2009
DOI: 10.1016/j.cageo.2008.10.011
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Real-time automatic interpolation of ambient gamma dose rates from the Dutch radioactivity monitoring network

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Cited by 396 publications
(238 citation statements)
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“…Kriging analysis was performed with the "gstat" package (Pebesma 2004). Variogram fitting for each variable was optimized using iterative re-weighted least squares using the "automap" package (Hiemstra et al 2009). Pairwise Wilcoxon Rank Sum Test was used to compare statistical differences between inflow and outflow nutrients, sediment and carbon loads.…”
Section: Discussionmentioning
confidence: 99%
“…Kriging analysis was performed with the "gstat" package (Pebesma 2004). Variogram fitting for each variable was optimized using iterative re-weighted least squares using the "automap" package (Hiemstra et al 2009). Pairwise Wilcoxon Rank Sum Test was used to compare statistical differences between inflow and outflow nutrients, sediment and carbon loads.…”
Section: Discussionmentioning
confidence: 99%
“…the lag. More details on the automatic variogram fitting may be found in Hiemstra et al (2009). A station-gridpoint comparison was performed at seasonal scale to assess the quality of the interpolated data.…”
Section: Climate Observations and Interpolationmentioning
confidence: 99%
“…KED is the kriging with external drift method which is similar to regression kriging (Hengl et al, 2007). An automated interpolation based on the AUTOMAP R packages (R Core Team, 2016;Hiemstra et al, 2009) has been used in this study.…”
Section: Frost Stress Crop Model and Pea Parametersmentioning
confidence: 99%
“…Spatial grids.-Environmental variables were measured at each gill-net set (n = 24,756) and subsequently interpolated into raster grids using ordinary kriging (Saveliev et al 2007;Elith et al 2008; via the "autoKrige" function in the automap package in R (Hiemstra et al 2009). Environmental grids were developed for each month (April, May, June, September, October, and November) and year combination between 1980 and 2012 to permit spatially specific predictions during specific months and/or time periods.…”
Section: Froeschke and Froeschkementioning
confidence: 99%