Mapping soil particle-size fractions based on compositional balances
文献类型：期刊论文
| 作者 | Zhang, Mo4,5; Shi, Wenjiao1,4,5; Ma, Yuxin3; Ge, Yong2,4,5 |
| 刊名 | CATENA
 |
| 出版日期 | 2024 |
| 卷号 | 234页码:12 |
| ISSN号 | 0341-8162 |
| 关键词 | Soil particle-size fractions Isometric log-ratio Random forest Regression kriging Compositional balance |
| DOI | 10.1016/j.catena.2023.107643 |
| 通讯作者 | Shi, Wenjiao(shiwj@lreis.ac.cn) |
| 英文摘要 | Mapping of soil particle-size fractions (PSFs) combined with log-ratio transformation has been widely employed, particularly for isometric log-ratio (ILR). Regression kriging (RK), as a hybrid interpolator, represents a method to enhance prediction accuracy. However, different choices of ILR balance yield distinct transformed data. It remains unclear and lacks a comparison as to whether these results exhibit robustness when employing RK modeling. In this study, we compared the performance of four modelling approaches-generalized linear model (GLM), random forest (RF), and their hybrid models (i.e., GLMRK and RFRK). These models were applied to three ILR transformed datasets based on different balances, resulting in a total of 12 models, in the upper reaches of the Heihe River Basin, China. The results indicated that RF tended to provide more accurate predictions of soil PSFs, while GLM was better at producing predictions with less bias. The study recommends the use of RK, as it was found to broaden the value ranges of predictions, adjust bias, and enhance accuracy, especially when applied in conjunction with RF models. Furthermore, prediction maps generated from RK unveiled finer details of soil sampling points. The choices of ILR balance resulted in varying data distributions for the components of sand, silt, and clay. These components tended to cluster at approximately 120 degrees in three groups, thereby indicating that even components with small content also exert significant influence on soil compositions. Rather than solely focusing on the relative abundance of components, this study suggests that the alignment of ILR components with a normal distribution is crucial for better model performance, especially for the first ILR component. Opting for the most abundant component as the first permutation may not always lead to optimal results for soil PSF mapping. This study provides insights into the role of data distribution and ILR balance selection in soil PSF mapping with transformed data. |
| WOS关键词 | GENERALIZED LINEAR-MODELS ; GEOSTATISTICAL ANALYSIS ; SPATIAL PREDICTION ; ROBUST ESTIMATORS ; REGRESSION TREE ; RIVER-BASIN ; VARIOGRAM ; INTERPOLATION ; CURVES |
| 资助项目 | National Natural Science Foundation of China[41930647] ; National Natural Science Foundation of China[72221002] ; National Key Research and Devel- opment Program of China[2022YFB3903504] ; State Key Laboratory of Resources and Environmental Information System |
| WOS研究方向 | Geology ; Agriculture ; Water Resources |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:001106155600001 |
| 资助机构 | National Natural Science Foundation of China ; National Key Research and Devel- opment Program of China ; State Key Laboratory of Resources and Environmental Information System |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200147]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Shi, Wenjiao |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, 11A Datun Rd, Beijing 100101, Peoples R China 2.Jiangxi Normal Univ, Key Lab Poyang Lake Wetland & Watershed Res, Minist Educ, Nanchang 330022, Peoples R China 3.Manaaki Whenua Landcare Res, Manawatu Mail Ctr, Private Bag 11052, Palmerston North 4442, New Zealand 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Mo,Shi, Wenjiao,Ma, Yuxin,et al. Mapping soil particle-size fractions based on compositional balances[J]. CATENA,2024,234:12. |
| APA | Zhang, Mo,Shi, Wenjiao,Ma, Yuxin,&Ge, Yong.(2024).Mapping soil particle-size fractions based on compositional balances.CATENA,234,12. |
| MLA | Zhang, Mo,et al."Mapping soil particle-size fractions based on compositional balances".CATENA 234(2024):12. |
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。