World's Best Scientists 2026 revealed!
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Computer Science
UK
2025

D-Index & Metrics

Environmental Sciences

D-Index
95
Citations
44360
World Ranking
468
National Ranking
35

Computer Science

D-Index
95
Citations
43520
World Ranking
455
National Ranking
28

Giles M. Foody publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Giles M. Foody sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 322 publications — 78th percentile

78% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Giles M. Foody D-index placement in Computer Science in 2026

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

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 95 D-Index — 97th percentile

97% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • 2025 - Research.com Computer Science in United Kingdom Leader Award
  • 2023 - Research.com Computer Science in United Kingdom Leader Award
  • 2022 - Research.com Computer Science in United Kingdom Leader Award
  • 2013 - IEEE Fellow For contributions to the remote sensing of land cover

Overview

Giles M. Foody is affiliated with the University of Nottingham in the United Kingdom and specializes in Environmental Science, with a particular emphasis on ecology, global and planetary change, and environmental engineering. Their research spans various interconnected disciplines, including ecological modeling and media technology.

The scientist's work covers a range of topics primarily related to remote sensing applications. These topics include:

  • Remote Sensing in Agriculture
  • Species Distribution and Climate Change
  • Remote-Sensing Image Classification
  • Remote Sensing and LiDAR Applications
  • Land Use and Ecosystem Services
  • Advanced Image Fusion Techniques
  • Flood Risk Assessment and Management

Giles M. Foody has contributed significantly to the academic literature. Recent papers include:

  • "Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification," 2020, Remote Sensing of Environment
  • "Applications in Remote Sensing to Forest Ecology and Management," 2020, One Earth
  • "Spatiotemporal Fusion of Land Surface Temperature Based on a Convolutional Neural Network," 2020, IEEE Transactions on Geoscience and Remote Sensing
  • "Active restoration accelerates the carbon recovery of human-modified tropical forests," 2020, Science
  • "Challenges in the real world use of classification accuracy metrics: From recall and precision to the Matthews correlation coefficient," 2023, PLoS ONE

Their frequent coauthors include:

  • Doreen S. Boyd
  • Yun Du
  • Feng Ling
  • Duccio Rocchini
  • Petra Šímová

The most common venues for their publications comprise:

  • Remote Sensing
  • Remote Sensing of Environment
  • IEEE Transactions on Geoscience and Remote Sensing
  • Zenodo (CERN European Organization for Nuclear Research)
  • Journal of Hydrology

Giles M. Foody was recognized as an IEEE Fellow in 2013 for contributions to the remote sensing of land cover, reflecting a notable aspect of their professional career.

Best Publications

  • Status of land cover classification accuracy assessment

    Giles M. Foody

  • Good practices for estimating area and assessing accuracy of land change

    Pontus Olofsson;Giles M. Foody;Martin Herold;Stephen V. Stehman

  • Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy

    Giles M. Foody

  • A relative evaluation of multiclass image classification by support vector machines

    G.M. Foody;A. Mathur

  • Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation

    Pontus Olofsson;Giles M. Foody;Stephen V. Stehman;Curtis E. Woodcock

  • Feature Selection for Classification of Hyperspectral Data by SVM

    Mahesh Pal;Giles M Foody

  • Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions

    Giles M. Foody;Doreen S. Boyd;Mark E.J. Cutler

  • Toward intelligent training of supervised image classifications: directing training data acquisition for SVM classification

    Giles M. Foody;Ajay Mathur

  • Approaches for the production and evaluation of fuzzy land cover classifications from remotely-sensed data

    Giles M. Foody

  • Key issues in rigorous accuracy assessment of land cover products

    Stephen V. Stehman;Giles M. Foody

  • Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification

    Giles M. Foody

  • The use of small training sets containing mixed pixels for accurate hard image classification: Training on mixed spectral responses for classification by a SVM

    Giles M. Foody;Ajay Mathur

  • Assessing the Accuracy of Remotely Sensed Data: Principles and Practices

    G. Foody

  • Derivation and applications of probabilistic measures of class membership from the maximum-likelihood classification

    G. M. Foody;N. A. Campbell;N. M. Trodd;T. F. Wood

  • Sub-pixel land cover composition estimation using a linear mixture model and fuzzy membership functions

    G. M. Foody;D. P. Cox

  • Measuring and modelling biodiversity from space

    Thomas W. Gillespie;Giles M. Foody;Duccio Rocchini;Ana Paula Giorgi

  • On the compensation for chance agreement in image classification accuracy assessment

    G. M. Foody

  • Multiclass and Binary SVM Classification: Implications for Training and Classification Users

    A. Mathur;G.M. Foody

  • Geographical weighting as a further refinement to regression modelling: An example focused on the NDVI–rainfall relationship

    G.M Foody

  • Harshness in image classification accuracy assessment

    Giles M. Foody

  • An evaluation of some factors affecting the accuracy of classification by an artificial neural network

    G. M. Foody;M. K. Arora

Frequent Co-Authors

Doreen S. Boyd
Doreen S. Boyd University of Nottingham
Paul J. Curran
Paul J. Curran City, University of London
Peter M. Atkinson
Peter M. Atkinson Lancaster University
Linda See
Linda See International Institute for Applied Systems Analysis
Steffen Fritz
Steffen Fritz International Institute for Applied Systems Analysis
Duccio Rocchini
Duccio Rocchini University of Bologna
Richard Lucas
Richard Lucas Aberystwyth University
Carlo Ricotta
Carlo Ricotta Sapienza University of Rome
Harini Nagendra
Harini Nagendra Azim Premji University
Jadunandan Dash
Jadunandan Dash University of Southampton

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