Fine-resolution mapping of cropland topsoil pH of Southern China and its environmental application
Bifeng Hu,
Modian Xie,
Zhou Shi,
Hongyi Li,
Songchao Chen,
Zhige Wang,
Yue Zhou,
Hanjie Ni,
Yibo Geng,
Qian Zhu,
Xianglin Zhang
Affiliations
Bifeng Hu
Department of Land Resource Management, School of Public Finance and Public Administration, Jiangxi University of Finance and Economics, Nanchang 330013, China; Key Laboratory of Data Science in Finance and Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China
Modian Xie
School of Information Management, Jiangxi University of Finance and Economics, Nanchang 330013, China
Zhou Shi
Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Hongyi Li
Department of Land Resource Management, School of Public Finance and Public Administration, Jiangxi University of Finance and Economics, Nanchang 330013, China; Key Laboratory of Data Science in Finance and Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China; Corresponding author at: Department of Land Resource Management, School of Public Finance and Public Administration, Jiangxi University of Finance and Economics, Nanchang 330013, China.
Songchao Chen
ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou 311200, China
Zhige Wang
Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Yue Zhou
Georges Lemaître Centre for Earth and Climate Research, Earth and Life Institute, Université Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium
Hanjie Ni
Department of Land Resource Management, School of Public Finance and Public Administration, Jiangxi University of Finance and Economics, Nanchang 330013, China
Yibo Geng
Department of Land Resource Management, School of Public Finance and Public Administration, Jiangxi University of Finance and Economics, Nanchang 330013, China
Qian Zhu
Department of Land Resource Management, School of Public Finance and Public Administration, Jiangxi University of Finance and Economics, Nanchang 330013, China
Xianglin Zhang
Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Soil pH is one of the critical indicators of soil quality. A fine resolution map of soil pH is urgently required to address practical issues of agricultural production, environmental protection, and ecosystem functioning, which often fall short of meeting the demands for local applications. To fill this gap, we used data from an extensive survey of 13,424 surface soil samples (0–0.2 m) across the cropland of Jiangxi Province in Southern China. Using digital soil mapping techniques with 46 covariates, we produced a 30 m resolution soil map of topsoil pH in cropland of Southern China. We integrate different variable selection algorithms and machine learning methods. Our results indicate the Random Forest with covariates selected by recursive feature selection had the best performance for mapping soil pH with r of 0.583 and RMSE of 0.41. The prediction interval coverage probability for our prediction was 0.92, indicating a low estimated prediction uncertainty. Climate was identified as the most critical variable for predicting soil pH with a contribution of 37.42 %, followed by soil properties (29.09 %), soil management (21.86 %), parent material (6.22 %), and biota (5.39 %) factors. The mean topsoil pH in the cropland of Jiangxi Province was 5.21, indicating a great pressure of soil acidification in this region. The high soil pH values were mainly distributed in the Northern, Western, and Eastern parts of the survey region while low soil pH values were majorly located in the central part. Compared with past surveys in 1980 s, there was no significant soil pH change in the surveyed region. Our soil pH map can provide important implications and guidance decisions on soil heavy metal pollution remediation, precision agriculture, and prevention of soil acidification.
