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Ecology and Evolution
Norway
2026
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Environmental Sciences
Norway
2025

D-Index & Metrics

Ecology and Evolution

D-Index
86
Citations
27482
World Ranking
587
National Ranking
8

Erik Næsset publication distribution in Ecology and Evolution in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Ecology and Evolution in 2026. The highlighted bar marks where Erik Næsset sits on this spectrum.

37–41 publications: 2 scientists 42–46 publications: 9 scientists 47–51 publications: 10 scientists 52–56 publications: 31 scientists 57–61 publications: 56 scientists 62–66 publications: 91 scientists 67–71 publications: 92 scientists 72–76 publications: 127 scientists 77–81 publications: 173 scientists 82–86 publications: 236 scientists 87–91 publications: 227 scientists 92–96 publications: 240 scientists 97–101 publications: 333 scientists 102–106 publications: 280 scientists 107–111 publications: 300 scientists 112–116 publications: 285 scientists 117–121 publications: 305 scientists 122–126 publications: 287 scientists 127–131 publications: 278 scientists 132–136 publications: 289 scientists 137–141 publications: 273 scientists 142–146 publications: 262 scientists 147–151 publications: 246 scientists 152–156 publications: 235 scientists 157–161 publications: 205 scientists 162–166 publications: 199 scientists 167–171 publications: 174 scientists 172–176 publications: 164 scientists 177–181 publications: 173 scientists 182–186 publications: 189 scientists 187–191 publications: 170 scientists 192–196 publications: 139 scientists 197–201 publications: 128 scientists 202–206 publications: 117 scientists 207–211 publications: 115 scientists 212–216 publications: 107 scientists 217–221 publications: 124 scientists 222–226 publications: 81 scientists 227–231 publications: 82 scientists 232–236 publications: 85 scientists 237–241 publications: 75 scientists 242–246 publications: 66 scientists 247–251 publications: 81 scientists 252–256 publications: 69 scientists 257–261 publications: 70 scientists 262–266 publications: 55 scientists 267–271 publications: 64 scientists 272–276 publications: 49 scientists 277–281 publications: 48 scientists 282–286 publications: 44 scientists 287–291 publications: 45 scientists 292–296 publications: 36 scientists 297–301 publications: 39 scientists 302–306 publications: 38 scientists 307–311 publications: 30 scientists 312–316 publications: 34 scientists 317–321 publications: 25 scientists 322–326 publications: 22 scientists 327–331 publications: 28 scientists 332–336 publications: 30 scientists 337–341 publications: 22 scientists 342–346 publications: 30 scientists 347–351 publications: 26 scientists 352–356 publications: 22 scientists 357–361 publications: 29 scientists 362–366 publications: 21 scientists 367–371 publications: 12 scientists 372–376 publications: 18 scientists 377–381 publications: 17 scientists 382–386 publications: 13 scientists 387–391 publications: 21 scientists 392–396 publications: 13 scientists 397–401 publications: 10 scientists 402–406 publications: 15 scientists 407–411 publications: 8 scientists 412–416 publications: 9 scientists 417–421 publications: 8 scientists 422–426 publications: 4 scientists 427–431 publications: 10 scientists 432–436 publications: 10 scientists 437–441 publications: 5 scientists 442–446 publications: 4 scientists 447–451 publications: 10 scientists 452–456 publications: 2 scientists 457–461 publications: 4 scientists 462–466 publications: 7 scientists 467–471 publications: 7 scientists 472–476 publications: 6 scientists 477–481 publications: 6 scientists 482–486 publications: 3 scientists 487–491 publications: 3 scientists 492–496 publications: 4 scientists 497–501 publications: 4 scientists 502–506 publications: 8 scientists 507–511 publications: 5 scientists 512–516 publications: 4 scientists 517–521 publications: 5 scientists 522–526 publications: 4 scientists 527–530 publications: 5 scientists 531+ publications: 100 scientists
37 publications 531+

This scientist: 312 publications — 92nd percentile

92% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 531 publications or more.

Erik Næsset D-index placement in Ecology and Evolution in 2026

The chart shows the D-index (discipline H-index) distribution of Ecology and Evolution scientists ranked by Research.com in 2026. The highlighted bar marks where Erik Næsset sits on this spectrum.

30 D-Index: 95 scientists 31 D-Index: 123 scientists 32 D-Index: 191 scientists 33 D-Index: 245 scientists 34 D-Index: 252 scientists 35 D-Index: 244 scientists 36 D-Index: 249 scientists 37 D-Index: 244 scientists 38 D-Index: 254 scientists 39 D-Index: 254 scientists 40 D-Index: 280 scientists 41 D-Index: 274 scientists 42 D-Index: 266 scientists 43 D-Index: 233 scientists 44 D-Index: 248 scientists 45 D-Index: 208 scientists 46 D-Index: 201 scientists 47 D-Index: 213 scientists 48 D-Index: 207 scientists 49 D-Index: 172 scientists 50 D-Index: 209 scientists 51 D-Index: 199 scientists 52 D-Index: 153 scientists 53 D-Index: 169 scientists 54 D-Index: 163 scientists 55 D-Index: 148 scientists 56 D-Index: 120 scientists 57 D-Index: 146 scientists 58 D-Index: 137 scientists 59 D-Index: 140 scientists 60 D-Index: 104 scientists 61 D-Index: 119 scientists 62 D-Index: 118 scientists 63 D-Index: 99 scientists 64 D-Index: 77 scientists 65 D-Index: 100 scientists 66 D-Index: 86 scientists 67 D-Index: 83 scientists 68 D-Index: 75 scientists 69 D-Index: 94 scientists 70 D-Index: 57 scientists 71 D-Index: 68 scientists 72 D-Index: 59 scientists 73 D-Index: 63 scientists 74 D-Index: 66 scientists 75 D-Index: 60 scientists 76 D-Index: 42 scientists 77 D-Index: 49 scientists 78 D-Index: 39 scientists 79 D-Index: 37 scientists 80 D-Index: 43 scientists 81 D-Index: 41 scientists 82 D-Index: 45 scientists 83 D-Index: 34 scientists 84 D-Index: 40 scientists 85 D-Index: 35 scientists 86 D-Index: 55 scientists 87 D-Index: 24 scientists 88 D-Index: 24 scientists 89 D-Index: 30 scientists 90 D-Index: 23 scientists 91 D-Index: 25 scientists 92 D-Index: 27 scientists 93 D-Index: 27 scientists 94 D-Index: 13 scientists 95 D-Index: 23 scientists 96 D-Index: 12 scientists 97 D-Index: 14 scientists 98 D-Index: 19 scientists 99 D-Index: 16 scientists 100 D-Index: 14 scientists 101 D-Index: 5 scientists 102 D-Index: 21 scientists 103 D-Index: 16 scientists 104 D-Index: 10 scientists 105 D-Index: 7 scientists 106 D-Index: 7 scientists 107 D-Index: 7 scientists 108 D-Index: 6 scientists 109 D-Index: 9 scientists 110 D-Index: 11 scientists 111 D-Index: 12 scientists 112 D-Index: 9 scientists 113 D-Index: 7 scientists 114 D-Index: 3 scientists 115 D-Index: 8 scientists 116 D-Index: 5 scientists 117 D-Index: 11 scientists 118 D-Index: 4 scientists 119 D-Index: 2 scientists 120 D-Index: 5 scientists 121+ D-Index: 100 scientists
30 D-Index 121+

This scientist: 86 D-Index — 93rd percentile

93% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 121 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Ecology and Evolution in Norway Leader Award
  • 2025 - Research.com Environmental Sciences in Norway Leader Award
  • 2023 - Research.com Environmental Sciences in Norway Leader Award
  • 2022 - Research.com Environmental Sciences in Norway Leader Award

Overview

Erik Næsset is affiliated with the Norwegian University of Life Sciences in Norway. Their research primarily falls within the field of Environmental Science, with significant contributions to Environmental Engineering, Nature and Landscape Conservation, and Ecology. Additional focus areas include Global and Planetary Change and Insect Science.

The scientist's work centers on Remote Sensing and LiDAR Applications, with substantial output related to forest ecology and management. Further research topics encompass Remote Sensing in Agriculture, Forest Ecology and Biodiversity Studies, Tree-ring climate responses, Forest Management and Policy, and Fire effects on ecosystems.

Næsset's recent publications include:

  • Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission, 2022, Remote Sensing of Environment
  • Remote sensing in forestry: current challenges, considerations and directions, 2023, Forestry An International Journal of Forest Research
  • Comparison of linear regression, k-nearest neighbour and random forest methods in airborne laser-scanning-based prediction of growing stock, 2020, Forestry An International Journal of Forest Research
  • Harvested area did not increase abruptly-how advancements in satellite-based mapping led to erroneous conclusions, 2022, Annals of Forest Science
  • Estimating aboveground biomass density using hybrid statistical inference with GEDI lidar data and Paraguay's national forest inventory, 2023, Environmental Research Letters

Frequent collaborators of Næsset include Terje Gobakken, Hans Ole Ørka, Ole Martin Bollandsås, Ronald E. McRoberts, and Svetlana Saarela.

Their research has been published extensively in several journals, notably Remote Sensing, Remote Sensing of Environment, Silva Fennica, SSRN Electronic Journal, and Forest Ecosystems.

Næsset has contributed to book publications, including the "Aboveground Woody Biomass Product Validation Good Practices Protocol," published by Ghent University in 2021.

Best Publications

  • Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data

    Erik Næsset

  • Lidar sampling for large-area forest characterization: A review

    Michael A. Wulder;Joanne C. White;Ross F. Nelson;Erik Næsset

  • Determination of mean tree height of forest stands using airborne laser scanner data

    Erik Næsset

  • Estimating timber volume of forest stands using airborne laser scanner data

    Erik Næsset

  • Practical large-scale forest stand inventory using a small-footprint airborne scanning laser

    Erik Næsset

  • Laser scanning of forest resources: the nordic experience

    Erik Næsset;Terje Gobakken;Johan Holmgren;Hannu Hyyppä

  • Estimating tree height and tree crown properties using airborne scanning laser in a boreal nature reserve

    Erik Næsset;Tonje Økland

  • An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning

    Harri Kaartinen;Juha Hyyppä;Xiaowei Yu;Mikko Vastaranta

  • Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser

    Erik Næsset;Terje Gobakken

  • Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

    Unknown

  • Comparative testing of single-tree detection algorithms under different types of forest

    Jari Vauhkonen;Liviu Ene;Sandeep Gupta;Johannes Heinzel

  • Estimating tree heights and number of stems in young forest stands using airborne laser scanner data

    Erik Næsset;Kjell-Olav Bjerknes

  • Tree Species Classification in Boreal Forests With Hyperspectral Data

    Michele Dalponte;Hans Ole Orka;Terje Gobakken;Damiano Gianelle

  • Inventory of Small Forest Areas Using an Unmanned Aerial System

    Stefano Puliti;Hans Ole Ørka;Terje Gobakken;Erik Næsset

  • Forestry Applications of Airborne Laser Scanning

    Matti Maltamo;Erik Næsset;Jari Vauhkonen

  • Classifying species of individual trees by intensity and structure features derived from airborne laser scanner data

    Hans Ole Ørka;Erik Næsset;Ole Martin Bollandsås

  • Effects of different sensors, flying altitudes, and pulse repetition frequencies on forest canopy metrics and biophysical stand properties derived from small-footprint airborne laser data

    Erik Næsset

  • Airborne laser scanning as a method in operational forest inventory: Status of accuracy assessments accomplished in Scandinavia

    Erik Næsset

  • Accuracy of forest inventory using airborne laser scanning: evaluating the first nordic full-scale operational project

    Erik Næsset

  • Single Tree Segmentation Using Airborne Laser Scanner Data in a Structurally Heterogeneous Spruce Forest

    Svein Solberg;Erik Naesset;Ole Martin Bollandsas

  • Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data

    Johannes Breidenbach;Erik Næsset;Vegard Lien;Terje Gobakken

Frequent Co-Authors

Terje Gobakken
Terje Gobakken Norwegian University of Life Sciences
Ole Martin Bollandsås
Ole Martin Bollandsås Norwegian University of Life Sciences
Ronald E. McRoberts
Ronald E. McRoberts University of Minnesota
Timothy G. Gregoire
Timothy G. Gregoire Yale University
Svein Solberg
Svein Solberg Norwegian Institute of Bioeconomy Research
Göran Ståhl
Göran Ståhl Swedish University of Agricultural Sciences
Matti Maltamo
Matti Maltamo University of Eastern Finland
Ross Nelson
Ross Nelson Goddard Space Flight Center
Rasmus Astrup
Rasmus Astrup Norwegian Institute of Bioeconomy Research
Michael A. Wulder
Michael A. Wulder Natural Resources Canada

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