Real-time automatic interpolation of ambient gamma dose rates from the Dutch radioactivity monitoring network

By Paul H. Hiemstra, Edzer J. Pebesma, Chris J. W. Twenhöfel, Gerard B. M. Heuvelink. Computational Geosciences, 2009

470 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/398fba9e79b47980771df2ef3d2e20e6f756747e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. G. Guillera‐Arroita
2. J. Lahoz‐Monfort
3. Jack A. Gilbert
4. Jane Elith
5. Michael Flannigan

In Environmental Engineering

1. G. Guillera‐Arroita
2. B. Michael Wotton
3. G. Marshall
4. Jane Elith
5. Michael Flannigan

In Global and Planetary Change

1. J. Lahoz‐Monfort
2. G. Guillera‐Arroita
3. Jane Elith
4. Michael Flannigan

Citations in the corpus

• Potential climate change impacts on fire intensity and key wildfire suppression thresholds in Canada (2017, methodology): “Specifically, the krige function from the gstat package (Pebesma 2004) alongside the autofitVariogram function in the automap package (Hiemstra et al 2009).”
• blockCV: an R package for generating spatially or environmentally separated folds for k-fold cross-validation of species distribution models (2018, methodology): “The variogram fitting procedure uses the automap package (Hiemstra, Pebesma, Twenhöfel, & Heuvelink, 2009).”
• Geographic patterns of co-occurrence network topological features for soil microbiota at continental scale in eastern China (2016, methodology): “We then predicted the spatial distribution of these topological features based on Krige interpolation using the function autoKrige in automap packages (Hiemstra et al., 2009).”