E. Pebesma | Semantic Scholar

Publications
Influence

Multivariable geostatistics in S: the gstat package

E. Pebesma
Computer Science
Comput. Geosci.
1 August 2004

E. Pebesma, R. Bivand
Mathematics
18 October 2015

Simple Features for R: Standardized Support for Spatial Vector Data

E. Pebesma
Computer Science
R J.
2018

The sf package implements simple features in R, and has roughly the same capacity for spatial vector data as packages sp, rgeos and rgdal, and its place in the R package ecosystem, and the potential to connect R to other computer systems are described.

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Applied Spatial Data Analysis with R - Second Edition

R. Bivand, E. Pebesma, V. Gómez‐Rubio
Environmental Science, Mathematics
Use R!
1 September 2008

Hello, world: handling spatial data in R.- Classes for spatial data in R.- Visualizing spatial data.- Spatial data import and export.- Further methods for handling spatial data.- Customising spatial…

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GSTAT: a program for geostatistical modelling, prediction and simulation

E. Pebesma, C. Wesseling
Computer Science
1 February 1998

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Spatio-Temporal Interpolation using gstat

B. Gräler, E. Pebesma, G. Heuvelink
Environmental Science, Computer Science
R J.
2016

R code for variogram fitting and interpolation is presented in this paper to illustrate the workflow of spatio-temporal interpolation using gstat, and it is concluded that the system works properly and that the extension of gstat facilitates and eases spatiotemporal geostatistical modelling and prediction for R users.

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Mapping of background air pollution at a fine spatial scale across the European Union.

R. Beelen, G. Hoek, E. Pebesma, D. Vienneau, K. de Hoogh, D. Briggs
Environmental Science
The Science of the total environment
1 March 2009

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Applied Spatial Data Analysis with R. Springer

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

P. Hiemstra, E. Pebesma, C. Twenhöfel, G. Heuvelink
Environmental Science
Comput. Geosci.
1 August 2009

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spacetime: Spatio-Temporal Data in R

E. Pebesma
Computer Science
13 November 2012

To explore how spatio-temporal data can be sensibly represented in classes, and to find out which analysis and visualisation methods are useful and feasible, the time series convention of representing time intervals by their starting time only is discussed.

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