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Environmental Sciences

D-Index
65
Citations
15327
World Ranking
2201
National Ranking
26

Overview

Terje Gobakken is affiliated with the Norwegian University of Life Sciences in Norway. Their research primarily spans the field of Environmental Science, with significant contributions to Environmental Engineering, Nature and Landscape Conservation, Ecology, Global and Planetary Change, and Insect Science.

The scientist's work focuses on a range of topics, particularly in the application of remote sensing and LiDAR technologies alongside forest ecology and management. Their main research topics include:

  • Remote Sensing and LiDAR Applications
  • Forest ecology and management
  • Remote Sensing in Agriculture
  • Forest Ecology and Biodiversity Studies
  • Forest Management and Policy
  • Forest Insect Ecology and Management
  • Land Use and Ecosystem Services

Terje Gobakken has published extensively in several academic venues. The most frequent publication venues are:

  • Silva Fennica
  • Remote Sensing
  • Forestry An International Journal of Forest Research
  • Forest Ecosystems
  • International Journal of Applied Earth Observation and Geoinformation

The scientist collaborates regularly with a number of co-authors whose frequent partnerships include:

  • Erik Næsset
  • Hans Ole Ørka
  • Ole Martin Bollandsås
  • Lennart Noordermeer
  • Svetlana Saarela

Among recent published papers, several demonstrate a focus on biomass density, stock prediction methods, and the use of satellite or airborne laser scanning for forest data analysis:

  • Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission, 2022, Remote Sensing of Environment
  • 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
  • Use of local and global maps of forest canopy height and aboveground biomass to enhance local estimates of biomass in miombo woodlands in Tanzania, 2020, International Journal of Applied Earth Observation and Geoinformation

The research often addresses the integration of local and global forest data to improve biomass estimations, as well as methodological comparisons for forest stock prediction. The body of work contributes to understanding forest ecosystems through advanced remote sensing techniques and ecological modeling frameworks.

Best Publications

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

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

  • Laser scanning of forest resources: the nordic experience

    Erik Næsset;Terje Gobakken;Johan Holmgren;Hannu Hyyppä

  • 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

  • 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

  • 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

  • Tree crown delineation and tree species classification in boreal forests using hyperspectral and ALS data

    Michele Dalponte;Hans Ole Ørka;Liviu Theodor Ene;Terje Gobakken

  • Assessing effects of laser point density, ground sampling intensity, and field sample plot size on biophysical stand properties derived from airborne laser scanner data

    Terje GobakkenT. Gobakken;Erik NæssetE. Næsset

  • Living and dying in a multi‐predator landscape of fear: roe deer are squeezed by contrasting pattern of predation risk imposed by lynx and humans

    Karen Lone;Leif Egil Loe;Terje Gobakken;John D. C. Linnell

  • Estimating forest growth using canopy metrics derived from airborne laser scanner data

    Erik Næsset;Terje Gobakken

  • Model-assisted estimation of biomass in a LiDAR sample survey in Hedmark County, NorwayThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time.

    Timothy G. GregoireT.G. Gregoire;Göran StåhlG. Ståhl;Erik NæssetE. Næsset;Terje GobakkenT. Gobakken

  • Comparing regression methods in estimation of biophysical properties of forest stands from two different inventories using laser scanner data

    Erik Næsset;Ole Martin Bollandsås;Terje Gobakken

  • Model-based inference for biomass estimation in a LiDAR sample survey in Hedmark County, Norway

    Göran StåhlG. Ståhl;Sören HolmS. Holm;Timothy G. GregoireT.G. Gregoire;Terje GobakkenT. Gobakken

  • Estimation of diameter and basal area distributions in coniferous forest by means of airborne laser scanner data

    Terje Gobakken;Erik Næsset

  • Comparing stand inventories for large areas based on photo-interpretation and laser scanning by means of cost-plus-loss analyses

    Tron Eid;Terje Gobakken;Erik Næsset

  • Remote sensing and forest inventories in Nordic countries – roadmap for the future

    Annika Kangas;Rasmus Andreas Astrup;Johannes Breidenbach;Jonas Fridman

  • Model-assisted regional forest biomass estimation using LiDAR and InSAR as auxiliary data: A case study from a boreal forest area

    Erik Næsset;Terje Gobakken;Svein Solberg;Timothy G. Gregoire

  • Inference for lidar-assisted estimation of forest growing stock volume

    Ronald E. McRoberts;Erik Næsset;Terje Gobakken

  • Assessing effects of positioning errors and sample plot size on biophysical stand properties derived from airborne laser scanner data.

    Terje GobakkenT. Gobakken;Erik NæssetE. Næsset

Frequent Co-Authors

Erik Næsset
Erik Næsset Norwegian University of Life Sciences
Ole Martin Bollandsås
Ole Martin Bollandsås Norwegian University of Life Sciences
Timothy G. Gregoire
Timothy G. Gregoire Yale University
Matti Maltamo
Matti Maltamo University of Eastern Finland
Ronald E. McRoberts
Ronald E. McRoberts University of Minnesota
Göran Ståhl
Göran Ståhl Swedish University of Agricultural Sciences
Svein Solberg
Svein Solberg Norwegian Institute of Bioeconomy Research
Ross Nelson
Ross Nelson Goddard Space Flight Center
Birger Solberg
Birger Solberg Norwegian University of Life Sciences
Rasmus Astrup
Rasmus Astrup Norwegian Institute of Bioeconomy Research

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