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Thorsten Behrens

Thorsten Behrens

Thorsten Behrens publication distribution in Earth Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Earth Science in 2026. The highlighted bar marks where Thorsten Behrens sits on this spectrum.

38–42 publications: 1 scientists 43–47 publications: 0 scientists 48–52 publications: 3 scientists 53–57 publications: 8 scientists 58–62 publications: 11 scientists 63–67 publications: 16 scientists 68–72 publications: 24 scientists 73–77 publications: 31 scientists 78–82 publications: 49 scientists 83–87 publications: 77 scientists 88–92 publications: 86 scientists 93–97 publications: 88 scientists 98–102 publications: 92 scientists 103–107 publications: 84 scientists 108–112 publications: 102 scientists 113–117 publications: 108 scientists 118–122 publications: 117 scientists 123–127 publications: 126 scientists 128–132 publications: 146 scientists 133–137 publications: 114 scientists 138–142 publications: 102 scientists 143–147 publications: 127 scientists 148–152 publications: 102 scientists 153–157 publications: 112 scientists 158–162 publications: 102 scientists 163–167 publications: 127 scientists 168–172 publications: 121 scientists 173–177 publications: 112 scientists 178–182 publications: 109 scientists 183–187 publications: 98 scientists 188–192 publications: 92 scientists 193–197 publications: 105 scientists 198–202 publications: 77 scientists 203–207 publications: 80 scientists 208–212 publications: 89 scientists 213–217 publications: 70 scientists 218–222 publications: 74 scientists 223–227 publications: 74 scientists 228–232 publications: 70 scientists 233–237 publications: 67 scientists 238–242 publications: 59 scientists 243–247 publications: 67 scientists 248–252 publications: 51 scientists 253–257 publications: 46 scientists 258–262 publications: 41 scientists 263–267 publications: 39 scientists 268–272 publications: 34 scientists 273–277 publications: 39 scientists 278–282 publications: 35 scientists 283–287 publications: 36 scientists 288–292 publications: 35 scientists 293–297 publications: 29 scientists 298–302 publications: 23 scientists 303–307 publications: 39 scientists 308–312 publications: 34 scientists 313–317 publications: 23 scientists 318–322 publications: 18 scientists 323–327 publications: 18 scientists 328–332 publications: 21 scientists 333–337 publications: 20 scientists 338–342 publications: 15 scientists 343–347 publications: 13 scientists 348–352 publications: 24 scientists 353–357 publications: 25 scientists 358–362 publications: 10 scientists 363–367 publications: 20 scientists 368–372 publications: 17 scientists 373–377 publications: 18 scientists 378–382 publications: 15 scientists 383–387 publications: 7 scientists 388–392 publications: 22 scientists 393–397 publications: 9 scientists 398–402 publications: 11 scientists 403–407 publications: 16 scientists 408–412 publications: 4 scientists 413–417 publications: 5 scientists 418–422 publications: 14 scientists 423–427 publications: 8 scientists 428–432 publications: 7 scientists 433–437 publications: 7 scientists 438–442 publications: 10 scientists 443–447 publications: 10 scientists 448–452 publications: 3 scientists 453–457 publications: 9 scientists 458–462 publications: 11 scientists 463–467 publications: 4 scientists 468–472 publications: 6 scientists 473–477 publications: 11 scientists 478–482 publications: 8 scientists 483–487 publications: 2 scientists 488–492 publications: 3 scientists 493–497 publications: 4 scientists 498–502 publications: 4 scientists 503–507 publications: 4 scientists 508–509 publications: 4 scientists 510+ publications: 100 scientists
38 publications 510+

The last bar groups every scientist with 510 publications or more.

Thorsten Behrens D-index placement in Earth Science in 2026

The chart shows the D-index (discipline H-index) distribution of Earth Science scientists ranked by Research.com in 2026. The highlighted bar marks where Thorsten Behrens sits on this spectrum.

30 D-Index: 15 scientists 31 D-Index: 42 scientists 32 D-Index: 60 scientists 33 D-Index: 90 scientists 34 D-Index: 103 scientists 35 D-Index: 108 scientists 36 D-Index: 142 scientists 37 D-Index: 147 scientists 38 D-Index: 147 scientists 39 D-Index: 152 scientists 40 D-Index: 143 scientists 41 D-Index: 157 scientists 42 D-Index: 141 scientists 43 D-Index: 151 scientists 44 D-Index: 140 scientists 45 D-Index: 135 scientists 46 D-Index: 121 scientists 47 D-Index: 108 scientists 48 D-Index: 128 scientists 49 D-Index: 111 scientists 50 D-Index: 106 scientists 51 D-Index: 112 scientists 52 D-Index: 102 scientists 53 D-Index: 103 scientists 54 D-Index: 94 scientists 55 D-Index: 61 scientists 56 D-Index: 101 scientists 57 D-Index: 71 scientists 58 D-Index: 65 scientists 59 D-Index: 78 scientists 60 D-Index: 93 scientists 61 D-Index: 56 scientists 62 D-Index: 58 scientists 63 D-Index: 52 scientists 64 D-Index: 63 scientists 65 D-Index: 49 scientists 66 D-Index: 53 scientists 67 D-Index: 57 scientists 68 D-Index: 50 scientists 69 D-Index: 44 scientists 70 D-Index: 44 scientists 71 D-Index: 31 scientists 72 D-Index: 33 scientists 73 D-Index: 33 scientists 74 D-Index: 23 scientists 75 D-Index: 32 scientists 76 D-Index: 24 scientists 77 D-Index: 17 scientists 78 D-Index: 19 scientists 79 D-Index: 9 scientists 80 D-Index: 21 scientists 81 D-Index: 20 scientists 82 D-Index: 17 scientists 83 D-Index: 19 scientists 84 D-Index: 19 scientists 85 D-Index: 14 scientists 86 D-Index: 6 scientists 87 D-Index: 14 scientists 88 D-Index: 17 scientists 89 D-Index: 10 scientists 90 D-Index: 8 scientists 91 D-Index: 8 scientists 92 D-Index: 9 scientists 93 D-Index: 6 scientists 94+ D-Index: 98 scientists
30 D-Index 94+

The last bar groups every scientist with 94 D-Index or more.

Overview

Thorsten Behrens is affiliated with the University of Tübingen in Germany and contributes primarily to the fields of Environmental Science and Agricultural and Biological Sciences. Their work spans several subfields including Environmental Engineering, Soil Science, Artificial Intelligence, Ecology, and Civil and Structural Engineering.

The researcher's major topics encompass Soil Geostatistics and Mapping, Geochemistry and Geologic Mapping, Soil Erosion and Sediment Transport, Soil Carbon and Nitrogen Dynamics, Soil and Unsaturated Flow, Soil Moisture and Remote Sensing, and Spectroscopy and Chemometric Analyses.

Thorsten Behrens has published multiple papers across notable scientific journals. Some recent papers include:

  • Improving the Spatial Prediction of Soil Organic Carbon Content in Two Contrasting Climatic Regions by Stacking Machine Learning Models and Rescanning Covariate Space, 2020, Remote Sensing
  • Improving the spatial prediction of soil salinity in arid regions using wavelet transformation and support vector regression models, 2020, Geoderma
  • Multi-task convolutional neural networks outperformed random forest for mapping soil particle size fractions in central Iran, 2020, Geoderma
  • Diffuse reflectance spectroscopy for estimating soil properties: A technology for the 21st century, 2022, European Journal of Soil Science
  • Deep transfer learning of global spectra for local soil carbon monitoring, 2022, ISPRS Journal of Photogrammetry and Remote Sensing

Their frequent co-authors include Raphael A. Viscarra Rossel, Karsten Schmidt, Thomas Scholten, Leonardo Ramírez-López, and Ruhollah Taghizadeh-Mehrjardi.

Publications are predominantly found in these venues: Geoderma, Remote Sensing, European Journal of Soil Science, Scientific Reports, and arXiv (Cornell University).

Best Publications

  • Using data mining to model and interpret soil diffuse reflectance spectra.

    R.A. Viscarra Rossel;T. Behrens

  • A global spectral library to characterize the world’s soil

    R.A. Viscarra Rossel;T. Behrens;E. Ben-Dor;D.J. Brown

  • Soil organic carbon concentrations and stocks on Barro Colorado Island — Digital soil mapping using Random Forests analysis

    R. Grimm;T. Behrens;M. Marker;Helmut Elsenbeer;Helmut Elsenbeer

  • Impacts of species richness on productivity in a large-scale subtropical forest experiment.

    Yuanyuan Huang;Yuxin Chen;Nadia Castro-Izaguirre;Martin Baruffol;Martin Baruffol

  • Multi-scale digital terrain analysis and feature selection for digital soil mapping

    Thorsten Behrens;A-Xing Zhu;A-Xing Zhu;Karsten Schmidt;Thomas Scholten

  • Digital soil mapping using artificial neural networks

    Thorsten Behrens;Helga Förster;Thomas Scholten;Ulrich Steinrücken

  • An approach to computing topographic wetness index based on maximum downslope gradient

    Cheng-Zhi Qin;A-Xing Zhu;Tao Pei;Bao-Lin Li

  • Improving the Spatial Prediction of Soil Organic Carbon Content in Two Contrasting Climatic Regions by Stacking Machine Learning Models and Rescanning Covariate Space

    Ruhollah Taghizadeh-Mehrjardi;Karsten Schmidt;Alireza Amirian-Chakan;Tobias Rentschler

  • Continental-scale soil carbon composition and vulnerability modulated by regional environmental controls

    R. A. Viscarra Rossel;R. A. Viscarra Rossel;J. Lee;J. Lee;T. Behrens;Z. Luo

  • Spatial modelling with Euclidean distance fields and machine learning

    T. Behrens;K. Schmidt;R. A. Viscarra Rossel;P. Gries

  • Digital soil mapping in Germany—a review

    Thorsten Behrens;Thomas Scholten

  • Assimilating satellite imagery and visible-near infrared spectroscopy to model and map soil loss by water erosion in Australia

    Hongfen Teng;Raphael A. Viscarra Rossel;Zhou Shi;Thorsten Behrens

  • Multi-scale digital soil mapping with deep learning.

    Thorsten Behrens;Karsten Schmidt;Robert A. MacMillan;Raphael A. Viscarra Rossel

  • Predictive soil mapping with limited sample data

    A. X. Zhu;J. Liu;F. Du;S. J. Zhang

  • Hyper-scale digital soil mapping and soil formation analysis

    Thorsten Behrens;Karsten Schmidt;Leonardo Ramirez-Lopez;John Gallant

  • Sampling optimal calibration sets in soil infrared spectroscopy

    Leonardo Ramirez-Lopez;Leonardo Ramirez-Lopez;Leonardo Ramirez-Lopez;Karsten Schmidt;Thorsten Behrens;Bas van Wesemael

  • Improving the spatial prediction of soil salinity in arid regions using wavelet transformation and support vector regression models

    Ruhollah Taghizadeh-Mehrjardi;Karsten Schmidt;Norair Toomanian;Brandon Heung

  • Multi-task convolutional neural networks outperformed random forest for mapping soil particle size fractions in central Iran

    R. Taghizadeh-Mehrjardi;M. Mahdianpari;F. Mohammadimanesh;T. Behrens

  • Distance and similarity-search metrics for use with soil vis-NIR spectra

    L. Ramirez-Lopez;L. Ramirez-Lopez;T. Behrens;K. Schmidt;R.A. Viscarra Rossel

  • Assessing the USLE crop and management factor C for soil erosion modeling in a large mountainous watershed in Central China

    Sarah Schönbrodt;Patrick Saumer;Thorsten Behrens;Christoph Seeber

Frequent Co-Authors

Thomas Scholten
Thomas Scholten University of Tübingen
Karsten Schmidt
Karsten Schmidt University of Tübingen
Peter Dietrich
Peter Dietrich University of Tübingen
A-Xing Zhu
A-Xing Zhu University of Wisconsin–Madison
R. A. Viscarra Rossel
R. A. Viscarra Rossel Curtin University
Xuezheng Shi
Xuezheng Shi Chinese Academy of Sciences
José Alexandre Melo Demattê
José Alexandre Melo Demattê Universidade de São Paulo
Bas van Wesemael
Bas van Wesemael Université Catholique de Louvain
Zhou Shi
Zhou Shi Zhejiang University
Peter Kühn
Peter Kühn University of Tübingen

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