His primary areas of investigation include Remote sensing, Forest inventory, Lidar, Statistics and Canopy. His Remote sensing study incorporates themes from Biomass, Linear model, Tree, Vegetation and Taiga. His research integrates issues of Mean squared error, Forest resource, Hyperspectral imaging and Random forest in his study of Forest inventory.
His study in the field of Regression analysis, Sampling and Least squares also crosses realms of Hectare. His biological study spans a wide range of topics, including Standard deviation, Physical geography, Deciduous and Laser scanning. His studies deal with areas such as Basal area and Sample as well as Laser scanning.
Terje Gobakken focuses on Remote sensing, Forest inventory, Laser scanning, Statistics and Lidar. He has researched Remote sensing in several fields, including Terrain, Biomass, Canopy, Tree and Vegetation. His study explores the link between Forest inventory and topics such as Basal area that cross with problems in Percentile.
His work in Laser scanning tackles topics such as Transect which are related to areas like Ecotone and Tundra. His Lidar research is multidisciplinary, relying on both Survey sampling, Sample, Linear regression and Interferometric synthetic aperture radar. His Estimator research includes elements of Sampling, Standard error and Econometrics.
Terje Gobakken mainly focuses on Remote sensing, Laser scanning, Forest inventory, Lidar and Statistics. He interconnects Tree, Terrain and Vegetation in the investigation of issues within Remote sensing. His Laser scanning research includes themes of Site index and Forest change.
His Forest inventory research incorporates themes from Diameter at breast height and Environmental resource management. His Lidar study combines topics in areas such as Synthetic aperture radar, Regression analysis, Convolutional neural network and Tree species. In the subject of general Statistics, his work in Mean squared error and Standard error is often linked to Stock, thereby combining diverse domains of study.
Remote sensing, Laser scanning, Forest inventory, Remote sensing and Photogrammetry are his primary areas of study. The concepts of his Remote sensing study are interwoven with issues in Tree and Diameter at breast height. His Laser scanning study integrates concerns from other disciplines, such as Mean squared error, Lidar, Regression analysis and Standard error.
The Forest inventory study combines topics in areas such as Calibration, Basal area and Tree canopy. The study incorporates disciplines such as Value, Sample, Emerging technologies and Value of information in addition to Remote sensing. His Photogrammetry research integrates issues from Terrain and Digital elevation model.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Lidar sampling for large-area forest characterization: A review
Michael A. Wulder;Joanne C. White;Ross F. Nelson;Erik Næsset.
Remote Sensing of Environment (2012)
Laser scanning of forest resources: the nordic experience
Erik Næsset;Terje Gobakken;Johan Holmgren;Hannu Hyyppä.
Scandinavian Journal of Forest Research (2004)
Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser
Erik Næsset;Terje Gobakken.
Remote Sensing of Environment (2008)
Comparative testing of single-tree detection algorithms under different types of forest
Jari Vauhkonen;Liviu Ene;Sandeep Gupta;Johannes Heinzel.
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.
Remote Sensing of Environment (2010)
Tree Species Classification in Boreal Forests With Hyperspectral Data
Michele Dalponte;Hans Ole Orka;Terje Gobakken;Damiano Gianelle.
IEEE Transactions on Geoscience and Remote Sensing (2013)
Inventory of Small Forest Areas Using an Unmanned Aerial System
Stefano Puliti;Hans Ole Ørka;Terje Gobakken;Erik Næsset.
Remote Sensing (2015)
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.
Remote Sensing of Environment (2014)
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.
Canadian Journal of Forest Research (2008)
Estimating forest growth using canopy metrics derived from airborne laser scanner data
Erik Næsset;Terje Gobakken.
Remote Sensing of Environment (2005)
Profile was last updated on December 6th, 2021.
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