human activity climate change
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000650740100001
WOS关键词	HORQIN SANDY LAND ; REMOTE ; CHINA ; AREA ; PLATEAU ; IMAGES ; INDEX ; UAV ; DEGRADATION ; SYSTEMS
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构	北京师范大学 ; 北京林业大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/351521
作者单位	[Chen, Ang; Yang, Xiuchun; Xu, Bin; Wang, Ping] Beijing Forestry Univ, Sch Grassland Sci, Beijing 100081, Peoples R China; [Xu, Bin; Jin, Yunxiang; Xing, Xiaoyu; Yang, Dong] Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Minist Agr & Rural Affairs, Key Lab Agriinformat, Beijing 100081, Peoples R China; [Guo, Jian] Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China; [Guo, Jian] Beijing Normal Univ, Fac Geog Sci, Beijing Key Lab Remote Sensing Environm & Digital, Beijing 100875, Peoples R China; [Zhu, Libo] Hulunbuir Inst Anim Husb Sci, Hulunbuir 021008, Peoples R China
推荐引用方式 GB/T 7714	Chen, Ang,Yang, Xiuchun,Xu, Bin,et al. Monitoring the Spatiotemporal Dynamics of Aeolian Desertification Using Google Earth Engine[J]. 北京师范大学, 北京林业大学,2021,13(9).
APA	Chen, Ang.,Yang, Xiuchun.,Xu, Bin.,Jin, Yunxiang.,Guo, Jian.,...&Zhu, Libo.(2021).Monitoring the Spatiotemporal Dynamics of Aeolian Desertification Using Google Earth Engine.REMOTE SENSING,13(9).
MLA	Chen, Ang,et al."Monitoring the Spatiotemporal Dynamics of Aeolian Desertification Using Google Earth Engine".REMOTE SENSING 13.9(2021).