Geographically weighted methods and their use in network re-designs for environmental monitoring

A - Papers appearing in refereed journals

Harris, P., Clarke, A., Juggins, S., Brunsdon, C. and Charlton, M. 2014. Geographically weighted methods and their use in network re-designs for environmental monitoring. Stochastic Environmental Research and Risk Assessment. 28 (7), pp. 1869-1887. https://doi.org/10.1007/s00477-014-0851-1

AuthorsHarris, P., Clarke, A., Juggins, S., Brunsdon, C. and Charlton, M.
Abstract

Given an initial spatial sampling campaign, it is often of importance to conduct a second, more targeted campaign based on the properties of the first. Here a network re-design modifies the first one by adding and/or removing sites so that maximum information is preserved. Commonly, this optimisation is constrained by limited sampling funds and a reduced sample network is sought. To this extent, we demonstrate the use of geographically weighted methods combined with a location-allocation algorithm, as a means to design a second-phase sampling campaign in univariate, bivariate and multivariate contexts. As a case study, we use a freshwater chemistry data set covering much of Great Britain. Applying the two-stage procedure enables the optimal identification of a pre-specified number of sites, providing maximum spatial and univariate/bivariate/multivariate water chemistry information for the second campaign. Network re-designs that account for the buffering capacity of a freshwater site to acidification are also conducted. To complement the use of basic methods, robust alternatives are used to reduce the effect of anomalous observations on the re-designs. Our non-stationary re-design framework is general and provides a relatively simple and a viable alternative to geostatistical re-design procedures that are commonly adopted. Particularly in the multivariate case, it represents an important methodological advance.

KeywordsNon-stationarity ; Summary statistics ; PCA; location-allocation; robust; acidification
Year of Publication2014
JournalStochastic Environmental Research and Risk Assessment
Journal citation28 (7), pp. 1869-1887
Digital Object Identifier (DOI)https://doi.org/10.1007/s00477-014-0851-1
Open accessPublished as non-open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeDelivering Sustainable Systems (SS) [ISPG]
The North Wyke Farm Platform [2012-2017]
Quantifying Sustainable Systems
Publisher's version
Copyright license
Publisher copyright
Output statusPublished
Publication dates
Online12 Feb 2014
ISSN1436-3240
PublisherSpringer

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