Hans Ole Ørka
Hans Ole Ørka
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Lidar sampling for large-area forest characterization: A review
MA Wulder, JC White, RF Nelson, E Næsset, HO Ørka, NC Coops, ...
Remote sensing of environment 121, 196-209, 2012
Inventory of small forest areas using an unmanned aerial system
S Puliti, HO Ørka, T Gobakken, E Næsset
Remote Sensing 7 (8), 9632-9654, 2015
Tree species classification in boreal forests with hyperspectral data
M Dalponte, HO Ørka, T Gobakken, D Gianelle, E Næsset
IEEE Transactions on Geoscience and Remote Sensing 51 (5), 2632-2645, 2012
Classifying species of individual trees by intensity and structure features derived from airborne laser scanner data
HO Ørka, E Næsset, OM Bollandsås
Remote Sensing of Environment 113 (6), 1163-1174, 2009
Tree crown delineation and tree species classification in boreal forests using hyperspectral and ALS data
M Dalponte, HO Ørka, LT Ene, T Gobakken, E Næsset
Remote sensing of environment 140, 306-317, 2014
Tree species classification using airborne LiDAR–effects of stand and tree parameters, downsizing of training set, intensity normalization, and sensor type
I Korpela, HO Ørka, M Maltamo, T Tokola, J Hyyppä
Silva Fennica 44 (2), 319-339, 2010
Range and AGC normalization in airborne discrete-return LiDAR intensity data for forest canopies
I Korpela, HO Ørka, J Hyyppä, V Heikkinen, T Tokola
ISPRS Journal of Photogrammetry and Remote Sensing 65 (4), 369-379, 2010
Biomass estimation using 3D data from unmanned aerial vehicle imagery in a tropical woodland
DJ Kachamba, HO Ørka, T Gobakken, T Eid, W Mwase
Remote Sensing 8 (11), 968, 2016
Estimating biomass in Hedmark County, Norway using national forest inventory field plots and airborne laser scanning
T Gobakken, E Næsset, R Nelson, OM Bollandsås, TG Gregoire, G Ståhl, ...
Remote Sensing of Environment 123, 443-456, 2012
Mapping and estimating forest area and aboveground biomass in miombo woodlands in Tanzania using data from airborne laser scanning, TanDEM-X, RapidEye, and global forest maps …
E Næsset, HO Ørka, S Solberg, OM Bollandsås, EH Hansen, E Mauya, ...
Remote sensing of Environment 175, 282-300, 2016
Effects of different sensors and leaf-on and leaf-off canopy conditions on echo distributions and individual tree properties derived from airborne laser scanning
HO Ørka, E Næsset, OM Bollandsås
Remote Sensing of Environment 114 (7), 1445-1461, 2010
Assessing 3D point clouds from aerial photographs for species-specific forest inventories
S Puliti, T Gobakken, HO Ørka, E Næsset
Scandinavian journal of forest research 32 (1), 68-79, 2017
Characterizing forest species composition using multiple remote sensing data sources and inventory approaches
HO Ørka, M Dalponte, T Gobakken, E Næsset, LT Ene
Scandinavian Journal of Forest Research 28 (7), 677-688, 2013
Interpreting cultural remains in airborne laser scanning generated digital terrain models: effects of size and shape on detection success rates
O Risbøl, OM Bollandsås, A Nesbakken, HO Ørka, E Næsset, T Gobakken
Journal of archaeological Science 40 (12), 4688-4700, 2013
Simultaneously acquired airborne laser scanning and multispectral imagery for individual tree species identification
HO Ørka, T Gobakken, E Næsset, L Ene, V Lien
Canadian Journal of Remote Sensing 38 (2), 125-138, 2012
Comparing the accuracies of forest attributes predicted from airborne laser scanning and digital aerial photogrammetry in operational forest inventories
L Noordermeer, OM Bollandsås, HO Ørka, E Næsset, T Gobakken
Remote Sensing of Environment 226, 26-37, 2019
Utilizing airborne laser intensity for tree species classification
HO Ørka, E Næsset, OM Bollandsås
International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2007
Effects of UAV image resolution, camera type, and image overlap on accuracy of biomass predictions in a tropical woodland
D Domingo, HO Ørka, E Næsset, D Kachamba, T Gobakken
Remote Sensing 11 (8), 948, 2019
Assessing forest inventory information obtained from different inventory approaches and remote sensing data sources
E Bergseng, HO Ørka, E Næsset, T Gobakken
Annals of forest science 72, 33-45, 2015
Predicting stem diameters and aboveground biomass of individual trees using remote sensing data
M Dalponte, L Frizzera, HO Ørka, T Gobakken, E Næsset, D Gianelle
Ecological Indicators 85, 367-376, 2018
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