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DOI	10.1016/j.gloplacha.2023.104310
	Global soil moisture trend analysis using microwave remote sensing data and an automated polynomial-based algorithm
	Mohseni, Farzane; Jamali, Sadegh; Ghorbanian, Arsalan; Mokhtarzade, Mehdi
通讯作者	Jamali, S
来源期刊	GLOBAL AND PLANETARY CHANGE
ISSN	0921-8181
EISSN	1872-6364
出版年	2023
卷号	231
英文摘要	The change in Soil Moisture Content (SMC) is one of the most crucial variables for regulating and analyzing basic hydrological processes, including runoff, evaporation, carbon and energy cycles, infiltration of water resources, droughts and floods, and desertification. This study aimed to detect and map the global SMC change using microwave remote sensing observations. Monthly SMC data from the Soil Moisture Ocean Salinity (SMOS) with a spatial resolution of 25 km were used to assess the SMC change from January 2010 to December 2021. Various trend patterns, including linear, quadratic, cubic, and concealed, were examined by applying a parametric polynomial fitting-based algorithm (Polytrend). In particular, approximately 16.93% of global land is subjected to soil moisture dynamics, of which 8.33% has become drier and 8.60% has become wetter. Both linear and nonlinear trends were observed in the global land areas that have experienced statistically significant changes. The concealed and linear trends were however the dominant trend patterns globally. The obtained trend results were further investigated using a well-known non-parametric trend test, Mann-Kendall, which showed 93.20% agreement, demonstrating the robustness and reliability of the observed trends.
英文关键词	Global Soil Moisture L-band radiometers SMOS Polytrend algorithm Time series analysis Trend analysis
类型	Article
语种	英语
开放获取类型	hybrid
收录类别	SCI-E
WOS记录号	WOS:001132092900001
WOS关键词	SMOS ; TEMPERATURE ; PERFORMANCE ; VALIDATION ; RETRIEVAL ; PRODUCTS ; RAINFALL ; SPACE ; MODEL ; BASIN
WOS类目	Geography, Physical ; Geosciences, Multidisciplinary
WOS研究方向	Physical Geography ; Geology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/396770
推荐引用方式 GB/T 7714	Mohseni, Farzane,Jamali, Sadegh,Ghorbanian, Arsalan,et al. Global soil moisture trend analysis using microwave remote sensing data and an automated polynomial-based algorithm[J],2023,231.
APA	Mohseni, Farzane,Jamali, Sadegh,Ghorbanian, Arsalan,&Mokhtarzade, Mehdi.(2023).Global soil moisture trend analysis using microwave remote sensing data and an automated polynomial-based algorithm.GLOBAL AND PLANETARY CHANGE,231.
MLA	Mohseni, Farzane,et al."Global soil moisture trend analysis using microwave remote sensing data and an automated polynomial-based algorithm".GLOBAL AND PLANETARY CHANGE 231(2023).