HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Free Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (12) Citing Articles via Google Scholar Google Scholar Articles by Juang, K.-W. Articles by Ellsworth, T. R. Search for Related Content PubMed PubMed Citation Articles by Juang, K.-W. Articles by Ellsworth, T. R. GeoRef GeoRef Citation Agricola Articles by Juang, K.-W. Articles by Ellsworth, T. R. Related Collections Heavy Metals Soil Models Soil Pollution

TECHNICAL REPORT
Heavy Metals in the Environment

Using Rank-Order Geostatistics for Spatial Interpolation of Highly Skewed Data in a Heavy-Metal Contaminated Site

^a Graduate Institute of Agricultural Chemistry, National Taiwan Univ., Taipei, 106 Taiwan
^b Dep. of Natural Resources and Environmental Sciences, Univ. of Illinois, Urbana–Champaign, IL 61801

Corresponding author (dylee{at}ccms.ntu.edu.tw)

Received for publication March 6, 2000. The spatial distribution of a pollutant in contaminated soils is usually highly skewed. As a result, the sample variogram often differs considerably from its regional counterpart and the geostatistical interpolation is hindered. In this study, rank-order geostatistics with standardized rank transformation was used for the spatial interpolation of pollutants with a highly skewed distribution in contaminated soils when commonly used nonlinear methods, such as logarithmic and normal-scored transformations, are not suitable. A real data set of soil Cd concentrations with great variation and high skewness in a contaminated site of Taiwan was used for illustration. The spatial dependence of ranks transformed from Cd concentrations was identified and kriging estimation was readily performed in the standardized-rank space. The estimated standardized rank was back-transformed into the concentration space using the middle point model within a standardized-rank interval of the empirical distribution function (EDF). The spatial distribution of Cd concentrations was then obtained. The probability of Cd concentration being higher than a given cutoff value also can be estimated by using the estimated distribution of standardized ranks. The contour maps of Cd concentrations and the probabilities of Cd concentrations being higher than the cutoff value can be simultaneously used for delineation of hazardous areas of contaminated soils.

Abbreviations: CDF, cumulative distribution function • EDA, exploratory data analysis • EDF, empirical distribution function • ME, mean error • MSRE, mean square relative error

This article has been cited by other articles:

				J.A. Chipres, J.C. Salinas, J. Castro-Larragoitia, and M.G. Monroy Geochemical mapping of major and trace elements in soils from the Altiplano Potosino, Mexico: a multi-scale comparison Geochemistry: Exploration, Environment, Analysis, November 1, 2008; 8(3-4): 279 - 290. [Abstract] [Full Text] [PDF]