干旱区生态环境知识资源中心(Arid): Remote sensing-based land surface change identification and prediction in the Aral Sea bed, Central Asia

Arid

DOI	10.1007/s13762-018-1801-0
	Remote sensing-based land surface change identification and prediction in the Aral Sea bed, Central Asia
	Shen, H.1,2,3; Abuduwaili, J.1,2,3; Ma, L.1,2; Samat, A.1,2
通讯作者	Abuduwaili, J.
来源期刊	INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY
ISSN	1735-1472
EISSN	1735-2630
出版年	2019
卷号	16 期号:4 页码:2031-2046
英文摘要	The human-induced desiccation of the Aral Sea has generated large amounts of salt dust and has been posing a great threat to local ecological environment and human health. Monitoring its land cover changes is essential to obtaining information about the desertification process and dynamics of potential salt/sand dust source. To this end, long-term Landsat imagery was applied for the land use/cover change analysis based on support vector machine approach. The land cover distribution of the study area for 1977, 1987, 1996, 2006 and 2015 was mapped. In addition, the Markov-cellular automata integrated approach was used to predict the land cover change in 2015 and project changes in 2025 by extrapolating current trends. The classification results revealed that water surface of the Aral Sea shrunk by more than 66%, leading to the dramatic expanding of the salt soil and bare area. Change detection analysis indicated a serious land degradation trend as well as a major land cover evolution mode in the Aral Kum that could predict shifts in dust composition. The Markov-cellular automata technique was successful in predicting land cover distribution in 2015, and the projected land cover for 2025 revealed more desertification of the landscape with potential expansion in the salt soils and bare area. It is worth noting that the vegetation cover of the region represented an obvious increase in recent years that may be a good signal of ecological recovery.
英文关键词	Remote sensing Aral Sea Markov-cellular automata Land use and land cover Support vector machine
类型	Article
语种	英语
国家	Peoples R China
收录类别	SCI-E
WOS记录号	WOS:000465479000018
WOS关键词	COVER CHANGE DETECTION ; DUST STORMS ; CLASSIFICATION ; DYNAMICS ; AREA ; EXPOSURE ; SPACE
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
来源机构	中国科学院新疆生态与地理研究所
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/216439
作者单位	1.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, 818 Beijing South Rd, Urumqi, Xinjiang, Peoples R China; 2.Chinese Acad Sci, Res Ctr Ecol & Environm Cent Asia, Urumqi, Peoples R China; 3.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Shen, H.,Abuduwaili, J.,Ma, L.,et al. Remote sensing-based land surface change identification and prediction in the Aral Sea bed, Central Asia[J]. 中国科学院新疆生态与地理研究所,2019,16(4):2031-2046.
APA	Shen, H.,Abuduwaili, J.,Ma, L.,&Samat, A..(2019).Remote sensing-based land surface change identification and prediction in the Aral Sea bed, Central Asia.INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY,16(4),2031-2046.
MLA	Shen, H.,et al."Remote sensing-based land surface change identification and prediction in the Aral Sea bed, Central Asia".INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY 16.4(2019):2031-2046.