SoilGrids250m: Global gridded soil information based on machine learning T Hengl, J Mendes de Jesus, GBM Heuvelink, M Ruiperez Gonzalez, ... PLoS one 12 (2), e0169748, 2017 | 1196 | 2017 |
A generic framework for spatial prediction of soil variables based on regression-kriging T Hengl, GBM Heuvelink, A Stein Geoderma 120 (1-2), 75-93, 2004 | 1095 | 2004 |
Error propagation in environmental modelling with GIS GBM Heuvelink CRC press, 1998 | 899 | 1998 |
About regression-kriging: From equations to case studies T Hengl, GBM Heuvelink, DG Rossiter Computers & geosciences 33 (10), 1301-1315, 2007 | 786 | 2007 |
SoilGrids1km—global soil information based on automated mapping T Hengl, JM de Jesus, RA MacMillan, NH Batjes, GBM Heuvelink, ... PloS one 9 (8), e105992, 2014 | 729 | 2014 |
Modelling soil variation: past, present, and future GBM Heuvelink, R Webster Geoderma 100 (3-4), 269-301, 2001 | 460 | 2001 |
Mapping soil properties of Africa at 250 m resolution: Random forests significantly improve current predictions T Hengl, GBM Heuvelink, B Kempen, JGB Leenaars, MG Walsh, ... PloS one 10 (6), e0125814, 2015 | 455 | 2015 |
Propagation of errors in spatial modelling with GIS GBM Heuvelink, PA Burrough, A Stein International Journal of Geographical Information System 3 (4), 303-322, 1989 | 377 | 1989 |
An integrated pan‐tropical biomass map using multiple reference datasets V Avitabile, M Herold, GBM Heuvelink, SL Lewis, OL Phillips, GP Asner, ... Global change biology 22 (4), 1406-1420, 2016 | 372 | 2016 |
Optimization of sample patterns for universal kriging of environmental variables DJ Brus, GBM Heuvelink Geoderma 138 (1-2), 86-95, 2007 | 369 | 2007 |
Spatio-temporal interpolation using gstat E Pebesma, G Heuvelink RFID Journal 8 (1), 204-218, 2016 | 367 | 2016 |
Understanding theory of change in international development D Stein, C Valters Justice and Security Research Programme, International Development …, 2012 | 311* | 2012 |
Real-time automatic interpolation of ambient gamma dose rates from the Dutch radioactivity monitoring network PH Hiemstra, EJ Pebesma, CJW Twenhöfel, GBM Heuvelink Computers & Geosciences 35 (8), 1711-1721, 2009 | 311 | 2009 |
Sampling for validation of digital soil maps DJ Brus, B Kempen, GBM Heuvelink European Journal of Soil Science 62 (3), 394-407, 2011 | 279 | 2011 |
Spatial aggregation and soil process modelling GBM Heuvelink, EJ Pebesma Geoderma 89 (1-2), 47-65, 1999 | 257 | 1999 |
DEM resolution effects on shallow landslide hazard and soil redistribution modelling L Claessens, GBM Heuvelink, JM Schoorl, A Veldkamp Earth Surface Processes and Landforms: The Journal of the British …, 2005 | 256 | 2005 |
Estimating fatigue curves with the random fatigue-limit model FG Pascual, WQ Meeker Technometrics 41 (4), 277-289, 1999 | 242 | 1999 |
Using linear integer programming for multi‐site land‐use allocation JCJH Aerts, E Eisinger, GBM Heuvelink, TJ Stewart Geographical analysis 35 (2), 148-169, 2003 | 235 | 2003 |
Using simulated annealing for resource allocation JCJH Aerts, GBM Heuvelink International Journal of Geographical Information Science 16 (6), 571-587, 2002 | 234 | 2002 |
Updating the 1: 50,000 Dutch soil map using legacy soil data: A multinomial logistic regression approach B Kempen, DJ Brus, GBM Heuvelink, JJ Stoorvogel Geoderma 151 (3-4), 311-326, 2009 | 232 | 2009 |