Gerard B. M. Heuvelink

Environmental Engineering · 2001–2020

A researcher in the Science corpus: 21 papers; trusts 35 researchers and is trusted by 57 researchers here, as inferred from the citation graph.

Subfields

• Environmental Engineering — 107 citations into it; #147 of 5,479 by trust here, #103 by citations
• Artificial Intelligence — 47 citations into it; #30,119 of 35,345 by trust here, #24,417 by citations
• Statistics and Probability — 33 citations into it
• Civil and Structural Engineering — 32 citations into it; #663 of 6,160 by trust here, #2,343 by citations
• Global and Planetary Change — 32 citations into it; #2,692 of 10,225 by trust here, #4,198 by citations
• Soil Science — 29 citations into it; #221 of 2,166 by trust here, #183 by citations
• Economics and Econometrics — 28 citations into it; #8,911 of 23,481 by trust here, #9,444 by citations
• Ecology — 24 citations into it; #1,337 of 10,717 by trust here, #1,767 by citations

Whom Gerard B. M. Heuvelink trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Tomislav Hengl
2. R. M. Lark
3. Michael L. Stein
4. Dick Brus
5. Edzer J. Pebesma
6. Budiman Minasny
7. Richard Webster
8. Kenneth A. Bollen
9. Yves Rosseel
10. Nicolai Meinshausen

Who trusts Gerard B. M. Heuvelink overall

1. Tomislav Hengl
2. A-Xing Zhu
3. Alex B. McBratney
4. Dick Brus
5. Mathieu Lepot
6. Jin Li
7. Tim Häring
8. Peter Scull
9. Budiman Minasny
10. M. E. Angelini

Papers from Gerard B. M. Heuvelink's perspective

Ordered by how strongly the researchers Gerard B. M. Heuvelink trusts endorse each paper. Same corpus, a different order for every researcher.

1. Bagging Predictors
2. Geostatistics for Natural Resources Evaluation
3. Modern Spatiotemporal Geostatistics
4. The elements of statistical learning: data mining, inference and prediction
5. A generic framework for spatial prediction of soil variables based on regression-kriging
6. Geostatistics For Environmental Scientists
7. Quantile Regression Forests
8. Methods to interpolate soil categorical variables from profile observations: Lessons from Iran
9. Optimized spatial sampling of soil for estimation of the variogram by maximum likelihood
10. Sampling for Natural Resource Monitoring

Their papers

• Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables (2018) — 919 citations
• Optimization of sample patterns for universal kriging of environmental variables (2007) — 350 citations
• Spatio-Temporal Interpolation using gstat (2016) — 788 citations
• Random Forest Spatial Interpolation (2020) — 303 citations
• Multivariate mapping of soil with structural equation modelling (2017) — 55 citations
• SoilGrids250m: Global gridded soil information based on machine learning (2017) — 3,747 citations
• An integrated pan‐tropical biomass map using multiple reference datasets (2016) — 648 citations
• Mapping the soils of an Argentine Pampas region using structural equation modelling (2016) — 65 citations
• Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions (2015) — 794 citations
• Do more detailed environmental covariates deliver more accurate soil maps (2015) — 116 citations
• SoilGrids1km — Global Soil Information Based on Automated Mapping (2014) — 1,112 citations
• Efficiency comparison of conventional and digital soil mapping for updating soil maps (2012) — 106 citations
• Sampling for validation of digital soil maps (2011) — 346 citations
• Sampling design optimization for multivariate soil mapping (2010) — 82 citations
• Real-time automatic interpolation of ambient gamma dose rates from the Dutch radioactivity monitoring network (2009) — 470 citations
• Bayesian Maximum Entropy prediction of soil categories using a traditional soil map as soft information (2008) — 56 citations
• A spatially explicit methodology to quantify soil nutrient balances and their uncertainties at the national level (2007) — 123 citations
• About regression-kriging: From equations to case studies (2007) — 956 citations
• Assessing uncertainty propagation through physically based models of soil water flow and solute transport (2006) — 94 citations
• A generic framework for spatial prediction of soil variables based on regression-kriging (2004) — 1,074 citations