Geostatistical mapping of geomorphic variables in the presence of trend

A - Papers appearing in refereed journals

Lark, R. M. and Webster, R. 2006. Geostatistical mapping of geomorphic variables in the presence of trend. Earth Surface Processes and Landforms. 31 (7), pp. 862-874.

AuthorsLark, R. M. and Webster, R.
Abstract

Mapping geomorphic variables geostatistically, specifically by kriging, runs into difficulties when there is trend. The reason is that the variogram required for the kriging must be of residuals from any trend, which in turn cannot be estimated optimally by the usual method of trend surface analysis because the residuals are correlated. The difficulties can be overcome by the use of residual maximum likelihood (REML) to estimate both the trend and the variogram of the residuals simultaneously. We summarize the theory of REML as it applies to kriging in the presence of trend. We present the equations to show how estimates of the trend are combined with kriging of residuals to give empirical best linear unbiased predictions (E-BLUPs). We then apply the method to estimate the height of the sub-Upper-Chalk surface beneath the Chiltern Hills of southeast England from 238 borehole data. The variogram of the REML residuals is substantially different from that computed by ordinary least squares (OLS) analysis. The map of the predicted surface is similar to that made from kriging with the OLS variogram. The variances, however, are substantially larger because (a) they derive from a variogram with a much lager sill and (b) they include the uncertainty of the estimate of the trend. Copyright (c) 2006 John Wiley & Sons, Ltd.

KeywordsGeography, Physical; Geosciences, Multidisciplinary
Year of Publication2006
JournalEarth Surface Processes and Landforms
Journal citation31 (7), pp. 862-874
Digital Object Identifier (DOI)doi:10.1002/esp.1296
Open accessPublished as non-open access
Funder project or code513
ISSN01979337
PublisherWiley

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