Spatio-temporal interpolation using gstat. B Gräler, EJ Pebesma, GBM Heuvelink R J. 8 (1), 204, 2016 | 890 | 2016 |
Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables T Hengl, M Nussbaum, MN Wright, GBM Heuvelink, B Gräler PeerJ 6, e5518, 2018 | 728 | 2018 |
S classes and methods for spatial data: the sp package E Pebesma, RS Bivand R news 5 (2), 9-13, 2005 | 402 | 2005 |
Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation B Gräler, MJ van den BERG, S Vandenberghe, A Petroselli, S Grimaldi, ... Hydrology and Earth System Sciences 17 (4), 1281-1296, 2013 | 321 | 2013 |
Spatio‐temporal interpolation of daily temperatures for global land areas at 1 km resolution M Kilibarda, T Hengl, GBM Heuvelink, B Gräler, E Pebesma, ... Journal of Geophysical Research: Atmospheres 119 (5), 2294-2313, 2014 | 250 | 2014 |
VineCopula: Statistical inference of vine copulas U Schepsmeier, J Stoeber, EC Brechmann, B Graeler, T Nagler, T Erhardt R package version 1, 2012 | 234 | 2012 |
Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables, PeerJ, 6, e5518 T Hengl, M Nussbaum, MN Wright, GBM Heuvelink, B Gräler | 145 | 2018 |
Modelling skewed spatial random fields through the spatial vine copula B Gräler Spatial Statistics 10, 87-102, 2014 | 123 | 2014 |
Package ‘vinecopula’ U Schepsmeier, J Stoeber, EC Brechmann, B Graeler, T Nagler, T Erhardt, ... R package version 2 (5), 2015 | 119* | 2015 |
VineCopula: Statistical inference of vine copulas T Nagler, U Schepsmeier, J Stoeber, EC Brechmann, B Graeler, T Erhardt, ... R package version 2 (0), 2019 | 105 | 2019 |
Spatio-temporal interpolation of soil water, temperature, and electrical conductivity in 3D+ T: The Cook Agronomy Farm data set CK Gasch, T Hengl, B Gräler, H Meyer, TS Magney, DJ Brown Spatial Statistics 14, 70-90, 2015 | 95 | 2015 |
The pair-copula construction for spatial data: a new approach to model spatial dependency B Gräler, E Pebesma Procedia Environmental Sciences 7, 206-211, 2011 | 92 | 2011 |
gstat: Spatial and spatio-temporal geostatistical modelling, prediction and simulation E Pebesma, B Graeler R package version, 1.1-5, 2022 | 79* | 2022 |
Spatio-temporal analysis and interpolation of PM10 measurements in Europe for 2009 B Gräler, M Rehr, L Gerharz, E Pebesma ETC/ACM Technical Paper 8, 1-29, 2012 | 59 | 2012 |
Package ‘gstat’ E Pebesma, B Graeler, ME Pebesma Comprehensive R Archive Network (CRAN), 1-0, 2015 | 57 | 2015 |
Spatio-temporal geostatistics using gstat E Pebesma, B Gräler R J 903, 2014 | 45* | 2014 |
Linked brazilian amazon rainforest data T Kauppinen, GM de Espindola, J Jones, A Sánchez, B Gräler, ... Semantic Web 5 (2), 151-155, 2014 | 37 | 2014 |
Spatio-Temporal Interpolation using gstat, R J., 8, 204–218 B Gräler, E Pebesma, G Heuvelink | 34 | 2016 |
Modeling spatiotemporal information generation S Scheider, B Gräler, E Pebesma, C Stasch International Journal of Geographical Information Science 30 (10), 1980-2008, 2016 | 28 | 2016 |
Joint return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation S Vandenberghe, MJ Van den Berg, B Gräler, A Petroselli, S Grimaldi, ... Hydrology and Earth System Sciences Discussions 9 (5), 6781-6828, 2012 | 24 | 2012 |