Dick Brus

Environmental Engineering · 2006–2020

A researcher in the Science corpus: 8 papers; trusts 9 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Environmental Engineering — 38 citations into it; #1,248 of 5,479 by trust here, #1,138 by citations
• Soil Science — 16 citations into it
• Civil and Structural Engineering — 15 citations into it; #5,250 of 6,160 by trust here, #5,586 by citations
• Artificial Intelligence — 10 citations into it; #31,602 of 35,345 by trust here, #27,551 by citations
• Ecology — 9 citations into it
• Management, Monitoring, Policy and Law — 8 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Dick Brus trusts overall

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

1. Michael L. Stein
2. Tomislav Hengl
3. Patrick Bogaert
4. Gerard B. M. Heuvelink
5. Alfred Stein
6. R. M. Lark
7. Sabine Grunwald
8. David G. Rossiter
9. George Christakos
10. Giles M. Foody

Who trusts Dick Brus overall

1. Tomislav Hengl
2. Scott M. Lesch
3. Gerard B. M. Heuvelink
4. Bas Kempen
5. Mah-Rukh Fida
6. Dennis L. Corwin
7. Andra Lutu
8. G. Aarts
9. Stephen V. Stehman
10. Jinfeng Wang

Papers from Dick Brus's perspective

Ordered by how strongly the researchers Dick Brus trusts endorse each paper. Same corpus, a different order for every researcher.

1. Modern Spatiotemporal Geostatistics
2. Geostatistics for Natural Resources Evaluation
3. Modelling soil variation: past, present, and future
4. Sampling for Natural Resource Monitoring
5. Optimized spatial sampling of soil for estimation of the variogram by maximum likelihood
6. Status of land cover classification accuracy assessment
7. A generic framework for spatial prediction of soil variables based on regression-kriging
8. Spatial sampling design for parameter estimation of the covariance function
9. Spatial prediction of categorical variables: the Bayesian maximum entropy approach
10. Extrapolating regional soil landscapes from an existing soil map: Sampling intensity, validation procedures, and integration of spatial context

Their papers

• Optimization of sample patterns for universal kriging of environmental variables (2007) — 350 citations
• Comparison of conditioned Latin hypercube and feature space coverage sampling for predicting soil classes using simulation from soil maps (2020) — 56 citations
• Mapping soil organic carbon content by geographically weighted regression: A case study in the Heihe River Basin, China (2016) — 183 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
• Bayesian Maximum Entropy prediction of soil categories using a traditional soil map as soft information (2008) — 56 citations
• Sampling for Natural Resource Monitoring (2006) — 555 citations
• Chapter 14 Designing Spatial Coverage Samples Using the k-means Clustering Algorithm (2006) — 54 citations