干旱区生态环境知识资源中心(Arid): Modeling and Mapping of Soil Salinity and Alkalinity Using Remote Sensing Data and Topographic Factors: a Case Study in Iran

Arid

DOI	10.1007/s10666-022-09823-8
	Modeling and Mapping of Soil Salinity and Alkalinity Using Remote Sensing Data and Topographic Factors: a Case Study in Iran
	Shahrayini, Elham; Noroozi, Ali Akbar
通讯作者	Shahrayini, E
来源期刊	ENVIRONMENTAL MODELING & ASSESSMENT
ISSN	1420-2026
EISSN	1573-2967
出版年	2022
卷号	27 期号:5 页码:901-913
英文摘要	Soil salinity and alkalinity seriously threaten crop production, soil productivity, and sustainable agriculture, especially in arid and semi-arid areas, leading to land degradation. Therefore, the spatial distribution of these parameters is really important for the successful management of such areas. The salinity and sodium adsorption ratio (SAR) of soil surface have been modeled in this article. Auxiliary data were terrain attributes derived from the digital elevation model (DEM), remote sensing spectral bands, and indices of vegetation and salinity derived from the Landsat 8 OLI satellite. In total, 118 soil samples were collected from a depth of 0-15 cm in homogenous units at Doviraj plain in the southern part of Ilam province, western Iran. Saturated electrical conductivity (ECe), SAR, and other soil properties were analyzed and calculated. To model ECe and SAR parameters with the auxiliary data, stepwise multiple linear regression (SMLR) and random forest (RF) regression were applied. The highest accuracy was obtained through the RF model with validation coefficient of determination (R-2) = 0.82 and 0.83 and validation root mean square error (RMSE) = 7.40 dS/m and 11.20 for ECe and SAR, respectively. Furthermore, results indicated that the strongest influence on the prediction of soil salinity was obtained with Band10, principal component analysis (PC3), vertical distance to channel network (VDCN), and analytical hill-shading (AH). Also, Band10, Band11, flow accumulation (FA), and topographic wetness index (TWI) were the important covariates in alkalinity prediction through the RF model. Finally, it is suggested that similar techniques can be used to map and monitor soil salinity and alkalinity in other parts of arid regions.
英文关键词	Soil salinity and alkalinity Remote sensing Terrain data Multi linear regression Random forest regression
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000767736700001
WOS关键词	RANDOM FOREST ; COVER CHANGE ; PROVINCE ; REGION ; SAR
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/392465
推荐引用方式 GB/T 7714	Shahrayini, Elham,Noroozi, Ali Akbar. Modeling and Mapping of Soil Salinity and Alkalinity Using Remote Sensing Data and Topographic Factors: a Case Study in Iran[J],2022,27(5):901-913.
APA	Shahrayini, Elham,&Noroozi, Ali Akbar.(2022).Modeling and Mapping of Soil Salinity and Alkalinity Using Remote Sensing Data and Topographic Factors: a Case Study in Iran.ENVIRONMENTAL MODELING & ASSESSMENT,27(5),901-913.
MLA	Shahrayini, Elham,et al."Modeling and Mapping of Soil Salinity and Alkalinity Using Remote Sensing Data and Topographic Factors: a Case Study in Iran".ENVIRONMENTAL MODELING & ASSESSMENT 27.5(2022):901-913.