World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
21718
World Ranking
10426
National Ranking
523

Edzer Pebesma 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 Edzer Pebesma 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: 176 publications — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Edzer Pebesma 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 Edzer Pebesma 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Edzer Pebesma is affiliated with the University of Münster in Germany and specializes in environmental science with a focus on global and planetary change, environmental engineering, ecology, ecological modeling, as well as information systems and management. Their research spans multiple intersecting subfields that contribute to understanding environmental systems and their dynamics.

Their scientific work covers diverse main topics including:

  • Species Distribution and Climate Change
  • Atmospheric and Environmental Gas Dynamics
  • Remote Sensing and LiDAR Applications
  • Fire effects on ecosystems
  • Scientific Computing and Data Management
  • Distributed and Parallel Computing Systems
  • Remote Sensing in Agriculture

Edzer Pebesma has contributed to a variety of publications in multiple venues. Frequent publication platforms include:

  • Zenodo (CERN European Organization for Nuclear Research)
  • Remote Sensing
  • Nature Communications
  • Methods in Ecology and Evolution
  • Global Ecology and Biogeography

Recent papers authored or co-authored by Edzer Pebesma cover diverse aspects of environmental science and remote sensing, listed as follows:

  • "Machine learning-based global maps of ecological variables and the challenge of assessing them" (2022, Nature Communications)
  • "The openEO API-Harmonising the Use of Earth Observation Cloud Services Using Virtual Data Cube Functionalities" (2021, Remote Sensing)
  • "Nearest neighbour distance matching Leave-One-Out Cross-Validation for map validation" (2022, Methods in Ecology and Evolution)
  • "Assessing and improving the transferability of current global spatial prediction models" (2023, Global Ecology and Biogeography)
  • "Practical Reproducibility in Geography and Geosciences" (2020, Annals of the American Association of Geographers)

Collaborative research is a substantial part of Edzer Pebesma's scientific activity. Frequent coauthors include:

  • Hanna Meyer
  • Milutin Milenković
  • Johannes Heisig
  • Henning Teickner
  • Yomna Eid

Best Publications

  • Applied Spatial Data Analysis with R

    Roger S. Bivand;Edzer J. Pebesma;Virgilio Gómez-Rubio

  • Simple Features for R: Standardized Support for Spatial Vector Data

    Edzer J. Pebesma

  • Multivariable geostatistics in S: the gstat package $

    Edzer J Pebesma

  • Classes and Methods for Spatial Data

    Edzer Pebesma;Roger Bivand

  • Spatio-Temporal Interpolation using gstat

    Benedikt Gräler;Edzer J. Pebesma;Gerard B. M. Heuvelink

  • Spatial Data Science

    Unknown

  • GSTAT: a program for geostatistical modelling, prediction and simulation

    Edzer J. Pebesma;Cees G. Wesseling

  • Predicting into unknown space? Estimating the area of applicability of spatial prediction models

    Hanna Meyer;Edzer J. Pebesma

  • Real-time automatic interpolation of ambient gamma dose rates from the Dutch radioactivity monitoring network

    Paul H. Hiemstra;Edzer J. Pebesma;Chris J. W. Twenhöfel;Gerard B. M. Heuvelink

  • Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images

    Tomislav Hengl;Gerard B. M. Heuvelink;Melita Perčec Tadić;Edzer J. Pebesma

  • Spatial aggregation and soil process modelling

    Gerard B.M. Heuvelink;Edzer J. Pebesma

  • spacetime: Spatio-Temporal Data in R

    Edzer Pebesma

  • Using Google Earth Engine to detect land cover change: Singapore as a use case

    Nanki Sidhu;Edzer Pebesma;Gilberto Câmara

  • The Importance of Scale in Object-based Mapping of Vegetation Parameters with Hyperspectral Imagery

    Elisabeth A. Addink;Steven M. de Jong;Edzer J. Pebesma

  • Managing uncertainty in integrated environmental modelling: The UncertWeb framework

    Lucy Bastin;Dan Cornford;Richard Jones;Gerard B. M. Heuvelink

  • Automatic Prediction of High-Resolution Daily Rainfall Fields for Multiple Extents: The Potential of Operational Radar

    J.M. Schuurmans;M.F.P. Bierkens;E.J. Pebesma;R. Uijlenhoet

  • Above-ground biomass assessment of Mediterranean forests using airborne imaging spectrometry: the DAIS Peyne experiment

    S. M. De Jong;E. J. Pebesma;B. Lacaze

  • INTAMAP: The design and implementation of an interoperable automated interpolation web service

    Edzer Pebesma;Dan Cornford;Gregoire Dubois;Gerard B. M. Heuvelink

  • Interactive visualization of uncertain spatial and spatio-temporal data under different scenarios: an air quality example

    Edzer J. Pebesma;Kor de Jong;David Briggs

  • A temporal GIS for field based environmental modeling

    Sören Gebbert;Edzer Pebesma

  • The Role of External Variables and GIS Databases in Geostatistical Analysis

    Edzer J Pebesma

  • plotKML: Scientific Visualization of Spatio-Temporal Data

    Tomislav Hengl;Pierre Roudier;Dylan Beaudette;Edzer Pebesma

Frequent Co-Authors

Jan Verbesselt
Jan Verbesselt Wageningen University & Research
Alberto Viglione
Alberto Viglione Polytechnic University of Turin
Wouter Buytaert
Wouter Buytaert Imperial College London
Alfred Stein
Alfred Stein University of Twente
Søren Hansen
Søren Hansen University of Copenhagen
Keith Loague
Keith Loague Stanford University
Piotr Jankowski
Piotr Jankowski San Diego State University
Pierre Soille
Pierre Soille Joint Research Centre

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