干旱区生态环境知识资源中心(Arid): Spatial stochastic model for predicting soil organic matter using remote sensing data

Arid

DOI	10.1080/10106049.2020.1720314
	Spatial stochastic model for predicting soil organic matter using remote sensing data
	Mallick, Javed 1; Ahmed, Mohd 1; Alqadhi, Saeed Dhafer 1; Falqi, Ibrahim I.1; Parayangat, Muneer 2; Singh, Chander Kumar 3; Rahman, Atiqur 4; Ijyas, Thafasal 2
通讯作者	Mallick, Javed
来源期刊	GEOCARTO INTERNATIONAL
ISSN	1010-6049
EISSN	1752-0762
出版年	2020-03
英文摘要	Accurate soil organic matter (SOM) estimation could provide critical information to understand soil organic carbon sequestration, soil fertility, and the global carbon cycle. A nearest-neighbourhood autoregressive moving average (NN-ARMA) modelling technique along with linear regression has been used to predict localized soil SOM variation based on topographical characteristics and vegetation indices in semi-arid region of Saudi Arabia. Seven topographic variables derived using DEM, and twelve vegetation indices obtained from Landsat 8 used in the model. The best NN-ARMA model showed seven significant variables explaining 96.4% of the total variation of SOM, whereas the best linear regression model could explain 78.8% of the total variation of SOM. The results showed that NN-ARMA model gave better results compared to the linear regression model. Our research gave a better understanding of the possibility of accurate estimation of SOM using the NN-ARMA approach using topographical characteristics and vegetation indices easily acquired by RS sensors.
英文关键词	Soil organic matter semi-arid region nearest-neighbourhood ARMA linear regression topographic variables vegetation indices
类型	Article ; Early Access
语种	英语
国家	Saudi Arabia ; India
收录类别	SCI-E
WOS记录号	WOS:000519408600001
WOS关键词	LEAF-AREA INDEX ; VEGETATION INDEXES ; CARBON STOCKS ; VARIABILITY ; REGRESSION ; DERIVATION ; STABILITY ; SURFACE ; LINE ; BAND
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/2XILL650/314576
作者单位	1.King Khalid Univ, Coll Engn, Dept Civil Engn, Abha, Saudi Arabia; 2.King Khalid Univ, Coll Engn, Dept Elect Engn, Abha, Saudi Arabia; 3.TERI Sch Adv Studies, Dept Energy & Environm, New Delhi, India; 4.Jamia Millia Islamia, Fac Nat Sci, Urban Environm & Remote Sensing Div, New Delhi, India
推荐引用方式 GB/T 7714	Mallick, Javed,Ahmed, Mohd,Alqadhi, Saeed Dhafer,et al. Spatial stochastic model for predicting soil organic matter using remote sensing data[J],2020.
APA	Mallick, Javed.,Ahmed, Mohd.,Alqadhi, Saeed Dhafer.,Falqi, Ibrahim I..,Parayangat, Muneer.,...&Ijyas, Thafasal.(2020).Spatial stochastic model for predicting soil organic matter using remote sensing data.GEOCARTO INTERNATIONAL.
MLA	Mallick, Javed,et al."Spatial stochastic model for predicting soil organic matter using remote sensing data".GEOCARTO INTERNATIONAL (2020).