World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
63
Citations
14788
World Ranking
2465
National Ranking
69

Jan G. P. W. Clevers 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 Jan G. P. W. Clevers 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: 267 publications — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Jan G. P. W. Clevers 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 Jan G. P. W. Clevers 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: 63 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Overview

What is he best known for?

The fields of study he is best known for:

  • Ecology
  • Statistics
  • Artificial intelligence

His primary areas of study are Remote sensing, Leaf area index, Vegetation, Spectral bands and Red edge. His biological study spans a wide range of topics, including Pixel, Canopy, Water content and Imaging spectrometer. His Leaf area index study combines topics from a wide range of disciplines, such as Multispectral image, Reflectivity, Growing season, Microwave radiometer and Atmospheric radiative transfer codes.

His Vegetation study incorporates themes from Chlorophyll, Agronomy, Spectroradiometer, Temporal resolution and Data stream. The study incorporates disciplines such as Soil water, Soil test, Contamination, Transect and Pollution in addition to Spectral bands. His studies deal with areas such as Enhanced vegetation index, Partial least squares regression, Multivariate statistics and Grassland as well as Red edge.

His most cited work include:

  • Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3 (300 citations)
  • Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review (270 citations)
  • Application of a weighted infrared-red vegetation index for estimating leaf Area Index by Correcting for Soil Moisture (265 citations)

What are the main themes of his work throughout his whole career to date?

Jan G. P. W. Clevers spends much of his time researching Remote sensing, Canopy, Vegetation, Land cover and Leaf area index. His work deals with themes such as Image resolution, Pixel and Imaging spectrometer, which intersect with Remote sensing. The Canopy study combines topics in areas such as Picea abies, Atmospheric radiative transfer codes and Water content.

In Vegetation, Jan G. P. W. Clevers works on issues like Hydrology, which are connected to Arid. His studies in Land cover integrate themes in fields like Cartography and Satellite imagery. His Leaf area index research is multidisciplinary, incorporating perspectives in Photosynthetically active radiation, Chlorophyll and Growing season.

He most often published in these fields:

  • Remote sensing (65.27%)
  • Canopy (17.57%)
  • Vegetation (15.48%)

What were the highlights of his more recent work (between 2014-2020)?

  • Remote sensing (65.27%)
  • Canopy (17.57%)
  • Vegetation (15.48%)

In recent papers he was focusing on the following fields of study:

His primary areas of investigation include Remote sensing, Canopy, Vegetation, Leaf area index and Land cover. Jan G. P. W. Clevers is interested in Zenith, which is a field of Remote sensing. Jan G. P. W. Clevers interconnects Hydrology, Pixel, Silvopasture and Normalized Difference Vegetation Index in the investigation of issues within Canopy.

His research in Vegetation intersects with topics in Random forest, Downscaling, Regression and Time series. His Leaf area index study integrates concerns from other disciplines, such as Photosynthesis, Focus, Growing season and Mean squared error. Jan G. P. W. Clevers combines subjects such as Physical geography and Greenhouse gas with his study of Land cover.

Between 2014 and 2020, his most popular works were:

  • Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review (270 citations)
  • Gross changes in reconstructions of historic land cover/use for Europe between 1900 and 2010 (152 citations)
  • Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods - A comparison (146 citations)

In his most recent research, the most cited papers focused on:

  • Ecology
  • Statistics
  • Artificial intelligence

His main research concerns Remote sensing, Deforestation, Land use, Vegetation and Mean squared error. His Remote sensing study combines topics in areas such as Photosynthesis, Precision agriculture, Chlorophyll, Data stream mining and Data stream. His Deforestation research incorporates themes from Global warming, Climate change, Biomass and Environmental protection.

His study in the field of Land cover and Land use, land-use change and forestry also crosses realms of Data sharing. His work carried out in the field of Vegetation brings together such families of science as Canopy and Data mining. The concepts of his Mean squared error study are interwoven with issues in Nonparametric statistics, Heteroscedasticity, Linear regression, Reflectivity and Leaf area index.

Best Publications

  • Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3

    Jan G. P. W. Clevers;Anatoly A. Gitelson

  • Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review

    Jochem Verrelst;Gustau Camps-Valls;Jordi Muñoz-Marí;Juan Pablo Rivera

  • Application of a weighted infrared-red vegetation index for estimating leaf Area Index by Correcting for Soil Moisture

    J.G.P.W. Clevers

  • Review of optical-based remote sensing for plant trait mapping

    Lucie Homolova;Lucie Homolova;Zbynek Malenovsky;Jan G. P. W Clevers;Glenda Garcia-Santos

  • Algorithm theoretical basis document

    S. Huber;M.E. Schaepman;J.G.P.W. Clevers;Z. Malenovsky

  • Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods - A comparison

    Jochem Verrelst;Juan Pablo Rivera;Frank Veroustraete;Jordi Muñoz-Marí

  • The Derivation of a Simplified Reflectance Model for the Estimation of Leaf Area Index

    J.G.P.W. Clevers

  • Using Hyperspectral Remote Sensing Data for Retrieving Canopy Chlorophyll and Nitrogen Content

    J. G. P. W. Clevers;L. Kooistra

  • Using Sentinel-2 Data for Retrieving LAI and Leaf and Canopy Chlorophyll Content of a Potato Crop

    Jan G. P. W. Clevers;Lammert Kooistra;Marnix M. M. Van den Brande

  • Gross changes in reconstructions of historic land cover/use for Europe between 1900 and 2010

    Richard Fuchs;Martin Herold;Peter H. Verburg;Jan G.P.W. Clevers

  • The robustness of canopy gap fraction estimates from red and near-infrared reflectances: A comparison of approaches

    Frédéric Baret;J.G.P.W. Clevers;M.D. Steven

  • Land use patterns and related carbon losses following deforestation in South America

    V. de Sy;M. Herold;F. Achard;R. Beuchle

  • Unmixing-Based Landsat TM and MERIS FR Data Fusion

    R. Zurita-Milla;J. Clevers;M.E. Schaepman

  • A high-resolution and harmonized model approach for reconstructing and analysing historic land changes in Europe

    R. Fuchs;M. Herold;P. H. Verburg;J. G. P. W. Clevers

  • Estimating canopy water content using hyperspectral remote sensing data

    Jan G. P. W. Clevers;Lammert Kooistra;Michael E. Schaepman

  • Efficiency and accuracy of per-field classification for operational crop mapping

    A. J. W. De Wit;J. G. P. W. Clevers

  • Derivation of the red edge index using the MERIS standard band setting

    J. G. P. W. Clevers;S. M. De Jong;G. F. Epema;F. D. Van Der Meer

  • Identification of soil heavy metal sources and improvement in spatial mapping based on soil spectral information: A case study in northwest China

    Tao Chen;Qingrui Chang;Jing Liu;J.G.P.W. Clevers

  • Retrieving sub-pixel land cover composition through an effective integration of the spatial, spectral and temporal dimensions of MERIS imagery

    R. Zurita Milla;J.G.P.W. Clevers;M.E. Schaepman;A.J. Plaza

  • Basics of remote sensing

    S.M. de Jong;F.D. van der Meer;J.G.P.W. Clevers

Frequent Co-Authors

Michael E. Schaepman
Michael E. Schaepman University of Zurich
Lammert Kooistra
Lammert Kooistra Wageningen University & Research
Harm Bartholomeus
Harm Bartholomeus Wageningen University & Research
Martin Herold
Martin Herold Wageningen University & Research
Andrew K. Skidmore
Andrew K. Skidmore University of Twente
Jochem Verrelst
Jochem Verrelst University of Valencia
Arnold K. Bregt
Arnold K. Bregt Wageningen University & Research
Juha Suomalainen
Juha Suomalainen Wageningen University & Research
Pavel Cudlín
Pavel Cudlín Czech Academy of Sciences
Nuno Carvalhais
Nuno Carvalhais Max Planck Institute for Biogeochemistry

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