干旱区生态环境知识资源中心(Arid): National digital soil map of organic matter in topsoil and its associated uncertainty in 1980's China

Arid

DOI	10.1016/j.geoderma.2018.08.011
	National digital soil map of organic matter in topsoil and its associated uncertainty in 1980's China
	Liang, Zongzheng 1,2; Chen, Songchao 3,4; Yang, Yuanyuan 1; Zhao, Ruiying 1; Shi, Zhou 1; Rossel, Raphael A. Viscarra 2
通讯作者	Shi, Zhou
来源期刊	GEODERMA
ISSN	0016-7061
EISSN	1872-6259
出版年	2019
卷号	335 页码:47-56
英文摘要	Accurate digital soil maps of soil organic matter (SOM) are needed to evaluate soil fertility, to estimate stocks, and for ecological and environment modeling. We used 5982 soil profiles collected during the second national soil survey of China, along with 19 environment predictors, to derive a spatial model of SOM concentration in the topsoil (0-20 cm layer). The environmental predictors relate to the soil forming factors, climate, vegetation, relief and parent material. We developed the model using the Cubist machine-learning algorithm combined with a non-parametric bootstrap to derive estimates of model uncertainty. We optimized the Cubist model using a 10-fold cross-validation and the best model used 17 rules. The correlation coefficient between the observed and predicted values was 0.65, and the root mean squared error was 0.28 g/kg. We then applied the model over China and mapped the SOM distribution at a resolution of 90 x 90 m. Our predictions show that there is more SOM in the eastern Tibetan Plateau, northern Heilongjiang province, northeast Mongolia, and a small area of Tianshan Mountain in Xinjiang. There is less SOM in the Loess Plateau and most of the desert areas in northwest China. The average topsoil SOM content is 24.82 g/kg. The study provides a map that can be used for decision-making and contribute towards a baseline assessment for inventory and monitoring. The map could also aid the design of future soil surveys and help with the development of a SOM monitoring network in China.
英文关键词	Soil organic matter Spatial modeling Cubist machine learning algorithm Soil map Uncertainty assessment
类型	Article
语种	英语
国家	Peoples R China ; Australia ; France
收录类别	SCI-E
WOS记录号	WOS:000447095700005
WOS关键词	CARBON SEQUESTRATION ; DEPTH FUNCTIONS ; STORAGE ; GLOBALSOILMAP ; SCALE ; AREA
WOS类目	Soil Science
WOS研究方向	Agriculture
来源机构	Commonwealth Scientific and Industrial Research Organisation
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/215912
作者单位	1.Zhejiang Univ, Inst Agr Remote Sensing & Informat Technol Applic, Hangzhou 310058, Zhejiang, Peoples R China; 2.CSIRO Land & Water, Bruce E Butler Lab, POB 1700, Canberra, ACT 2601, Australia; 3.INRA, Unite InfoSol, F-45075 Orleans, France; 4.Agrocampus Ouest, INRA, UMR SAS, F-35000 Rennes, France
推荐引用方式 GB/T 7714	Liang, Zongzheng,Chen, Songchao,Yang, Yuanyuan,et al. National digital soil map of organic matter in topsoil and its associated uncertainty in 1980's China[J]. Commonwealth Scientific and Industrial Research Organisation,2019,335:47-56.
APA	Liang, Zongzheng,Chen, Songchao,Yang, Yuanyuan,Zhao, Ruiying,Shi, Zhou,&Rossel, Raphael A. Viscarra.(2019).National digital soil map of organic matter in topsoil and its associated uncertainty in 1980's China.GEODERMA,335,47-56.
MLA	Liang, Zongzheng,et al."National digital soil map of organic matter in topsoil and its associated uncertainty in 1980's China".GEODERMA 335(2019):47-56.