World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
42
Citations
7480
World Ranking
7363
National Ranking
4

Martin Schlerf 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 Martin Schlerf 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: 130 publications — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Martin Schlerf 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 Martin Schlerf 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: 42 D-Index — 25th percentile

25% of scientists in this discipline score the same or lower.

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

Overview

Martin Schlerf is affiliated with the Luxembourg Institute of Science and Technology in Luxembourg. Their research primarily focuses on environmental science, with extensive contributions across several interconnected subfields.

The main fields of study for Schlerf include:

  • Environmental Science

Their work spans numerous subfields, such as:

  • Ecology
  • Environmental Engineering
  • Global and Planetary Change
  • Plant Science
  • Atmospheric Science

Schlerf's research topics emphasize aspects related to remote sensing applications in environmental and agricultural contexts. The primary topics covered include:

  • Remote Sensing in Agriculture
  • Plant Water Relations and Carbon Dynamics
  • Urban Heat Island Mitigation
  • Remote Sensing and LiDAR Applications
  • Leaf Properties and Growth Measurement
  • Species Distribution and Climate Change
  • Tree-ring Climate Responses

Their frequent co-authors throughout multiple publications are:

  • Miriam Machwitz
  • Kaniska Mallick
  • Katja Berger
  • Jochem Verrelst
  • Anne J. Hoek van Dijke

Schlerf has published multiple papers in a variety of publication venues, with repeated contributions to:

  • Remote Sensing of Environment
  • International Journal of Applied Earth Observation and Geoinformation
  • Biogeosciences
  • Precision Agriculture
  • Nature Geoscience

Notable recent papers authored or co-authored by Martin Schlerf include:

  • "Shifts in regional water availability due to global tree restoration," 2022, Nature Geoscience
  • "Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review," 2022, Remote Sensing of Environment
  • "Thermal infrared remote sensing of vegetation: Current status and perspectives," 2021, International Journal of Applied Earth Observation and Geoinformation
  • "Examining the link between vegetation leaf area and land-atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data," 2020, Biogeosciences
  • "Comparison of Crop Trait Retrieval Strategies Using UAV-Based VNIR Hyperspectral Imaging," 2021, Remote Sensing

Best Publications

  • Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland

    Roshanak Darvishzadeh;Andrew Skidmore;Martin Schlerf;Clement Atzberger

  • LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements

    Roshanak Darvishzadeh;Andrew Skidmore;Martin Schlerf;Clement Atzberger

  • Remote sensing of forest biophysical variables using HyMap imaging spectrometer data

    Martin Schlerf;Clement Atzberger;Joachim Hill

  • Shifts in regional water availability due to global tree restoration

    Unknown

  • Inversion of a forest reflectance model to estimate structural canopy variables from hyperspectral remote sensing data

    Martin Schlerf;Clement Atzberger

  • Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

    Unknown

  • Challenges and Future Perspectives of Multi-/Hyperspectral Thermal Infrared Remote Sensing for Crop Water-Stress Detection: A Review

    Max Gerhards;Martin Schlerf;Kaniska Mallick;Thomas Udelhoven

  • Mapping grassland leaf area index with airborne hyperspectral imagery : a comparison study of statistical approaches and inversion of radiative transfer models

    Roshanak Darvishzadeh;Clement Atzberger;Andrew Skidmore;Martin Schlerf

  • The fourth phase of the radiative transfer model intercomparison (RAMI) exercise: Actual canopy scenarios and conformity testing

    Jean Luc Widlowski;Corrado Mio;Mathias Disney;Jennifer Adams

  • Regional estimation of savanna grass nitrogen using the red-edge band of the spaceborne RapidEye sensor

    Abel Ramoelo;Abel Ramoelo;Andrew K. Skidmore;Moses Azong Cho;Martin Schlerf

  • Retrieval of chlorophyll and nitrogen in Norway spruce (Picea abies L. Karst.) using imaging spectroscopy

    Martin Schlerf;Clement Atzberger;Joachim Hill;Henning Buddenbaum

  • Comparative analysis of different retrieval methods for mapping grassland leaf area index using airborne imaging spectroscopy

    Clement Atzberger;Roshanak Darvishzadeh;Markus Immitzer;Martin Schlerf

  • Classification of coniferous tree species and age classes using hyperspectral data and geostatistical methods

    H. Buddenbaum;M. Schlerf;J. Hill

  • Mapping spatio-temporal variation of grassland quantity and quality using MERIS data and the PROSAIL model

    Yali Si;Yali Si;Martin Schlerf;Raul Zurita-Milla;Andrew Skidmore

  • The fourth radiation transfer model intercomparison (RAMI-IV): Proficiency testing of canopy reflectance models with ISO-13528

    J. L. Widlowski;B. Pinty;M. Lopatka;C. Atzberger

  • Simple and robust methods for remote sensing of canopy chlorophyll content: a comparative analysis of hyperspectral data for different types of vegetation.

    Yoshio Inoue;Martine Guérif;Frédéric Baret;Andrew Skidmore

  • Water stress detection in potato plants using leaf temperature, emissivity, and reflectance

    Max Gerhards;Gilles Rock;Martin Schlerf;Thomas Udelhoven

  • Identifying plant species using mid-wave infrared (2.5–6μm) and thermal infrared (8–14μm) emissivity spectra

    Saleem Ullah;Saleem Ullah;Martin Schlerf;Andrew K. Skidmore;Christoph Hecker

  • Water-removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations

    Abel Ramoelo;Abel Ramoelo;Andrew K. Skidmore;Martin Schlerf;Renaud Mathieu

  • Non-linear partial least square regression increases the estimation accuracy of grass nitrogen and phosphorus using in situ hyperspectral and environmental data

    Abel Ramoelo;Abel Ramoelo;AK Skidmore;Moses A Cho;Renaud Sa Mathieu

  • Hyperspectral analysis of mangrove foliar chemistry using PLSR and support vector regression

    Christoffer Axelsson;AndrewK. Skidmore;Martin Schlerf;Anas Fauzi

  • Estimation of grassland biomass and nitrogen using MERIS data

    Saleem Ullah;Yali Si;Martin Schlerf;Andrew K. Skidmore

Frequent Co-Authors

Andrew K. Skidmore
Andrew K. Skidmore University of Twente
Clement Atzberger
Clement Atzberger BOKU University
Roshanak Darvishzadeh
Roshanak Darvishzadeh University of Twente
Joachim Hill
Joachim Hill University of Trier
Moses Azong Cho
Moses Azong Cho Council for Scientific and Industrial Research
Renaud Mathieu
Renaud Mathieu International Rice Research Institute
Tiejun Wang
Tiejun Wang University of Twente
Martin Herold
Martin Herold Wageningen University & Research
Ignas M. A. Heitkönig
Ignas M. A. Heitkönig Wageningen University & Research
Lucien Hoffmann
Lucien Hoffmann Luxembourg Institute of Science and Technology

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