Spatial interpolation of cropland soil bulk density by increasing soil samples with filled missing values
文献类型：期刊论文
| 作者 | Li, Aiwen3; Cheng, Jinli3; Chen, Dan3; Li, Wendan3; Mao, Yaruo3; Chen, Xinyi3; Zhao, Bin2; Shi, Wenjiao1; Yue, Tianxiang1; Li, Qiquan3 |
| 刊名 | SCIENTIFIC REPORTS
 |
| 出版日期 | 2025-03-07 |
| 卷号 | 15期号:1页码:8008 |
| 关键词 | Soil bulk density Spatial interpolation Incomplete historical soil dataset Data imputation Sichuan basin |
| ISSN号 | 2045-2322 |
| DOI | 10.1038/s41598-025-91335-y |
| 产权排序 | 3 |
| 文献子类 | Article |
| 英文摘要 | Large sample sizes are crucial for accurately capturing spatial changes in soil properties by spatial interpolation methods. However, soil bulk density (BD) data in historical datasets is often incomplete, and it's uncertain if filled values enhance spatial interpolation accuracy. Using 2,883 cropland soil BD samples from the Sichuan Basin in China, we developed the best prediction models from traditional pedotransfer function (PTF), multiple linear regression (MLR), random forest (RF), and radial basis function neural network (RBFNN) to fill missing BD values for 1,336 samples. We then applied ordinary kriging (OK) and inverse distance weighting (IDW) to map soil BD, incorporating the filled BD as modeling points. The RBFNN model, tailored for each sub-watershed, yielded the highest accuracy in filling missing BD, with an increase in coefficient of determination (R2) by 19.54-37.36% and reductions in mean absolute error (MAE), mean relative error (MRE) and root mean square error (RMSE) by 8.91-14.81%, 9.02-16.22% and 7.71-13.61%, respectively. Incorporating filled BD data reduced the MAE, MRE, and RMSE of OK and IDW by 4.17%, 4.36%, 4.96%, and 6.54%, 6.92%, 8.15%, respectively, significantly lowering spatial interpolation uncertainty. This methodology improves the accuracy of soil property mapping in regions with incomplete historical data. |
| URL标识 | 查看原文 |
| WOS关键词 | PEDOTRANSFER FUNCTIONS ; ORGANIC-CARBON ; LOESS PLATEAU ; HILLY AREA ; PREDICTION ; UNCERTAINTY ; MATTER ; CHINA ; VARIABILITY ; NUTRIENT |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001439808000017 |
| 出版者 | NATURE PORTFOLIO |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/213267]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Li, Qiquan |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Sichuan Agr Univ, Coll Environm Sci, Chengdu 611130, Peoples R China; 3.Sichuan Agr Univ, Coll Resources, Chengdu 611130, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Li, Aiwen,Cheng, Jinli,Chen, Dan,et al. Spatial interpolation of cropland soil bulk density by increasing soil samples with filled missing values[J]. SCIENTIFIC REPORTS,2025,15(1):8008. |
| APA | Li, Aiwen.,Cheng, Jinli.,Chen, Dan.,Li, Wendan.,Mao, Yaruo.,...&Li, Qiquan.(2025).Spatial interpolation of cropland soil bulk density by increasing soil samples with filled missing values.SCIENTIFIC REPORTS,15(1),8008. |
| MLA | Li, Aiwen,et al."Spatial interpolation of cropland soil bulk density by increasing soil samples with filled missing values".SCIENTIFIC REPORTS 15.1(2025):8008. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。