World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
5739
World Ranking
11232
National Ranking
95

Teemu Hakala 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 Teemu Hakala 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: 131 publications — 19th percentile

19% of scientists in this discipline score the same or lower.

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

Teemu Hakala 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 Teemu Hakala 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Teemu Hakala is affiliated with the Finnish Geospatial Research Institute in Finland. Their research spans multiple areas within environmental science and engineering, focusing particularly on remote sensing and its diverse applications. The main fields of study include Environmental Science and Engineering, with subfields such as Environmental Engineering, Ecology, Insect Science, Aerospace Engineering, and Nature and Landscape Conservation.

The scientist's work extensively covers topics related to remote sensing technology and its implementation in environmental and forestry studies. Key topics include:

  • Remote Sensing and LiDAR Applications
  • Forest Ecology and Biodiversity Studies
  • Forest Ecology and Management
  • 3D Surveying and Cultural Heritage
  • Remote Sensing in Agriculture
  • Fire Effects on Ecosystems
  • Robotics and Sensor-Based Localization

Among recent publications by Teemu Hakala are works published mainly in well-known journals related to photogrammetry, remote sensing, and environmental monitoring. Selected papers include:

  • Under-canopy UAV laser scanning for accurate forest field measurements, 2020, ISPRS Journal of Photogrammetry and Remote Sensing
  • Comparison of Backpack, Handheld, Under-Canopy UAV, and Above-Canopy UAV Laser Scanning for Field Reference Data Collection in Boreal Forests, 2020, Remote Sensing
  • Machine learning estimators for the quantity and quality of grass swards used for silage production using drone-based imaging spectrometry and photogrammetry, 2020, Remote Sensing of Environment
  • Direct reflectance transformation methodology for drone-based hyperspectral imaging, 2021, Remote Sensing of Environment
  • Effect of small-scale snow surface roughness on snow albedo and reflectance, 2021, The Cryosphere

Teemu Hakala frequently collaborates with various researchers. Notable co-authors include Juha Hyyppä, Antero Kukko, Harri Kaartinen, Eija Honkavaara, and Juha Suomalainen. The collaboration with these co-authors reflects a sustained engagement in multidisciplinary research within the geospatial and remote sensing communities.

The scientist publishes regularly in several reputable venues. The most frequent publication venues are:

  • Remote Sensing
  • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • SSRN Electronic Journal
  • ISPRS Open Journal of Photogrammetry and Remote Sensing
  • ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Best Publications

  • Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight UAV spectral camera for precision agriculture

    Eija Honkavaara;Heikki Saari;Jere Kaivosoja;Ilkka Pölönen

  • Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

    Olli Nevalainen;Eija Honkavaara;Sakari Tuominen;Niko Viljanen

  • Using UAV-based photogrammetry and hyperspectral imaging for mapping bark beetle damage at tree-level

    Roope Näsi;Eija Honkavaara;Päivi Marja Emilia Lyytikäinen-Saarenmaa;Minna Blomqvist

  • Full waveform hyperspectral LiDAR for terrestrial laser scanning

    Teemu Hakala;Juha Suomalainen;Sanna Kaasalainen;Yuwei Chen

  • Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft

    Roope Näsi;Eija Honkavaara;Minna Blomqvist;Päivi Marja Emilia Lyytikäinen-Saarenmaa

  • A Novel Machine Learning Method for Estimating Biomass of Grass Swards Using a Photogrammetric Canopy Height Model, Images and Vegetation Indices Captured by a Drone

    Niko Viljanen;Eija Honkavaara;Roope Näsi;Teemu Hakala

  • Estimating Biomass and Nitrogen Amount of Barley and Grass Using UAV and Aircraft Based Spectral and Photogrammetric 3D Features

    Roope Näsi;Niko Viljanen;Jere Kaivosoja;Katja Alhonoja

  • Under-canopy UAV laser scanning for accurate forest field measurements

    Eric Hyyppä;Juha Hyyppä;Juha Hyyppä;Teemu Hakala;Antero Kukko;Antero Kukko

  • Comparison of Backpack, Handheld, Under-Canopy UAV, and Above-Canopy UAV Laser Scanning for Field Reference Data Collection in Boreal Forests

    Eric Hyyppä;Xiaowei Yu;Harri Kaartinen;Teemu Hakala

  • Two-channel Hyperspectral LiDAR with a Supercontinuum Laser Source

    Yuwei Chen;Esa Räikkönen;Sanna Kaasalainen;Juha Suomalainen

  • Structural and photosynthetic dynamics mediate the response of SIF to water stress in a potato crop

    Shan Xu;Shan Xu;Shan Xu;Jon Atherton;Anu Riikonen;Chao Zhang

  • Polarised bidirectional reflectance factor measurements from soil, stones, and snow

    Jouni Peltoniemi;Teemu Hakala;Juha Suomalainen;Eetu Puttonen

  • SLAM-Aided Stem Mapping for Forest Inventory with Small-Footprint Mobile LiDAR

    Jian Tang;Yuwei Chen;Antero Kukko;Harri Kaartinen

  • Machine learning estimators for the quantity and quality of grass swards used for silage production using drone-based imaging spectrometry and photogrammetry

    Raquel Alves Oliveira;Roope Näsi;Oiva Niemeläinen;Laura Nyholm

  • Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system

    Eija Honkavaara;Jere Kaivosoja;Jussi Mäkynen;Ismo Pellikka

  • Fast and nondestructive method for leaf level chlorophyll estimation using hyperspectral LiDAR

    Olli Nevalainen;Teemu Hakala;Juha Suomalainen;Juha Suomalainen;Raisa Mäkipää

  • Remote Sensing of 3-D Geometry and Surface Moisture of a Peat Production Area Using Hyperspectral Frame Cameras in Visible to Short-Wave Infrared Spectral Ranges Onboard a Small Unmanned Airborne Vehicle (UAV)

    Eija Honkavaara;Matti A. Eskelinen;Ilkka Polonen;Heikki Saari

  • Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

    Ninni Saarinen;Mikko Vastaranta;Roope Näsi;Tomi Rosnell

  • Acquisition of Bidirectional Reflectance Factor Dataset Using a Micro Unmanned Aerial Vehicle and a Consumer Camera

    Teemu Hakala;Juha Suomalainen;Jouni I. Peltoniemi

  • Polarised Multiangular Reflectance Measurements Using the Finnish Geodetic Institute Field Goniospectrometer

    Juha Suomalainen;Teemu Hakala;Jouni Peltoniemi;Eetu Puttonen

  • Tree species classification from fused active hyperspectral reflectance and LIDAR measurements.

    Eetu Puttonen;Juha Suomalainen;Teemu Hakala;Esa Räikkönen

Frequent Co-Authors

Eija Honkavaara
Eija Honkavaara Finnish Geospatial Research Institute
Juha Suomalainen
Juha Suomalainen Wageningen University & Research
Sanna Kaasalainen
Sanna Kaasalainen Finnish Geospatial Research Institute
Harri Kaartinen
Harri Kaartinen University of Turku
Juha Hyyppä
Juha Hyyppä Finnish Geospatial Research Institute
Antero Kukko
Antero Kukko Aalto University
Markus Holopainen
Markus Holopainen University of Helsinki
Mikko Vastaranta
Mikko Vastaranta University of Eastern Finland
Anttoni Jaakkola
Anttoni Jaakkola Finnish Geospatial Research Institute
Hui Zhou
Hui Zhou Huazhong University of Science and Technology

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