Title: Methods to interpolate soil categorical variables from profile observations : lessons fron Iran
Authors: HENGL TOMISLAVTOOMANIAN NorairREUTER HANNES ISAAKMALAKOUTI Mohammad J.
Citation: GEODERMA vol. 140 no. 4 p. 417-427
Publisher: ELSEVIER SCIENCE BV
Publication Year: 2007
JRC N°: JRC31701
ISSN: 0016-7061
URI: http://www.sciencedirect.com/science/article/pii/S0016706107001218#
http://publications.jrc.ec.europa.eu/repository/handle/JRC31701
DOI: 10.1016/j.geoderma.2007.04.022
Type: Articles in periodicals and books
Abstract: Tha paper gives comparison of interpolation methods to produce soil-class maps from profile observations, given the large amount of auxiliary predictors such as terrain parameters, remote sensing indices and similar. The Soil Profile Database of Iran, consisting of 4250 profiles, was used to test different soil-class interpolators. Four techniques have been considered: (a) supervised classification using maximum likelihoods; (b) multinominal logistic regression; (c) regression-kriging on memberships; and (d) classification of taxonomic distances. The predictive capabilities were assessed using a control subset of 30% profiles and kappa statistics. Steps to improve interpolation of osil-class data, by considering the fuzziness of classes directly on the field and by improving the quality of input data, are further discussed.
JRC Directorate:Sustainable Resources

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