A COMPARISON OF KRIGING, CO-KRIGING AND KRIGING COMBINED WITH REGRESSION FOR SPATIAL INTERPOLATION OF HORIZON DEPTH WITH CENSORED OBSERVATIONS

被引:236
作者
KNOTTERS, M [1 ]
BRUS, DJ [1 ]
VOSHAAR, JHO [1 ]
机构
[1] DLO,AGR MATH GRP,6700 AC WAGENINGEN,NETHERLANDS
关键词
D O I
10.1016/0016-7061(95)00011-C
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
We compared the performances of kriging and two methods of interpolation which allow to account for an auxiliary variable: co-kriging, and kriging combined with regression. These two methods were applied to improve the interpolation of the soft layers depth (D-sl) measured by augering, using the bulk soil electrical conductivity (EC(a)) measured by an electromagnetic instrument as auxiliary variable, We predicted D-sl from observations of EC(a) using an exponential regression model. These predictions were treated as uncertain measurements of D-sl in kriging. Results of this type of kriging were compared with those of co-kriging for grids of various spacing for D-sl. As the analysis of the spatial structure showed the presence of a drift of degree 2, IRF-2 kriging using generalized covariance functions was applied. Soft layers were not detected within the augering depth of 1.20 m at 10% of the locations. We paid special attention to these so-called censored observations of D-sl in the fitting of the regression model and in the interpolations. Kriging combined with regression gave better results than co-kriging. Moreover, in kriging combined with regression fewer model parameters needed to be estimated. This would be even more advantageous if two or more auxiliary variables were used.
引用
收藏
页码:227 / 246
页数:20
相关论文
共 50 条
[31]   Automatic method of kriging interpolation of spatial data [J].
Xu W. ;
Qiu F. ;
Xu A. .
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2016, 41 (04) :498-502
[32]   Kriging for localized spatial interpolation in sensor networks [J].
Umer, Muhammad ;
Kulik, Lars ;
Tanin, Egemen .
SCIENTIFIC AND STATISTICAL DATABASE MANAGEMENT, PROCEEDINGS, 2008, 5069 :525-532
[33]   Spatial Variability of Rock Depth Using Simple Kriging, Ordinary Kriging, RVM and MPMR [J].
Viswanathan, R. ;
Jagan, J. ;
Samui, Pijush ;
Porchelvan, P. .
GEOTECHNICAL AND GEOLOGICAL ENGINEERING, 2015, 33 (01) :69-78
[34]   Development and comparison of different methods of monitoring network design based on co-kriging [J].
Chang, LC ;
Chiu, YF .
AFTER THE RAIN HAS FALLEN, 1998, :63-68
[35]   A COMPARISON OF KRIGING WITH NONPARAMETRIC REGRESSION METHODS [J].
YAKOWITZ, SJ ;
SZIDAROVSZKY, F .
JOURNAL OF MULTIVARIATE ANALYSIS, 1985, 16 (01) :21-53
[36]   Bayesian Latent Variable Co-kriging Model in Remote Sensing for Quality Flagged Observations [J].
Bledar A. Konomi ;
Emily L. Kang ;
Ayat Almomani ;
Jonathan Hobbs .
Journal of Agricultural, Biological and Environmental Statistics, 2023, 28 :423-441
[37]   Spatial Interpolation of Reference Evapotranspiration in India: Comparison of IDW and Kriging Methods [J].
Hodam S. ;
Sarkar S. ;
Marak A.G.R. ;
Bandyopadhyay A. ;
Bhadra A. .
Journal of The Institution of Engineers (India): Series A, 2017, 98 (04) :511-524
[38]   Bayesian Latent Variable Co-kriging Model in Remote Sensing for Quality Flagged Observations [J].
Konomi, Bledar A. ;
Kang, Emily L. ;
Almomani, Ayat ;
Hobbs, Jonathan .
JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 2023, 28 (03) :423-441
[39]   Failure probability assessment using co-Kriging surrogate models [J].
Lefebvre, J. -P. ;
Dompierre, B. ;
Robert, A. ;
Le Bihan, M. ;
Wyart, E. ;
Sainvitu, C. .
FATIGUE DESIGN 2015, INTERNATIONAL CONFERENCE PROCEEDINGS, 6TH EDITION, 2015, 133 :622-630
[40]   Comments on "Performance of co-kriging in the determination of variability in soil attributes" [J].
Mata-Lima, Herlander .
REVISTA BRASILEIRA DE CIENCIA DO SOLO, 2007, 31 (04) :833-835