Stefano Puliti
Stefano Puliti
Researcher, Norwegian Institute for Bio-economy Research (NIBIO) National Forest Inventory
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Zitiert von
Zitiert von
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
Structure from motion photogrammetry in forestry: A review
J Iglhaut, C Cabo, S Puliti, L Piermattei, J O’Connor, J Rosette
Current Forestry Reports 5 (3), 155-168, 2019
Combining UAV and Sentinel-2 auxiliary data for forest growing stock volume estimation through hierarchical model-based inference
S Puliti, S Saarela, T Gobakken, G Ståhl, E Næsset
Remote sensing of environment 204, 485-497, 2018
A new approach with DTM-independent metrics for forest growing stock prediction using UAV photogrammetric data
F Giannetti, G Chirici, T Gobakken, E Naesset, D Travaglini, S Puliti
Remote Sensing of Environment 213, 195-205, 2018
Use of partial-coverage UAV data in sampling for large scale forest inventories
S Puliti, LT Ene, T Gobakken, E Næsset
Remote Sensing of Environment 194, 115-126, 2017
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
Use of UAV photogrammetric data for estimation of biophysical properties in forest stands under regeneration
S Puliti, S Solberg, A Granhus
Remote Sensing 11 (3), 233, 2019
Estimation of forest growing stock volume with UAV laser scanning data: can it be done without field data?
S Puliti, J Breidenbach, R Astrup
Remote Sensing 12 (8), 1245, 2020
Value of airborne laser scanning and digital aerial photogrammetry data in forest decision making
A Kangas, T Gobakken, S Puliti, M Hauglin, E Naesset
Silva Fennica 52 (1), 19, 2018
Tree-stump detection, segmentation, classification, and measurement using unmanned aerial vehicle (UAV) imagery
S Puliti, B Talbot, R Astrup
Forests 9 (3), 102, 2018
A comparison of UAV laser scanning, photogrammetry and airborne laser scanning for precision inventory of small-forest properties
S Puliti, JP Dash, MS Watt, J Breidenbach, GD Pearse
Forestry: An International Journal of Forest Research 93 (1), 150-162, 2020
Modelling above-ground biomass stock over Norway using national forest inventory data with ArcticDEM and Sentinel-2 data
S Puliti, M Hauglin, J Breidenbach, P Montesano, CSR Neigh, J Rahlf, ...
Remote Sensing of Environment 236, 111501, 2020
National mapping and estimation of forest area by dominant tree species using Sentinel-2 data
J Breidenbach, LT Waser, M Debella-Gilo, J Schumacher, J Rahlf, ...
Canadian Journal of Forest Research 51 (3), 365-379, 2021
Aboveground Woody biomass product validation good practices protocol
L Duncanson, J Armston, M Disney, V Avitabile, N Barbier, K Calders, ...
Land Product Validation Subgroup (WGCV/CEOS, 2021
Use of UAV photogrammetric data in forest genetic trials: measuring tree height, growth, and phenology in Norway spruce (Picea abies L. Karst.)
TM Solvin, S Puliti, A Steffenrem
Scandinavian Journal of Forest Research 35 (7), 322-333, 2020
Age-independent site index mapping with repeated single-tree airborne laser scanning
S Solberg, H Kvaalen, S Puliti
Scandinavian Journal of Forest Research 34 (8), 763-770, 2019
Inventory of small forest areas using an unmanned aerial system. Remote Sens 7: 9632–9654
S Puliti, HO Ørka, T Gobakken, E Næsset
Assessing harvested sites in a forested boreal mountain catchment through global forest watch
F Rossi, J Breidenbach, S Puliti, R Astrup, B Talbot
Remote sensing 11 (5), 543, 2019
Assessment of UAV photogrammetric DTM-independent variables for modelling and mapping forest structural indices in mixed temperate forests
F Giannetti, N Puletti, S Puliti, D Travaglini, G Chirici
Ecological Indicators 117, 106513, 2020
Detection and classification of Root and Butt-Rot (RBR) in stumps of Norway Spruce using RGB images and machine learning
A Ostovar, B Talbot, S Puliti, R Astrup, O Ringdahl
Sensors 19 (7), 1579, 2019
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