中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid

Enhancing the digital mapping accuracy of farmland soil organic carbon in arid areas using agricultural land use history

文献类型:期刊论文

作者Zhang, Zhaotong1,2; Zhang, Hongqi2; Xu, Erqi2
刊名JOURNAL OF CLEANER PRODUCTION
出版日期2022-02-01
卷号334页码:11
关键词Soil organic carbon digital mapping Agricultural land use history Random forest model
ISSN号0959-6526
DOI10.1016/j.jclepro.2021.130232
通讯作者Xu, Erqi(xueq@igsnrr.ac.cn)
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.
WOS关键词REGRESSION TREE ; RANDOM FORESTS ; REGION ; RECLAMATION ; CROPLANDS ; STOCKS ; PLAIN ; TEMPERATURE ; FRACTIONS ; VARIABLES
资助项目Second Tibetan Plateau Scientific Expedition and Research Program (STEP)[2019QZKK0603] ; National Natural Science Foundations of China[41601095] ; Youth Innovation Promotion Association CAS[2021052]
WOS研究方向Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000793137900004
出版者ELSEVIER SCI LTD
资助机构Second Tibetan Plateau Scientific Expedition and Research Program (STEP) ; National Natural Science Foundations of China ; Youth Innovation Promotion Association CAS
源URL[http://ir.igsnrr.ac.cn/handle/311030/176478]  
专题中国科学院地理科学与资源研究所
通讯作者Xu, Erqi
作者单位1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
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]. JOURNAL OF CLEANER PRODUCTION,2022,334:11.
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,334,11.
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):11.

入库方式: OAI收割

来源:地理科学与资源研究所

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