World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
51
Citations
18301
World Ranking
4628
National Ranking
356

Philip Lewis 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 Philip Lewis 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: 282 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: 26 scientists 501–510 publications: 17 scientists 511–520 publications: 19 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 681–689 publications: 4 scientists 690+ publications: 100 scientists
41 publications 690+

This scientist: 214 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 690 publications or more.

Philip Lewis 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 Philip Lewis 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: 198 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: 20 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: 9 scientists 126+ D-Index: 92 scientists
30 D-Index 126+

This scientist: 51 D-Index — 52nd percentile

52% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 126 D-Index or more.

Overview

Philip Lewis is affiliated with University College London in the United Kingdom. Their research primarily spans the fields of Environmental Science and Agricultural and Biological Sciences, with a significant focus on subfields such as Ecology, Global and Planetary Change, Plant Science, Nature and Landscape Conservation, and Environmental Engineering.

The scientist's work covers a range of topics including Remote Sensing in Agriculture, Leaf Properties and Growth Measurement, Remote Sensing and LiDAR Applications, Climate Change Impacts on Agriculture, Land Use and Ecosystem Services, Atmospheric Aerosols and Clouds, as well as Atmospheric and Environmental Gas Dynamics.

Among their recent publications are:

  • Bayesian atmospheric correction over land: Sentinel-2/MSI and Landsat 8/OLI, 2022, published in Geoscientific Model Development
  • Assessment of Bias in Pan-Tropical Biomass Predictions, 2020, published in Frontiers in Forests and Global Change
  • Linking Remote Sensing with APSIM through Emulation and Bayesian Optimization to Improve Yield Prediction, 2022, published in Remote Sensing
  • Location, biophysical and agronomic parameters for croplands in northern Ghana, 2022, published in Earth System Science Data
  • Linking Remote Sensing with APSIM through Emulation and Bayesian Optimization to Improve Maize Yield Prediction in the U.S Midwest, 2022, published in Preprints.org

Frequent co-authors collaborating with Philip Lewis include José Gómez-Dans, Feng Yin, Kofi Asare, Patrick Lamptey, and Kenneth Aidoo.

The scientist often publishes in venues such as Zenodo (CERN European Organization for Nuclear Research), Geoscientific Model Development, Frontiers in Forests and Global Change, Remote Sensing, and Earth System Science Data.

Best Publications

  • First operational BRDF, albedo nadir reflectance products from MODIS

    Crystal B Schaaf;Feng Gao;Alan H Strahler;Wolfgang Lucht

  • The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research

    C.O. Justice;E. Vermote;J.R.G. Townshend;R. Defries

  • Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data

    Pasi Raumonen;Mikko Kaasalainen;Markku Åkerblom;Sanna Kaasalainen

  • Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data

    David P. Roy;Y. Jin;P. E. Lewis;C. O. Justice

  • Multi-temporal MODIS-Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data

    David P. Roy;David P. Roy;Junchang Ju;Junchang Ju;Philip Lewis;Philip Lewis;Crystal Schaaf;Crystal Schaaf

  • Retrieval and global assessment of terrestrial chlorophyll fluorescence from GOSAT space measurements

    Luis Guanter;Luis Guanter;Christian Frankenberg;Anu Dudhia;Philip E. Lewis

  • Burned area mapping using multi-temporal moderate spatial resolution data—a bi-directional reflectance model-based expectation approach

    D.P. Roy;D.P. Roy;P.E. Lewis;C.O. Justice

  • Hyperspectral remote sensing of foliar nitrogen content.

    Yuri Knyazikhin;Mitchell A. Schull;Pauline Stenberg;Matti Mõttus

  • Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

    Jochem Verrelst;Zbynek Malenovsky;Zbynek Malenovsky;Christiaan van der Tol;Gustau Camps-Valls

  • Assimilation of remote sensing into crop growth models: Current status and perspectives

    Jianxi Huang;Jose L. Gómez-Dans;Hai Huang;Hongyuan Ma

  • Global retrieval of bidirectional reflectance and albedo over land from EOS MODIS and MISR data: Theory and algorithm

    W. Wanner;A. H. Strahler;B. Hu;P. Lewis

  • Geostatistical classification for remote sensing: an introduction

    P. M. Atkinson;P. Lewis

  • A general method to normalize Landsat reflectance data to nadir BRDF adjusted reflectance

    David P. Roy;Hankui Zhang;Junchang Ju;Junchang Ju;Jose Luis Gomez-Dans

  • Developments in the 'validation' of satellite sensor products for the study of the land surface

    C. Justice;A. Belward;J. Morisette;P. Lewis

  • Third Radiation Transfer Model Intercomparison (RAMI) exercise: Documenting progress in canopy reflectance models

    Jean-Luc Widlowski;Malcolm Taberner;Bernard Pinty;Véronique Bruniquel-Pinel

  • Can we measure terrestrial photosynthesis from space directly, using spectral reflectance and fluorescence?

    J Grace;C Nichol;M Disney;P Lewis

  • 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

  • Evaluation of regional estimates of winter wheat yield by assimilating three remotely sensed reflectance datasets into the coupled WOFOST–PROSAIL model

    Jianxi Huang;Hongyuan Ma;Fernando Sedano;Philip Lewis

  • Radiation Transfer Model Intercomparison (RAMI) exercise: Results from the second phase

    B. Pinty;J.-L. Widlowski;M. Taberner;N. Gobron

  • 3d modelling of forest canopy structure for remote sensing simulations in the optical and microwave domains

    M. Disney;P. Lewis;P. Saich

  • Theoretical noise sensitivity of BRDF and albedo retrieval from the EOS-MODIS and MISR sensors with respect to angular sampling

    W. Lucht;P. Lewis

Frequent Co-Authors

Mathias Disney
Mathias Disney University College London
Jeffrey V. Rosenfeld
Jeffrey V. Rosenfeld Monash University
Jan-Peter Muller
Jan-Peter Muller University College London
Tristan Quaife
Tristan Quaife University of Reading
Alan H. Strahler
Alan H. Strahler Boston University
Crystal B. Schaaf
Crystal B. Schaaf University of Massachusetts Boston
David P. Roy
David P. Roy Michigan State University
D. Denisov
D. Denisov Fermilab
Greg Landsberg
Greg Landsberg Brown University
A. P. Heinson
A. P. Heinson University of California, Riverside

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Related Online Degrees & Career Pathways

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Lastly, prospective students aiming for a smoother academic journey may seek out the easy bachelor's degree options that align with environmental interests. These programs can provide a manageable pathway to earning a degree while gaining foundational knowledge in the field.

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