干旱区生态环境知识资源中心(Arid): Combining ancillary soil data with VisNIR spectra to improve predictions of organic and inorganic carbon content of soils

Arid

DOI	10.1016/j.mex.2018.05.019
	Combining ancillary soil data with VisNIR spectra to improve predictions of organic and inorganic carbon content of soils
	Filippi, Patrick; Cattle, Stephen R.; Bishop, Thomas F. A.; Jones, Edward J.; Minasny, Budiman
通讯作者	Filippi, P
来源期刊	METHODSX
EISSN	2215-0161
出版年	2018
卷号	5 页码:551-560
英文摘要	While traditional laboratory methods of determining soil organic carbon (SOC) content are generally simple, this becomes more challenging when carbonates are present in the soil; such is commonly found in semi-arid areas. Additionally, soil inorganic carbon (SIC) content itself is difficult to determine. This study uses visible near infrared (VisNIR) spectra to predict SOC and SIC contents of samples, and the impact of including soil pH and soil total carbon (STC) data as predictor variables was evaluated. The results indicated that combining available soil pH and STC content data with VisNIR spectra dramatically improved prediction accuracy of the Cubist models. Using the full suite of predictor variables, Cubist models trained on the calibration dataset (75%) could predict the validation dataset (25%) for SOC content with a Lin's concordance correlation coefficient (LCCC) of 0.94, and an LCCC of 0.83 for SIC content. This is compared to an LCCC of 0.81 and 0.35 for SOC and SIC content, respectively, when no ancillary soil data was included with VisNIR spectra as predictor variables. These results suggest that there may be promise for using other readily available soil data in combination with VisNIR spectra to improve the predictions of different soil properties. It can be laborious and expensive to measure soil organic and inorganic carbon content with traditional laboratory methods, and there has been recent focus on using spectroscopic techniques to overcome this. This study demonstrates that combining ancillary soil data (pH and total carbon content) with these spectroscopic techniques can considerably improve predictions of SOC and SIC content. (C) 2018 The Authors. Published by Elsevier B.V.
英文关键词	Visible near-infrared spectroscopy Ancillary soil data Organic carbon Inorganic carbon Carbonate Cubist
类型	Article
语种	英语
开放获取类型	DOAJ Gold, Green Published
收录类别	ESCI
WOS记录号	WOS:000454531500058
WOS关键词	DIFFUSE-REFLECTANCE SPECTROSCOPY
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/333168
作者单位	[Filippi, Patrick; Cattle, Stephen R.; Bishop, Thomas F. A.; Jones, Edward J.; Minasny, Budiman] Univ Sydney, Sch Life & Environm Sci, Sydney Inst Agr, Sydney, NSW, Australia
推荐引用方式 GB/T 7714	Filippi, Patrick,Cattle, Stephen R.,Bishop, Thomas F. A.,et al. Combining ancillary soil data with VisNIR spectra to improve predictions of organic and inorganic carbon content of soils[J],2018,5:551-560.
APA	Filippi, Patrick,Cattle, Stephen R.,Bishop, Thomas F. A.,Jones, Edward J.,&Minasny, Budiman.(2018).Combining ancillary soil data with VisNIR spectra to improve predictions of organic and inorganic carbon content of soils.METHODSX,5,551-560.
MLA	Filippi, Patrick,et al."Combining ancillary soil data with VisNIR spectra to improve predictions of organic and inorganic carbon content of soils".METHODSX 5(2018):551-560.