Master students

Torjus Birkeland (planned 2025). Detection of trees that pose a risk to power lines.

Mathias Nordhagen (planned 2025). Mapping young forest needs for pre-commercial thinning with airborne laser.

Gerhard Sørensen-Fuglem (planned 2025). Classification of suitability for selective logging with airborne laser.

Kim Andre Anstensen Nielsen (planned 2024). Owning biodiversity: Linking biodiversity indicators and forest ownership.

Jon Endre Bjørnbet (planned 2024). Detection of retention trees using remote sensing.

Folarin Kazeem Olawale (planned 2024). Using satellite data to study spruce performance after an extreme drought on different site conditions and along a climatic gradient.

Silje Helen Røen Gümüs (planned 2024). Using remote sensing for detection potential recruiting veteran oak trees.

Jon Thomas Haugland (2023). Spruce on pine sites – can we detect drought stress by remotely sensed laser data? Project affiliation: Forest4Society

Haakon Kristiansen (2023). Quantifying tree detection in the treeline ecotone: An analysis based on drone-based laser scanning. Project affiliation: ForestPotential

Hanne Torsdatter Petlund (2023). Trees as determinants of soil carbon stock sizes across geographically different treeline ecotones in Norway. Project affiliation: ForestPotential

Håkon Næss Sandum (2023). The effect of reduced area coverage of available calculation cells on the precision of the site index estimate when using the direct method for forest site index estimation.

Tollef Tinholt Låg (2023). Remote sensing as a tool in mapping geological landforms in forests.

Lars Wallerud (2023). Prediction of site index in young forest using laser data.

Sara Emilie Bråten Aarskog (2023). Remote sensing-based models of biomass for trees and shrub species in the forest-tundra ecotone. Project affiliation: ForestPotential

Johan Stubsjøen Storås (2022). The effect of sample tree selection and calculation methods on accuracy and precision of volume, mean height and dominant height at plot level.

Hans Yngve Ivar Swärd (2022). Predicting living and dead wood volumes in a mature managed Swedish forest with airborne laser scanning.

Olav With Aasgård (2022). Soil carbon stocks in different vegetation classes across the treeline ecotone in central- and southern Norway. Project affiliation: ForestPotential

Elisabeth Annie Anderheim Hansen (2021). Accuracy and precision in field measurements of individual tree height.

Mikal Råheim (2021). Use of harvester data as reference data when mapping total volume and saw log volume. Project affiliation: PRECISION

Kevin Robertson Sinclair (2021). Analysing forests naturalness in southern Norway using airborne laser scanning.

Kaja Skyrud Skarpnord (2021). Reuse of prediction models by area-based forest inventory – Correction of predictions using field observations. Project affiliation: Gjenbruk av prøveflatedata

Mathis Stangeby (2021). The harvesting strategies influence on attacks from the pine weevil (Hylobius abietis).

Eivind Handegard (2020).  Identifying old Norway spruce and Scots pine trees by visual inspection: An analysis of the relationship between age, spatial distribution and morphological traits in trees.

Erik Armand Iversen (2020). Detection of root and butt rot in Norway Spruce (Picea Abies) using airborne hyperspectral images and laser scanning. Project affiliation: PRECISION

Marlene Palm (2020). Resilience of alpine salix shrubs to changes in browsing pressure. Project affiliation: ForestPotential

Ole Marius Tollefsen Moen (2020). Predicting the extent of root and butt rot in stems of Norway Spruce (Picea abies). Project affiliation: PRECISION

Trude Okkenhaug Rønning (2020). Stand age determination for Norway Spruce and Scots Pine using bitemporal airborne laser scanning data. Project affiliation: ForestPotential

Lena Straume (2020). Changed grazing pressure has effects on plant characteristics in the selected boreal and alpine species – A follow-up survey after 15 years grazing experiment. Project affiliation: ForestPotential

Inger Elisabeth Hilstad (2019). Crowberry (Empetrum nigrum) impact on mortality and recruitment on trees in the treeline ecotone. Project affiliation: ForestPotential

Gustaf Lindsköld (2019): Airborne laser scanning for the identification of accumulations of coarse dead wood. Project affiliation: PreMiNa

Jon Hidle Pedersen (2019): Mapping forest key habitats using machine learning and remote sensing data. Project affiliation: PreMiNa

Kenneth Langlie Simensen (2019). Treeline dynamics in Norway – Changes in number of trees, mortality and growth for pioneer trees along a latitudinal gradient. Project affiliation: ForestPotential

Margrethe Fønhus Skeie (2019). Is forest mapping using airborne laser a more appropriate method for finding areas with natural forest than Nature in Norway’s (Natur i Norge, NiN) natural forest criteria?

Steinar Gilleberg Stensli (2019). Detection of pioneer trees in the treeline ecotone using three-dimensional point clouds from image matching. Project affiliation: ForestPotential

Øyvind Sørhuus (2019). Detection of root and butt rot in Norway Spruce (Picea abies) using airborne hyperspectral scanner. Project affiliation: PRECICION.

Anders Johan Konnestad (2018). On the accuracy of GNSS in forests – A test of consumer-grade GNSS equipment, smartphones and open-source postprocessing sorftware under forest canopies, for mapping of forest species.

Magnus Korsvold (2018). Does introduction of digitalized forest management plans affect forestry activities?

Ola Doksrød Strande (2018). Classification of changes using airborne laser scanning data. Project affiliation: ForestPotential

Erik Ødegård (2018). A quantitative analysis of factors which influence the activity of pre-commercial thinning in Trysil municipality.

Axel Johan Berlin (2017). Determination of age-independent site index with area-based laser data from two points in time.

Lennart Noordermeer (2017). Inventory of young forest using airborne laser scanning.

Malin Kristina Sørensen (2017). Future forest management planning – forest owner adapted management plans.

Maxim Galashevskiy (2015). Use of laser data to predict regeneration in mountain forests. Project affiliation: NORKLIMA

Pål Hanssen (2015): Mapping of young forest by using drone and different cameras flown at different altitude.

Sindre Hasselvold (2015). Growth response to thinning in common alder (Alnus glutinosa (L.) Gaertn.) over a seventeen year period.

Robert Østreng (2014): Identification of risk trees along powerlines using airborne laser scanning.

Hans-Petter Ruud (2013). LiDAR as a tool for remote sensing of moose (Alces alces) forage biomass.

Ole Erik Dufseth (2012). Prediction models of site index using airborne laserscanning and digital data map.

Silje Undeland Lysbakken (2012). Predicting need for thinning by means of airborne laser scanning data.

Nenad Marjanovic (2012). Using multi-temporal airborne laser scanner data for predicting change in above ground biomass components in a boreal forest.

Sigriður Júlia Brynleifsdóttir (2011). The forest carbon certification project in Iceland: a case study.

José Luis Barreiro Tomé (2011). Using airborne laser data for estimation of biomass change in boreal conifer forest.

Roar Økseter (2011). Estimating biomass changes in young forest using airborne laser scanner data.

Lars Østbye Hemsing (2010). GIS-modelling of potential natural vegetation (PNV): A methodological case study from south-central Norway.

Joachim Kjelstrup (2010). Registration of diameter at breastheight using data from terrestrial laser scanning.

Torgrim Østgaard (2010). Detection of big Scots pine trees using airborne laser.