干旱区生态环境知识资源中心(Arid): Spatio-Temporal Variation Analysis of Soil Salinization in the Ougan-Kuqa River Oasis of China

Arid

DOI	10.3390/su16072706
	Spatio-Temporal Variation Analysis of Soil Salinization in the Ougan-Kuqa River Oasis of China
	Du, Danying; He, Baozhong; Luo, Xuefeng; Ma, Shilong; Song, Yaning; Yang, Wen
通讯作者	He, BZ
来源期刊	SUSTAINABILITY
EISSN	2071-1050
出版年	2024
卷号	16 期号:7
英文摘要	In order to investigate the mechanism of environmental factors in soil salinization, this study focused on analyzing the temporal-spatial variation of soil salinity in the Ogan-Kuqa River Oasis in Xinjiang, China. The research aimed to predict soil salinity using a combination of satellite data, environmental covariates, and advanced modeling techniques. Firstly, Boruta and ReliefF algorithms were employed to select variables that significantly affect soil salinity from the Sentinel-2 satellite data and environmental covariates. Subsequently, a soil salinity inversion model was established using three advanced strategies: comprehensive variable analysis, a Boruta-based variable selection algorithm, and a ReliefF-based variable selection algorithm. Each strategy was modeled using a Light Gradient Boosting Machine (LightGBM), an Extreme Learning Machine (ELM), and a Support Vector Machine (SVM). Finally, the Boruta-LightGBM strategy was proven to be the most effective in predicting soil electrical conductivity (EC), with a coefficient of determination (R2) of 0.72 and a Root Mean Square Error (RMSE) of 12.49 ds/m. The experimental results show that the red-edge band index is the foremost variable in predicting soil salinity, succeeded by the salinity index and soil attribute data, while the topographic index has the least influence, which further demonstrates that proper variable selection could significantly improve model functionality and predictive precision. Furthermore, the Multiscale Geographically Weighted Regression (MGWR) model was utilized to reveal the influence and temporal-temporal-spatial heterogeneity of environmental factors such as soil organic carbon (SOC), precipitation (PRE), pH value, and temperature (TEM) on soil EC. This research offers not just a viable methodological framework for monitoring soil salinization but also new perspectives on the environmental drivers of soil salinity changes, which have implications for sustainable land management and provide valuable information for decision-making in soil salinity control and mitigation efforts.
英文关键词	variable selection algorithm soil salinity inversion model multiscale geographically weighted regression soil salinization temporal-spatial variation analysis
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E ; SSCI
WOS记录号	WOS:001200925600001
WOS关键词	EXTREME LEARNING-MACHINE ; REGRESSION ; SALINITY ; REGION
WOS类目	Green & Sustainable Science & Technology ; Environmental Sciences ; Environmental Studies
WOS研究方向	Science & Technology - Other Topics ; Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/405724
推荐引用方式 GB/T 7714	Du, Danying,He, Baozhong,Luo, Xuefeng,et al. Spatio-Temporal Variation Analysis of Soil Salinization in the Ougan-Kuqa River Oasis of China[J],2024,16(7).
APA	Du, Danying,He, Baozhong,Luo, Xuefeng,Ma, Shilong,Song, Yaning,&Yang, Wen.(2024).Spatio-Temporal Variation Analysis of Soil Salinization in the Ougan-Kuqa River Oasis of China.SUSTAINABILITY,16(7).
MLA	Du, Danying,et al."Spatio-Temporal Variation Analysis of Soil Salinization in the Ougan-Kuqa River Oasis of China".SUSTAINABILITY 16.7(2024).