干旱区生态环境知识资源中心(Arid): Enhancing the digital mapping accuracy of farmland soil organic carbon in arid areas using agricultural land use history

Arid

DOI	10.1016/j.jclepro.2021.130232
	Enhancing the digital mapping accuracy of farmland soil organic carbon in arid areas using agricultural land use history
	Zhang, Zhaotong; Zhang, Hongqi; Xu, Erqi
通讯作者	Xu, EQ
来源期刊	JOURNAL OF CLEANER PRODUCTION
ISSN	0959-6526
EISSN	1879-1786
出版年	2022
卷号	334
英文摘要	Accurate digital mapping of soil organic carbon (SOC) over cultivated land is significant for estimating potential soil carbon sequestration and mitigating future climate changes. Large-scale land and water resource development in arid Northwest China has led to significant changes in SOC. Therefore, agricultural land use history, including reclamation source (RS) and cultivation year (CY), has significantly influenced SOC. However, when this information is ignored in digital mapping, biases arise. To solve this problem, this study applied RS and CY to SOC mapping and examined its impact on the results. The cultivated land of Qitai County was selected as the study area. Land use from 1980 to 2018 was superimposed to identify the agricultural land use history using our proposed methods. RS and CY were incorporated as environmental covariates and combined with other natural variables and field soil samples to predict the spatial distribution of SOC using the random forest (RF) model. The results showed that the SOC contents of plots reclaimed from high-coverage grassland and bare land were higher and lower, respectively, than other plots. The SOC increased in the short-term farming, but declined after reaching mid-and-long term. RS and CY were important environmental covariates for predicting cultivated land SOC. Incorporating RS and CY increased the mapping accuracy of SOC compared to only using natural variables. Adding RS and CY into the model resulted in an R-2 increase from 0.381 to 0.469, as well as an decrease in statistical errors. In addition, RS and CY provided more spatial detail attributed to land reclamation when mapping SOC. Overall, this study provided a new and improved method for integrating human activities into digital soil mapping.
英文关键词	Soil organic carbon digital mapping Agricultural land use history Random forest model
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000793137900004
WOS关键词	REGRESSION TREE ; RANDOM FORESTS ; REGION ; RECLAMATION ; CROPLANDS ; STOCKS ; PLAIN ; TEMPERATURE ; FRACTIONS ; VARIABLES
WOS类目	Green & Sustainable Science & Technology ; Engineering, Environmental ; Environmental Sciences
WOS研究方向	Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/393359
推荐引用方式 GB/T 7714	Zhang, Zhaotong,Zhang, Hongqi,Xu, Erqi. Enhancing the digital mapping accuracy of farmland soil organic carbon in arid areas using agricultural land use history[J],2022,334.
APA	Zhang, Zhaotong,Zhang, Hongqi,&Xu, Erqi.(2022).Enhancing the digital mapping accuracy of farmland soil organic carbon in arid areas using agricultural land use history.JOURNAL OF CLEANER PRODUCTION,334.
MLA	Zhang, Zhaotong,et al."Enhancing the digital mapping accuracy of farmland soil organic carbon in arid areas using agricultural land use history".JOURNAL OF CLEANER PRODUCTION 334(2022).