World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
9230
World Ranking
7893
National Ranking
76

Martino Pesaresi 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 Martino Pesaresi 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 115 publications — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Martino Pesaresi 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 Martino Pesaresi sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Martino Pesaresi is affiliated with the European Commission Joint Research Centre in Belgium. Their research primarily focuses on Environmental Science, with significant contributions to subfields including Global and Planetary Change, Environmental Engineering, Building and Construction, Ecology, and Atmospheric Science.

The main topics of Pesaresi's work cover a range of areas related to land use and remote sensing. These include:

  • Land Use and Ecosystem Services
  • Remote Sensing and LiDAR Applications
  • Remote Sensing in Agriculture
  • Remote Sensing and Land Use
  • Urban Transport and Accessibility
  • Impact of Light on Environment and Health
  • Remote-Sensing Image Classification

Pesaresi's publication record includes several papers in notable venues. Some of the recent papers are:

  • "Applying the Degree of Urbanisation to the globe: A new harmonised definition reveals a different picture of global urbanisation," 2020, Journal of Urban Economics
  • "Big Earth Data science: an information framework for a sustainable planet," 2020, International Journal of Digital Earth
  • "Global long-term mapping of surface temperature shows intensified intra-city urban heat island extremes," 2021, Global Environmental Change
  • "Land use efficiency of functional urban areas: Global pattern and evolution of development trajectories," 2022, Habitat International
  • "Advances on the Global Human Settlement Layer by joint assessment of Earth Observation and population survey data," 2024, International Journal of Digital Earth

Their frequent co-authors include Thomas Kemper, Michele Melchiorri, Christina Corbane, Marcello Schiavina, and Sérgio Freire. These collaborations reflect a diverse network within their research community.

Pesaresi has published in several academic venues, with a majority of their work appearing in the Joint Research Centre (European Commission), the International Journal of Digital Earth, Scientific Data, Data in Brief, and the Journal of Urban Economics.

Best Publications

  • A new approach for the morphological segmentation of high-resolution satellite imagery

    M. Pesaresi;J.A. Benediktsson

  • Classification and feature extraction for remote sensing images from urban areas based on morphological transformations

    J.A. Benediktsson;M. Pesaresi;K. Amason

  • A Global Human Settlement Layer From Optical HR/VHR RS Data: Concept and First Results

    Martino Pesaresi;Guo Huadong;Xavier Blaes;Daniele Ehrlich

  • Next-generation Digital Earth

    Michael F. Goodchild;Huadong Guo;Alessandro Annoni;Ling Bian

  • Advances in mathematical morphology applied to geoscience and remote sensing

    P. Soille;M. Pesaresi

  • A Robust Built-Up Area Presence Index by Anisotropic Rotation-Invariant Textural Measure

    Martino Pesaresi;Andrea Gerhardinger;FranÇois Kayitakire

  • The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use

    Stefan Leyk;Andrea E. Gaughan;Andrea E. Gaughan;Susana B. Adamo;Alex de Sherbinin

  • Digital Earth 2020: towards the vision for the next decade

    Max Craglia;Kees de Bie;Davina Jackson;Martino Pesaresi

  • Convolutional neural networks for global human settlements mapping from Sentinel-2 satellite imagery

    Christina Corbane;Vasileios Syrris;Filip Sabo;Panagiotis Politis

  • Assessment of the Added-Value of Sentinel-2 for Detecting Built-up Areas

    Martino Pesaresi;Christina Corbane;Andreea Julea;Aneta J. Florczyk

  • Unveiling 25 Years of Planetary Urbanization with Remote Sensing: Perspectives from the Global Human Settlement Layer

    Michele Melchiorri;Aneta J. Florczyk;Sergio Freire;Marcello Schiavina

  • Automated global delineation of human settlements from 40 years of Landsat satellite data archives

    Christina Corbane;Martino Pesaresi;Thomas Kemper;Panagiotis Politis

  • Principles and Applications of the Global Human Settlement Layer as Baseline for the Land Use Efficiency Indicator—SDG 11.3.1

    Michele Melchiorri;Martino Pesaresi;Aneta J. Florczyk;Christina Corbane

  • Texture Analysis for Urban Pattern Recognition Using Fine-resolution Panchromatic Satellite Imagery

    Martino Pesaresi

  • Identifying damage caused by the 2008 Wenchuan earthquake from VHR remote sensing data

    Daniele Ehrlich;Huadong Guo;Katrin Molch;J. W. Ma

  • Big earth data analytics on Sentinel-1 and Landsat imagery in support to global human settlements mapping

    Christina Corbane;Martino Pesaresi;Panagiotis Politis;Vasileios Syrris

  • The recognition of road network from high‐resolution satellite remotely sensed data using image morphological characteristics

    C. Zhu;Wen Zhong Shi;M. Pesaresi;L. Liu

  • Big Earth Data Science: an Information Framework for a Sustainable Planet

    Huadong Guo;Stefano Nativi;Dong Liang;Max Craglia

  • Rapid damage assessment of built-up structures using VHR satellite data in tsunami-affected areas

    M. Pesaresi;A. Gerhardinger;F. Haag

  • Urban Observing Sensors

    Q. Weng;P. Gamba;G. Mountrakis;M. Pesaresi

  • GHS-BUILT R2015B - GHS built-up confidence grid, derived from Landsat, multitemporal (1975, 1990, 2000, 2014)

    Martino Pesaresi;Daniele Ehrlich;Aneta Florczyk;Sergio Freire

  • The global human settlement layer from landsat imagery

    M. Pesaresi;D. Ehrlich;A. J. Florczyk;S. Freire

Frequent Co-Authors

Pierre Soille
Pierre Soille Joint Research Centre
Huadong Guo
Huadong Guo Chinese Academy of Sciences
Jon Atli Benediktsson
Jon Atli Benediktsson University of Iceland
Michael F. Goodchild
Michael F. Goodchild University of California, Santa Barbara
Richard J. Simpson
Richard J. Simpson La Trobe University
Chao Ren
Chao Ren University of Hong Kong
Luc Feyen
Luc Feyen Stanford University
Hannes Taubenböck
Hannes Taubenböck German Aerospace Center
Alex de Sherbinin
Alex de Sherbinin Columbia University
Alexander Baklanov
Alexander Baklanov University of Copenhagen

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