References
- Addinsoft. XLSTAT tutorial. Paris: Addinsoft. http://www.xlstat.com/en/support/tutorials/ (http://www.xlstat.com/en/support/tutorials/)
- Baltensweiler , A. and Zimmermann , S. 2010 . Modeling soil acidity in Switzerland using spatial statistics tools . Proceedings of the International ESRI User Conference. , July 12–16, 2010, Paper nr. 1493, ESRI, San Diego, CA
- Cheng , X. F. , Shi , X. Z. , Yu , D. S. , Pan , X. Z. , Wang , H. J. and Sun , W. X. 2004 . Using GIS spatial distribution to predict soil organic carbon in subtropical China . Pedosphere , 14 ( 4 ) : 425 – 431 .
- Cimmery, V. 2010. User guide for SAGA (version 2.0.5), vol. 2. Available at http://sourceforge.net/projects/saga-gis/files/SAGA-Documentation/SAGA (http://sourceforge.net/projects/saga-gis/files/SAGA-Documentation/SAGA)
- Florinsky , I. V. , Eilers , R. G. , Manning , G. R. and Fuller , L. G. 2002 . Prediction of soil properties by digital terrain modelling . Environmental Modelling and Software , 17 : 295 – 311 .
- Fotheringham , S. , Brunsdon , C. and Charlton , M. 2002 . Geographically weighted regression: The analysis of spatially varying relationships , Chichester , UK : Wiley .
- Hengl , T. 2007 . A practical guide to geostatistical mapping of environmental variables (JRC Scientific and Technical Reports EUR 22904 EN) , Luxembourg: Office for Official Publications of the European Communities .
- Hengl , T. , Heuvelink , G. B. M. and Stein , A. 2004 . A generic framework for spatial prediction of soil variables based on regression kriging . Geoderma , 120 : 75 – 93 .
- Hengl , T. , Reuter , H. I. and Rodriguez-Lado , L. 2007 . “ Digital soil mapping at work: Interpolation of soil parameters for the Danube River basin ” . In Status and prospect of soil information in southeastern Europe: Soil databases, projects, and applications (EUR 22646 EN) , Edited by: Hengl , T. 129 – 137 . Luxembourg: Office for Official Publications of the European Communities .
- Lagacherie , P. , McBratney , A. and Voltz , M. 2006 . Digital soil mapping: An introductory perspective , Amsterdam : the Netherlands: Elsevier .
- McBratney , A. B. , Mendonça Santos , M. L. and Minasny , B. 2003 . On digital soil mapping . Geoderma , 117 : 3 – 52 .
- Odeh , I. O. A. and McBratney , A. B. 2000 . Using AVHRR images for spatial prediction of clay content in the lower Namoi Valley of eastern Australia . Geoderma , 97 : 237 – 254 .
- Patriche , C. V. 2009 . Statistical methods applied in climatology , Iaşi , , Romania : Terra Nostra Press .
- Patriche , C. V. and Vasiliniuc , I. 2009 . Aspects regarding the usefulness of geographically weighted regression (GWR) for digital mapping of soil parameters . Lucrări Ştiinţifice , 52 ( 1 ) : 415 – 420 .
- Pîrnău , R. G. 2011 . Land use and agricultural soils quality in Dobrovăţ hydrographic basin. Ph.D. dissertation, Alexandru Ioan Cuza University of , Iaşi , , Romania : Iaşi .
- Xie , X. L. , Sun , B. , Zhou , H. Z. and Li , A. B. 2004 . Soil organic carbon storage in China . Pedosphere , 14 ( 4 ) : 491 – 500 .
- Zhang , C. , Tang , Y. , Xu , X. and Kiely , G. 2011 . Towards spatial geochemical modelling: Use of geographically weighted regression for mapping soil organic carbon contents in Ireland . Applied Geochemistry. , 26 ( 7 ) : 1239 – 1248 .
- Ziadat , F. M. 2010 . Prediction of soil depth from digital terrain data by integrating statistical and visual approaches . Pedosphere , 20 ( 3 ) : 361 – 367 .