干旱区生态环境知识资源中心(Arid): Assessing the Long-Term Evolution of Abandoned Salinized Farmland via Temporal Remote Sensing Data

Arid

DOI	10.3390/rs13204057
	Assessing the Long-Term Evolution of Abandoned Salinized Farmland via Temporal Remote Sensing Data
	Zhao, Liya; Yang, Qi; Zhao, Qiang; Wu, Jingwei
通讯作者	Wu, JW (corresponding author), Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Peoples R China.
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2021
卷号	13 期号:20
英文摘要	Salinization in arid or semiarid regions with water logging limits cropland yield, threatening food security. The highest level of farmland salinization, that is, abandoned salinized farmland, is a tradeoff between inadequate drainage facilities and sustainable farming. The evolution of abandoned salinized farmlands is closely related to the development of cropping systems. However, detecting abandoned salinized farmland using time-series remote sensing data has not been investigated well by previous studies. In this study, a novel approach was proposed to detect the dynamics of abandoned salinized farmland using time-series multispectral and thermal imagery. Thirty-two years of temporal Landsat imagery (from 1988 to 2019) was used to assess the evolution of salinization in Hetao, a two-thousand-year-old irrigation district in northern China. As intermediate variables of the proposed method, the crop-specific planting area was retrieved via its unique temporal vegetation index (VI) pattern, in which the shape-model-fitting technology and the K-means cluster algorithm were used. The desert area was stripped from the clustered non-vegetative area using its distinct features in the thermal band. Subsequently, the abandoned salinized farmland was distinguished from the urban area by the threshold-based saline index (SI). In addition, a regression model between electrical conductance (EC) and SI was established, and the spatial saline degree was evaluated by the SI map in uncropped and unfrozen seasons. The results show that the cropland has constantly been expanding in recent decades (from 4.7 x 10(5) ha to 7.1 x 10(5) ha), while the planting area of maize and sunflower has grown and the area of wheat has decreased. Significant desalinization progress was observed in Hetao, where both the area of salt-affected land (salt-free area increased approximately 4 x 10(5) ha) and the abandoned salinized farmland decreased (reduced from 0.45 x 10(5) ha to 0.19 x 10(5) ha). This could be mainly attributed to three reasons: the popularization of water-saving irrigation technology, the construction of artificial drainage facilities, and a shift in cropping patterns. The decrease in irrigation and the increase in drainage have deepened the groundwater table in Hetao, which weakens the salt collection capacity of the abandoned salinized farmland. The results demonstrate the promising possibility of reutilizing abandoned salinized farmland via a leaching campaign where the groundwater table is sufficiently deep to stop salinization.
英文关键词	salinization abandoned salinized farmland remote sensing Hetao Irrigation District
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:000713815700001
WOS关键词	LAND-COVER CLASSIFICATION ; SOIL-SALINITY ; MODIS ; DESALINATION ; DRAINAGE ; YIELD ; WATER
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
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/368338
作者单位	[Zhao, Liya; Yang, Qi; Zhao, Qiang; Wu, Jingwei] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Liya,Yang, Qi,Zhao, Qiang,et al. Assessing the Long-Term Evolution of Abandoned Salinized Farmland via Temporal Remote Sensing Data[J],2021,13(20).
APA	Zhao, Liya,Yang, Qi,Zhao, Qiang,&Wu, Jingwei.(2021).Assessing the Long-Term Evolution of Abandoned Salinized Farmland via Temporal Remote Sensing Data.REMOTE SENSING,13(20).
MLA	Zhao, Liya,et al."Assessing the Long-Term Evolution of Abandoned Salinized Farmland via Temporal Remote Sensing Data".REMOTE SENSING 13.20(2021).