IGSNRR OpenIR
Robust variogram estimation combined with isometric log-ratio transformation for improved accuracy of soil particle-size fraction mapping
Wang, Zong1,2,3; Shi, Wenjiao1,3
2018-08-15
Source PublicationGEODERMA
ISSN0016-7061
Volume324Pages:56-66
Corresponding AuthorShi, Wenjiao(shiwj@lreis.ac.cn)
AbstractMapping soil particle-size fractions (psf) plays an important role in regional hydrological, ecological, geological, agricultural and environmental studies. To map soil compositional data like soil psf, interpolators such as compositional kriging and the combination of log-ratio transformations with ordinary kriging or cokriging were developed. In addition, robust estimators were proposed for these interpolators to improve the variogram models. However, few studies have focused on how to choose log-ratio transformation, kriging, cokriging, or robust variogram estimation methods based on data characteristics to achieve optimal performance when mapping soil psf by comprehensive comparative analysis. Here, we selected different compositional kriging, log ratio kriging, log-ratio cokriging and log-ratio cokriging methods combined with a robust variogram estimator to improve the accuracy of spatial predictions of soil psf when using 262 soil samples from the upper reaches of the Heihe River in China. In this study, a comprehensive comparative analysis of soil psf maps generated by using different interpolators is presented, and appropriate methods for mapping psf based on the characteristics of the available data are explored. The results show that using isometric log-ratio (ILR) transformation with different interpolators can achieve relatively better performance than the other log-ratio transformation methods. In addition, combining the interpolators with robust variogram estimators significantly improve the prediction accuracy compared with using standard estimators, which presented reasonable and smooth transitions when mapping soil psf. Combining ILR cokriging with a robust variogram estimator had the best accuracy, with the lowest root mean squared error (sand, 10.50%; silt, 11.24%; clay, 7.32%), an Aitchison's distance of 0.76, a standardized residual stun of squares of 0.70 and a relatively higher rate of correctly predicting soil texture types 90.04%. In the future, guideline for using log-ratio transformation methods with linear regression, a generalized linear model or random forest should be developed and combined with ancillary variables to improve the interpolators.
KeywordSoil particle-size fractions Spatial interpolation Log-ratio transformation Log-ratio cokriging Robust estimator
DOI10.1016/j.geoderma.2018.03.007
WOS KeywordCOMPOSITIONAL DATA-ANALYSIS ; SPATIAL PREDICTION ; REGIONALIZED COMPOSITIONS ; RANDOM FORESTS ; INTERPOLATION ; CARBON
Indexed BySCI
Language英语
Funding ProjectStrategic Priority Research Program of Chinese Academy of Sciences ; Pan-Third Pole Environment Study for a Green Silk Road (Pan-TPE) ; National Natural Science Foundation of China[41771111] ; National Natural Science Foundation of China[41771364] ; National Natural Science Foundation of China[41671219] ; Fund for Excellent Young Talents in Institute of Geographic Sciences ; Natural Resources Research, Chinese Academy of Sciences[2106RC201] ; State Key Laboratory of Resources and Environmental Information System
Funding OrganizationStrategic Priority Research Program of Chinese Academy of Sciences ; Pan-Third Pole Environment Study for a Green Silk Road (Pan-TPE) ; National Natural Science Foundation of China ; Fund for Excellent Young Talents in Institute of Geographic Sciences ; Natural Resources Research, Chinese Academy of Sciences ; State Key Laboratory of Resources and Environmental Information System
WOS Research AreaAgriculture
WOS SubjectSoil Science
WOS IDWOS:000431159500006
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/55082
Collection中国科学院地理科学与资源研究所
Corresponding AuthorShi, Wenjiao
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Wang, Zong,Shi, Wenjiao. Robust variogram estimation combined with isometric log-ratio transformation for improved accuracy of soil particle-size fraction mapping[J]. GEODERMA,2018,324:56-66.
APA Wang, Zong,&Shi, Wenjiao.(2018).Robust variogram estimation combined with isometric log-ratio transformation for improved accuracy of soil particle-size fraction mapping.GEODERMA,324,56-66.
MLA Wang, Zong,et al."Robust variogram estimation combined with isometric log-ratio transformation for improved accuracy of soil particle-size fraction mapping".GEODERMA 324(2018):56-66.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Wang, Zong]'s Articles
[Shi, Wenjiao]'s Articles
Baidu academic
Similar articles in Baidu academic
[Wang, Zong]'s Articles
[Shi, Wenjiao]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Wang, Zong]'s Articles
[Shi, Wenjiao]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.