World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
35
Citations
4753
World Ranking
9321
National Ranking
562

Karsten Schmidt publication distribution in Environmental Sciences in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Environmental Sciences in 2026. The highlighted bar marks where Karsten Schmidt sits on this spectrum.

41–50 publications: 21 scientists 51–60 publications: 62 scientists 61–70 publications: 133 scientists 71–80 publications: 257 scientists 81–90 publications: 361 scientists 91–100 publications: 440 scientists 101–110 publications: 492 scientists 111–120 publications: 541 scientists 121–130 publications: 617 scientists 131–140 publications: 544 scientists 141–150 publications: 541 scientists 151–160 publications: 539 scientists 161–170 publications: 444 scientists 171–180 publications: 444 scientists 181–190 publications: 400 scientists 191–200 publications: 377 scientists 201–210 publications: 318 scientists 211–220 publications: 283 scientists 221–230 publications: 263 scientists 231–240 publications: 220 scientists 241–250 publications: 217 scientists 251–260 publications: 180 scientists 261–270 publications: 181 scientists 271–280 publications: 155 scientists 281–290 publications: 130 scientists 291–300 publications: 127 scientists 301–310 publications: 130 scientists 311–320 publications: 85 scientists 321–330 publications: 106 scientists 331–340 publications: 80 scientists 341–350 publications: 83 scientists 351–360 publications: 75 scientists 361–370 publications: 69 scientists 371–380 publications: 52 scientists 381–390 publications: 54 scientists 391–400 publications: 56 scientists 401–410 publications: 44 scientists 411–420 publications: 40 scientists 421–430 publications: 36 scientists 431–440 publications: 25 scientists 441–450 publications: 25 scientists 451–460 publications: 32 scientists 461–470 publications: 29 scientists 471–480 publications: 21 scientists 481–490 publications: 26 scientists 491–500 publications: 25 scientists 501–510 publications: 17 scientists 511–520 publications: 18 scientists 521–530 publications: 15 scientists 531–540 publications: 22 scientists 541–550 publications: 12 scientists 551–560 publications: 15 scientists 561–570 publications: 11 scientists 571–580 publications: 19 scientists 581–590 publications: 9 scientists 591–600 publications: 9 scientists 601–610 publications: 7 scientists 611–620 publications: 11 scientists 621–630 publications: 5 scientists 631–640 publications: 5 scientists 641–650 publications: 6 scientists 651–660 publications: 3 scientists 661–670 publications: 3 scientists 671–680 publications: 4 scientists 681–686 publications: 3 scientists 687+ publications: 100 scientists
41 publications 687+

This scientist: 96 publications — 11th percentile

11% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 687 publications or more.

Karsten Schmidt D-index placement in Environmental Sciences in 2026

The chart shows the D-index (discipline H-index) distribution of Environmental Sciences scientists ranked by Research.com in 2026. The highlighted bar marks where Karsten Schmidt sits on this spectrum.

30 D-Index: 12 scientists 31 D-Index: 26 scientists 32 D-Index: 51 scientists 33 D-Index: 88 scientists 34 D-Index: 123 scientists 35 D-Index: 163 scientists 36 D-Index: 206 scientists 37 D-Index: 267 scientists 38 D-Index: 265 scientists 39 D-Index: 275 scientists 40 D-Index: 321 scientists 41 D-Index: 343 scientists 42 D-Index: 305 scientists 43 D-Index: 336 scientists 44 D-Index: 330 scientists 45 D-Index: 348 scientists 46 D-Index: 291 scientists 47 D-Index: 275 scientists 48 D-Index: 272 scientists 49 D-Index: 273 scientists 50 D-Index: 263 scientists 51 D-Index: 232 scientists 52 D-Index: 266 scientists 53 D-Index: 217 scientists 54 D-Index: 199 scientists 55 D-Index: 177 scientists 56 D-Index: 202 scientists 57 D-Index: 204 scientists 58 D-Index: 166 scientists 59 D-Index: 177 scientists 60 D-Index: 166 scientists 61 D-Index: 152 scientists 62 D-Index: 143 scientists 63 D-Index: 150 scientists 64 D-Index: 124 scientists 65 D-Index: 119 scientists 66 D-Index: 120 scientists 67 D-Index: 118 scientists 68 D-Index: 82 scientists 69 D-Index: 98 scientists 70 D-Index: 94 scientists 71 D-Index: 105 scientists 72 D-Index: 74 scientists 73 D-Index: 84 scientists 74 D-Index: 70 scientists 75 D-Index: 67 scientists 76 D-Index: 78 scientists 77 D-Index: 60 scientists 78 D-Index: 59 scientists 79 D-Index: 52 scientists 80 D-Index: 47 scientists 81 D-Index: 38 scientists 82 D-Index: 48 scientists 83 D-Index: 42 scientists 84 D-Index: 42 scientists 85 D-Index: 43 scientists 86 D-Index: 29 scientists 87 D-Index: 37 scientists 88 D-Index: 29 scientists 89 D-Index: 30 scientists 90 D-Index: 34 scientists 91 D-Index: 20 scientists 92 D-Index: 22 scientists 93 D-Index: 17 scientists 94 D-Index: 19 scientists 95 D-Index: 24 scientists 96 D-Index: 21 scientists 97 D-Index: 20 scientists 98 D-Index: 24 scientists 99 D-Index: 17 scientists 100 D-Index: 17 scientists 101 D-Index: 21 scientists 102 D-Index: 25 scientists 103 D-Index: 18 scientists 104 D-Index: 26 scientists 105 D-Index: 19 scientists 106 D-Index: 15 scientists 107 D-Index: 10 scientists 108 D-Index: 13 scientists 109 D-Index: 15 scientists 110 D-Index: 12 scientists 111 D-Index: 8 scientists 112 D-Index: 7 scientists 113 D-Index: 9 scientists 114 D-Index: 6 scientists 115 D-Index: 12 scientists 116 D-Index: 7 scientists 117 D-Index: 8 scientists 118 D-Index: 3 scientists 119 D-Index: 5 scientists 120 D-Index: 7 scientists 121 D-Index: 2 scientists 122 D-Index: 4 scientists 123 D-Index: 8 scientists 124 D-Index: 7 scientists 125+ D-Index: 99 scientists
30 D-Index 125+

This scientist: 35 D-Index — 5th percentile

5% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 125 D-Index or more.

Overview

Karsten Schmidt is affiliated with the University of Tübingen in Germany, where they contribute to research primarily in environmental science and agricultural and biological sciences. Their work is focused on various topics related to soil science and environmental engineering.

The scientist's research spans multiple subfields, including:

  • Environmental Engineering
  • Soil Science
  • Atmospheric Science
  • Civil and Structural Engineering
  • Plant Science

Their main topics of study cover:

  • Soil Geostatistics and Mapping
  • Soil erosion and sediment transport
  • Soil and Unsaturated Flow
  • Soil Carbon and Nitrogen Dynamics
  • Soil Moisture and Remote Sensing
  • Remote Sensing and LiDAR Applications
  • Remote Sensing in Agriculture

Karsten Schmidt has published research in several academic venues. Their frequent publication venues include:

  • Remote Sensing
  • Geoderma
  • Journal of Plant Nutrition and Soil Science
  • Vadose Zone Journal
  • PLoS ONE

Some of the recent papers authored or coauthored by Schmidt are:

  • "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
  • "Enhancing the accuracy of machine learning models using the super learner technique in digital soil mapping," 2021, Geoderma
  • "3D mapping of soil organic carbon content and soil moisture with multiple geophysical sensors and machine learning," 2020, Vadose Zone Journal

Karsten Schmidt frequently collaborates with several researchers, most notably:

  • Thomas Scholten
  • Thorsten Behrens
  • Ruhollah Taghizadeh-Mehrjardi
  • Tobias Rentschler
  • Sandra Teuber

This profile reflects Schmidt's contributions to advancing understanding in soil science and environmental engineering through a combination of machine learning techniques, remote sensing, and geospatial analysis. Their multidisciplinary approach covers significant aspects of soil spatial variability, erosion, moisture, carbon dynamics, and related environmental processes.

Best Publications

  • 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

  • Pedogenesis, permafrost, and soil moisture as controlling factors for soil nitrogen and carbon contents across the Tibetan Plateau

    Frank Baumann;Jin-Sheng He;Karsten Schmidt;Peter Kühn

  • The spectrum-based learner: A new local approach for modeling soil vis–NIR spectra of complex datasets

    Leonardo Ramirez-Lopez;Leonardo Ramirez-Lopez;Thosten Behrens;Karsten Schmidt;Antoine Stevens

  • 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

  • On the combined effect of soil fertility and topography on tree growth in subtropical forest ecosystems - a study from SE China

    Thomas Scholten;Philipp Goebes;Peter Kühn;Steffen Seitz

  • Spatial modelling with Euclidean distance fields and machine learning

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

  • Multi-scale digital soil mapping with deep learning.

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

  • Pedogenic and microbial interrelations to regional climate and local topography: New insights from a climate gradient (arid to humid) along the Coastal Cordillera of Chile

    Nadine Bernhard;Lisa-Marie Moskwa;Karsten Schmidt;Ralf A. Oeser

  • 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

  • Enhancing the accuracy of machine learning models using the super learner technique in digital soil mapping

    Ruhollah Taghizadeh-Mehrjardi;Nikou Hamzehpour;Nikou Hamzehpour;Maryam Hassanzadeh;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

  • The ConMap approach for terrain-based digital soil mapping

    T. Behrens;K. Schmidt;A. X. Zhu;A. X. Zhu;T. Scholten

  • Instance selection and classification tree analysis for large spatial datasets in digital soil mapping

    Karsten Schmidt;Thorsten Behrens;Thomas Scholten

  • Bryophyte-dominated biological soil crusts mitigate soil erosion in an early successional Chinese subtropical forest

    Steffen Seitz;Martin Nebel;Martin Nebel;Philipp Goebes;Kathrin Käppeler

  • Spatio-temporal land use dynamics and soil organic carbon in Swiss agroecosystems

    Felix Stumpf;Armin Keller;Karsten Schmidt;Andreas Mayr

  • Spatial and Temporal Dynamics of Hillslope-Scale Soil Moisture Patterns: Characteristic States and Transition Mechanisms

    Edoardo Martini;Ute Wollschläger;Simon Kögler;Thorsten Behrens

Frequent Co-Authors

Thomas Scholten
Thomas Scholten University of Tübingen
Thorsten Behrens
Thorsten Behrens University of Tübingen
Peter Kühn
Peter Kühn University of Tübingen
Peter Dietrich
Peter Dietrich University of Tübingen
Peter Kuhn
Peter Kuhn University of Southern California
Jin-Sheng He
Jin-Sheng He Peking University
Xuezheng Shi
Xuezheng Shi Chinese Academy of Sciences
Helge Bruelheide
Helge Bruelheide Martin Luther University Halle-Wittenberg
A-Xing Zhu
A-Xing Zhu University of Wisconsin–Madison
Keping Ma
Keping Ma Chinese Academy of Sciences

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