3 citations · 4 across the 5 of their papers we have counts for
6 papers
Assessing airborne laser scanning and aerial photogrammetry for deep learning-based stand delineation
Håkon Næss Sandum, Hans Ole Ørka, Oliver Tomic +1
Accurate forest stand delineation is essential for forest inventory and management but remains a largely manual and subjective process. A recent study has shown that deep learning…
Semantic segmentation of forest stands using deep learning
Håkon Næss Sandum, Hans Ole Ørka, Oliver Tomic +2
Forest stands are the fundamental units in forest management inventories, silviculture, and financial analysis within operational forestry. Over the past two decades, a common meth…
Estimation of boreal forest biomass from ICESat-2 data using hierarchical hybrid inference
Petri Varvia, Svetlana Saarela, Matti Maltamo +5
The ICESat-2, launched in 2018, carries the ATLAS instrument, which is a photon-counting spaceborne lidar that provides strip samples over the terrain. While primarily designed for…
Forest Parameter Prediction by Multiobjective Deep Learning of Regression Models Trained with Pseudo-Target Imputation
Sara Björk, Stian N. Anfinsen, Michael Kampffmeyer +3
In prediction of forest parameters with data from remote sensing (RS), regression models have traditionally been trained on a small sample of ground reference data. This paper prop…
On the potential of sequential and non-sequential regression models for Sentinel-1-based biomass prediction in Tanzanian miombo forests
Sara Björk, Stian Normann Anfinsen, Erik Næsset +2
This study derives regression models for above-ground biomass (AGB) estimation in miombo woodlands of Tanzania that utilise the high availability and low cost of Sentinel-1 data. T…
Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations
Chad Babcock, Andrew O. Finley, Hans-Erik Andersen +9
The goal of this research was to develop and examine the performance of a geostatistical coregionalization modeling approach for combining field inventory measurements, strip sampl…