Geographically weighted methods and their use in network re-designs for environmental monitoring |
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Authors: | Paul Harris Annemarie Clarke Steve Juggins Chris Brunsdon Martin Charlton |
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Affiliation: | 4. Sustainable Soil and Grassland Systems, Rothamsted Research, North Wyke, Okehampton, Devon, EX20 2SB, UK 2. APEM Ltd, Llantrisant, UK 3. School of Geography, Politics and Sociology, University of Newcastle, Newcastle upon Tyne, UK 1. National Centre for Geocomputation, National University of Ireland Maynooth, Iontas Building, Maynooth, Co. Kildare, Ireland
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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. |
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