干旱区生态环境知识资源中心(Arid): Quantitative Evaluation of Soil Quality Using Principal Component Analysis: The Case Study of El-Fayoum Depression Egypt

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DOI	10.3390/su13041824
	Quantitative Evaluation of Soil Quality Using Principal Component Analysis: The Case Study of El-Fayoum Depression Egypt
	Abdel-Fattah, Mohamed K.; Mohamed, Elsayed Said; Wagdi, Enas M.; Shahin, Sahar A.; Aldosari, Ali A.; Lasaponara, Rosa; Alnaimy, Manal A.
通讯作者	Abdel-Fattah, MK (corresponding author), Zagazig Univ, Soil Sci Dept, Fac Agr, Zagazig 44519, Egypt. ; Mohamed, ES (corresponding author), Natl Author Remote Sensing & Space Sci, Cairo 11843, Egypt. ; Aldosari, AA (corresponding author), King Saud Univ, Geog Dept, Riyadh 11451, Saudi Arabia.
来源期刊	SUSTAINABILITY
EISSN	2071-1050
出版年	2021
卷号	13 期号:4
英文摘要	Soil quality assessment is the first step towards precision farming and agricultural management. In the present study, a multivariate analysis and geographical information system (GIS) were used to assess and map a soil quality index (SQI) in El-Fayoum depression in the Western Desert of Egypt. For this purpose, a total of 36 geo-referenced representative soil samples (0-0.6 m) were collected and analyzed according to standardized protocols. Principal component analysis (PCA) was used to reduce the dataset into new variables, to avoid multi-collinearity, and to determine relative weights (Wi) and soil indicators (Si), which were used to obtain the soil quality index (SQI). The zones of soil quality were determined using principal component scores and cluster analysis of soil properties. A soil quality index map was generated using a geostatistical approach based on ordinary kriging (OK) interpolation. The results show that the soil data can be classified into three clusters: Cluster I represents about 13.89% of soil samples, Cluster II represents about 16.6% of samples, and Cluster III represents the rest of the soil data (69.44% of samples). In addition, the simulation results of cluster analysis using the Monte Carlo method show satisfactory results for all clusters. The SQI results reveal that the study area is classified into three zones: very good, good, and fair soil quality. The areas categorized as very good and good quality occupy about 14.48% and 50.77% of the total surface investigated, and fair soil quality (mainly due to salinity and low soil nutrients) constitutes about 34.75%. As a whole, the results indicate that the joint use of PCA and GIS allows for an accurate and effective assessment of the SQI.
英文关键词	soil quality index soil evaluation geographic information cluster 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:000624806600001
WOS类目	Green & Sustainable Science & Technology ; Environmental Sciences ; Environmental Studies
WOS研究方向	Science & Technology - Other Topics ; Environmental Sciences & Ecology
来源机构	King Saud University
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/351814
作者单位	[Abdel-Fattah, Mohamed K.; Wagdi, Enas M.; Alnaimy, Manal A.] Zagazig Univ, Soil Sci Dept, Fac Agr, Zagazig 44519, Egypt; [Mohamed, Elsayed Said] Natl Author Remote Sensing & Space Sci, Cairo 11843, Egypt; [Shahin, Sahar A.] Natl Res Ctr, Agr & Biol Div, Soils & Water Use Dept, Cairo 12622, Egypt; [Aldosari, Ali A.] King Saud Univ, Geog Dept, Riyadh 11451, Saudi Arabia; [Lasaponara, Rosa] Italian Natl Res Council, I-85050 Potenza, Italy
推荐引用方式 GB/T 7714	Abdel-Fattah, Mohamed K.,Mohamed, Elsayed Said,Wagdi, Enas M.,et al. Quantitative Evaluation of Soil Quality Using Principal Component Analysis: The Case Study of El-Fayoum Depression Egypt[J]. King Saud University,2021,13(4).
APA	Abdel-Fattah, Mohamed K..,Mohamed, Elsayed Said.,Wagdi, Enas M..,Shahin, Sahar A..,Aldosari, Ali A..,...&Alnaimy, Manal A..(2021).Quantitative Evaluation of Soil Quality Using Principal Component Analysis: The Case Study of El-Fayoum Depression Egypt.SUSTAINABILITY,13(4).
MLA	Abdel-Fattah, Mohamed K.,et al."Quantitative Evaluation of Soil Quality Using Principal Component Analysis: The Case Study of El-Fayoum Depression Egypt".SUSTAINABILITY 13.4(2021).