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ORCIDErik Næsset
Erik Nasset – Erik Næsset Ramtvedt
Person information
- affiliation: Norwegian University of Life Sciences, Ås, Norway
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Journal Articles
- 2024
[j48]Svein Solberg
, Ole Martin Bollandsås, Terje Gobakken, Erik Næsset, Paromita Basak, Laura Innice Duncanson:
Biomass Change Estimated by TanDEM-X Interferometry and GEDI in a Tanzanian Forest. Remote. Sens. 16(5): 861 (2024)- [j47]Eirik Næsset Ramtvedt, Hans Ole Ørka, Ole Martin Bollandsås, Erik Næsset, Terje Gobakken:
Effect of Albedo Footprint Size on Relationships between Measured Albedo and Forest Attributes for Small Forest Plots. Remote. Sens. 16(16): 3085 (2024) - 2023
- [j46]Lennart Noordermeer, Jaime Candelas-Bielza, Svetlana Saarela, Terje Gobakken, Ole Martin Bollandsås, Erik Næsset:
Monitoring tree occupancy and height in the Norwegian alpine treeline using a time series of airborne laser scanner data. Int. J. Appl. Earth Obs. Geoinformation 117: 103201 (2023) - [j45]Marie-Claude Jutras-Perreault, Terje Gobakken, Erik Næsset, Hans Ole Ørka:
Comparison of Different Remotely Sensed Data Sources for Detection of Presence of Standing Dead Trees Using a Tree-Based Approach. Remote. Sens. 15(9): 2223 (2023) - [j44]Ritwika Mukhopadhyay, Erik Næsset, Terje Gobakken, Ida Marielle Mienna, Jaime Candelas-Bielza, Gunnar Austrheim, Henrik J. Persson, Hans Ole Ørka, Bjørn-Eirik Roald, Ole Martin Bollandsås:
Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference. Remote. Sens. 15(14): 3508 (2023) - 2022
- [j43]Michele Dalponte, Yady Tatiana Solano Correa, Hans Ole Ørka, Terje Gobakken, Erik Næsset:
Detection of heartwood rot in Norway spruce trees with lidar and multi-temporal satellite data. Int. J. Appl. Earth Obs. Geoinformation 109: 102790 (2022) - [j42]Eirik Næsset Ramtvedt, Terje Gobakken, Erik Næsset:
Fine-Spatial Boreal-Alpine Single-Tree Albedo Measured by UAV: Experiences and Challenges. Remote. Sens. 14(6): 1482 (2022) - [j41]Michele Dalponte, Alvar J. I. Kallio, Hans Ole Ørka, Erik Næsset, Terje Gobakken:
Wood Decay Detection in Norway Spruce Forests Based on Airborne Hyperspectral and ALS Data. Remote. Sens. 14(8): 1892 (2022) - [j40]Benjamin Allen, Michele Dalponte, Hans Ole Ørka, Erik Næsset, Stefano Puliti, Rasmus Astrup, Terje Gobakken:
UAV-Based Hyperspectral Imagery for Detection of Root, Butt, and Stem Rot in Norway Spruce. Remote. Sens. 14(15): 3830 (2022) - [j39]Sara Björk, Stian Normann Anfinsen, Erik Næsset, Terje Gobakken, Eliakimu Zahabu:
On the Potential of Sequential and Nonsequential Regression Models for Sentinel-1-Based Biomass Prediction in Tanzanian Miombo Forests. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 15: 4612-4639 (2022) - 2021
- [j38]Erik Næsset, Terje Gobakken, Marie-Claude Jutras-Perreault, Eirik Næsset Ramtvedt:
Comparing 3D Point Cloud Data from Laser Scanning and Digital Aerial Photogrammetry for Height Estimation of Small Trees and Other Vegetation in a Boreal-Alpine Ecotone. Remote. Sens. 13(13): 2469 (2021) - 2020
- [j37]Erik Næsset, Ronald E. McRoberts, Anssi Pekkarinen, Sassan Saatchi, Maurizio Santoro, Øivind Due Trier, Eliakimu Zahabu, Terje Gobakken:
Use of local and global maps of forest canopy height and aboveground biomass to enhance local estimates of biomass in miombo woodlands in Tanzania. Int. J. Appl. Earth Obs. Geoinformation 89: 102109 (2020) - [j36]Erik Næsset, Ronald E. McRoberts, Anssi Pekkarinen, Sassan Saatchi, Maurizio Santoro, Øivind Due Trier, Eliakimu Zahabu, Terje Gobakken:
Use of local and global maps of forest canopy height and aboveground biomass to enhance local estimates of biomass in miombo woodlands in Tanzania. Int. J. Appl. Earth Obs. Geoinformation 93: 102138 (2020) - [j35]Ronald E. McRoberts, Erik Næsset, Christophe Sannier, Stephen V. Stehman, Erkki Tomppo:
Remote Sensing Support for the Gain-Loss Approach for Greenhouse Gas Inventories. Remote. Sens. 12(11): 1891 (2020) - [j34]Habitamu Taddese, Zerihun Asrat, Ingunn Burud, Terje Gobakken, Hans Ole Ørka, Øystein B. Dick, Erik Næsset:
Use of Remotely Sensed Data to Enhance Estimation of Aboveground Biomass for the Dry Afromontane Forest in South-Central Ethiopia. Remote. Sens. 12(20): 3335 (2020) - 2019
- [j33]Ronald E. McRoberts, Erik Næsset, Sassan Saatchi, Greg C. Liknes, Brian F. Walters, Qi Chen:
Local validation of global biomass maps. Int. J. Appl. Earth Obs. Geoinformation 83 (2019) - [j32]Darío Domingo, Hans Ole Ørka, Erik Næsset, Daud Jones Kachamba, Terje Gobakken:
Effects of UAV Image Resolution, Camera Type, and Image Overlap on Accuracy of Biomass Predictions in a Tropical Woodland. Remote. Sens. 11(8): 948 (2019) - [j31]Salim Malek, Franco Miglietta, Terje Gobakken, Erik Næsset, Damiano Gianelle, Michele Dalponte:
Optimizing Field Data Collection for Individual Tree Attribute Predictions Using Active Learning Methods. Remote. Sens. 11(8): 949 (2019) - [j30]Ole Martin Bollandsås, Hans Ole Ørka, Michele Dalponte, Terje Gobakken, Erik Næsset:
Modelling Site Index in Forest Stands Using Airborne Hyperspectral Imagery and Bi-Temporal Laser Scanner Data. Remote. Sens. 11(9): 1020 (2019) - [j29]Erik Næsset, Terje Gobakken, Ronald E. McRoberts:
A Model-Dependent Method for Monitoring Subtle Changes in Vegetation Height in the Boreal-Alpine Ecotone Using Bi-Temporal, Three Dimensional Point Data from Airborne Laser Scanning. Remote. Sens. 11(15): 1804 (2019) - [j28]Jessica Esteban, Ronald E. McRoberts, Alfredo Fernández-Landa, José Luis Tomé, Erik Næsset:
Estimating Forest Volume and Biomass and Their Changes Using Random Forests and Remotely Sensed Data. Remote. Sens. 11(16): 1944 (2019) - [j27]Lennart Noordermeer, Roar Økseter, Hans Ole Ørka, Terje Gobakken, Erik Næsset, Ole Martin Bollandsås:
Classifications of Forest Change by Using Bitemporal Airborne Laser Scanner Data. Remote. Sens. 11(18): 2145 (2019) - 2018
- [j26]Michele Dalponte, Liviu Theodor Ene, Terje Gobakken, Erik Næsset, Damiano Gianelle:
Predicting Selected Forest Stand Characteristics with Multispectral ALS Data. Remote. Sens. 10(4): 586 (2018) - [j25]Svetlana Saarela, Sören Holm, Sean P. Healey, Hans-Erik Andersen, Hans Petersson, Wilmer Prentius, Paul L. Patterson, Erik Næsset, Timothy G. Gregoire, Göran Ståhl:
Generalized Hierarchical Model-Based Estimation for Aboveground Biomass Assessment Using GEDI and Landsat Data. Remote. Sens. 10(11): 1832 (2018) - 2017
- [j24]Kaja Kandare, Hans Ole Ørka, Michele Dalponte, Erik Næsset, Terje Gobakken:
Individual tree crown approach for predicting site index in boreal forests using airborne laser scanning and hyperspectral data. Int. J. Appl. Earth Obs. Geoinformation 60: 72-82 (2017) - [j23]Jahangir Mohammadi, Shaban Shataee, Manochehr Namiranian, Erik Næsset:
Modeling biophysical properties of broad-leaved stands in the hyrcanian forests of Iran using fused airborne laser scanner data and ultraCam-D images. Int. J. Appl. Earth Obs. Geoinformation 61: 32-45 (2017) - [j22]Ivar Oveland, Marius Hauglin, Terje Gobakken, Erik Næsset, Ivar Maalen-Johansen:
Automatic Estimation of Tree Position and Stem Diameter Using a Moving Terrestrial Laser Scanner. Remote. Sens. 9(4): 350 (2017) - [j21]Kaja Kandare, Michele Dalponte, Hans Ole Ørka, Lorenzo Frizzera, Erik Næsset:
Prediction of Species-Specific Volume Using Different Inventory Approaches by Fusing Airborne Laser Scanning and Hyperspectral Data. Remote. Sens. 9(5): 400 (2017) - [j20]Daud Jones Kachamba, Hans Ole Ørka, Erik Næsset, Tron Eid, Terje Gobakken:
Influence of Plot Size on Efficiency of Biomass Estimates in Inventories of Dry Tropical Forests Assisted by Photogrammetric Data from an Unmanned Aircraft System. Remote. Sens. 9(6): 610 (2017) - [j19]Stefano Puliti, Svein Solberg, Erik Næsset, Terje Gobakken, Eliakimu Zahabu, Ernest Mauya, Rogers Ernest Malimbwi:
Modelling above Ground Biomass in Tanzanian Miombo Woodlands Using TanDEM-X WorldDEM and Field Data. Remote. Sens. 9(10): 984 (2017) - 2016
- [j18]Marius Hauglin, Erik Næsset:
Detection and Segmentation of Small Trees in the Forest-Tundra Ecotone Using Airborne Laser Scanning. Remote. Sens. 8(5): 407 (2016) - [j17]Erik Næsset:
Discrimination between Ground Vegetation and Small Pioneer Trees in the Boreal-Alpine Ecotone Using Intensity Metrics Derived from Airborne Laser Scanner Data. Remote. Sens. 8(7): 548 (2016) - 2015
- [j16]Endre Hofstad Hansen, Terje Gobakken, Ole Martin Bollandsås, Eliakimu Zahabu, Erik Næsset:
Modeling Aboveground Biomass in Dense Tropical Submontane Rainforest Using Airborne Laser Scanner Data. Remote. Sens. 7(1): 788-807 (2015) - [j15]Erik Næsset:
Vertical Height Errors in Digital Terrain Models Derived from Airborne Laser Scanner Data in a Boreal-Alpine Ecotone in Norway. Remote. Sens. 7(4): 4702-4725 (2015) - [j14]Endre Hofstad Hansen, Terje Gobakken, Erik Næsset:
Effects of Pulse Density on Digital Terrain Models and Canopy Metrics Using Airborne Laser Scanning in a Tropical Rainforest. Remote. Sens. 7(7): 8453-8468 (2015) - [j13]Stefano Puliti, Hans Ole Ørka, Terje Gobakken, Erik Næsset:
Inventory of Small Forest Areas Using an Unmanned Aerial System. Remote. Sens. 7(8): 9632-9654 (2015) - [j12]Endre Hofstad Hansen, Terje Gobakken, Svein Solberg, Annika Kangas, Liviu Theodor Ene, Ernest Mauya, Erik Næsset:
Relative Efficiency of ALS and InSAR for Biomass Estimation in a Tanzanian Rainforest. Remote. Sens. 7(8): 9865-9885 (2015) - 2014
- [j11]Nadja Stumberg, Marius Hauglin, Ole Martin Bollandsås, Terje Gobakken, Erik Næsset:
Improving Classification of Airborne Laser Scanning Echoes in the Forest-Tundra Ecotone Using Geostatistical and Statistical Measures. Remote. Sens. 6(5): 4582-4599 (2014) - [j10]Nadja Stumberg, Ole Martin Bollandsås, Terje Gobakken, Erik Næsset:
Automatic Detection of Small Single Trees in the Forest-Tundra Ecotone Using Airborne Laser Scanning. Remote. Sens. 6(10): 10152-10170 (2014) - [j9]Michele Dalponte, Liviu Theodor Ene, Hans Ole Ørka, Terje Gobakken, Erik Næsset:
Unsupervised Selection of Training Samples for Tree Species Classification Using Hyperspectral Data. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(8): 3560-3569 (2014) - [j8]Claudio Persello, Abdeslam Boularias, Michele Dalponte, Terje Gobakken, Erik Næsset, Bernhard Schölkopf:
Cost-Sensitive Active Learning With Lookahead: Optimizing Field Surveys for Remote Sensing Data Classification. IEEE Trans. Geosci. Remote. Sens. 52(10): 6652-6664 (2014) - 2013
- [j7]Ole Martin Bollandsås, Timothy G. Gregoire, Erik Næsset, Bernt-Håvard Øyen:
Detection of biomass change in a Norwegian mountain forest area using small footprint airborne laser scanner data. Stat. Methods Appl. 22(1): 113-129 (2013) - [j6]Ronald E. McRoberts, Erik Næsset, Terje Gobakken:
Accuracy and Precision for Remote Sensing Applications of Nonlinear Model-Based Inference. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 6(1): 27-34 (2013) - [j5]Michele Dalponte, Hans Ole Ørka, Terje Gobakken, Damiano Gianelle, Erik Næsset:
Tree Species Classification in Boreal Forests With Hyperspectral Data. IEEE Trans. Geosci. Remote. Sens. 51(5-1): 2632-2645 (2013) - 2012
- [j4]Harri Kaartinen, Juha Hyyppä, Xiaowei Yu, Mikko Vastaranta, Hannu Hyyppä, Antero Kukko, Markus Holopainen, Christian Heipke, Manuela Hirschmugl, Felix Morsdorf, Erik Næsset, Juho Pitkänen, Sorin C. Popescu, Svein Solberg, Bernd-Michael Wolf, Jee-Cheng Wu:
An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning. Remote. Sens. 4(4): 950-974 (2012) - 2011
- [j3]Christopher W. Bater, Michael A. Wulder, Nicholas C. Coops, Ross F. Nelson, Thomas Hilker, Erik Nasset:
Stability of Sample-Based Scanning-LiDAR-Derived Vegetation Metrics for Forest Monitoring. IEEE Trans. Geosci. Remote. Sens. 49(6-2): 2385-2392 (2011) - 2010
- [j2]Svein Solberg, Dan Johan Weydahl, Erik Nasset:
Simulating X-Band Interferometric Height in a Spruce Forest From Airborne Laser Scanning. IEEE Trans. Geosci. Remote. Sens. 48(9): 3369-3378 (2010) - 1996
- [j1]Erik Næsset:
Use of the Weighted Kappa Coefficient in Classification Error Assessment of Thematic Maps. Int. J. Geogr. Inf. Sci. 10(5): 591-604 (1996)
Conference and Workshop Papers
- 2020
- [c5]Sara Björk, Stian Normann Anfinsen, Erik Næsset, Terje Gobakken, Eliakimu Zahabu:
Generation of Lidar-Predicted Forest Biomass Maps from Radar Backscatter with Conditional Generative Adversarial Networks. IGARSS 2020: 4327-4330 - 2018
- [c4]Michele Dalponte, Liviu Theodor Ene, Terje Gobakken, Erik Næsset, Damiano Gianelle:
Prediction of Forest Attributes with Multispectral Lidar Data. IGARSS 2018: 7528-7531 - 2013
- [c3]Claudio Persello, Michele Dalponte, Terje Gobakken, Erik Næsset:
Optimizing the ground sample collection with cost-sensitive active learning for tree species classification using hyperspectral images. IGARSS 2013: 2091-2094 - [c2]Michele Dalponte, Liviu Theodor Ene, Hans Ole Ørka, Terje Gobakken, Erik Næsset:
Unsupervised selection of training plots and trees for tree species classification. IGARSS 2013: 2095-2098 - 2010
- [c1]Ross F. Nelson, Göran Ståhl, Sören Holm, Timothy G. Gregoire, Erik Næsset, Terje Gobakken:
Using airborne & space lidars for large-area inventory. IGARSS 2010: 2463-2466
Informal and Other Publications
- 2023
- [i2]Sara Björk, Stian Normann Anfinsen, Michael Kampffmeyer, Erik Næsset, Terje Gobakken, Lennart Noordermeer:
Forest Parameter Prediction by Multiobjective Deep Learning of Regression Models Trained with Pseudo-Target Imputation. CoRR abs/2306.11103 (2023) - 2021
- [i1]Sara Björk, Stian Normann Anfinsen, Erik Næsset, Terje Gobakken, Eliakimu Zahabu:
Constructing Forest Biomass Prediction Maps from Radar Backscatter by Sequential Regression with a Conditional Generative Adversarial Network. CoRR abs/2106.15020 (2021)
Coauthor Index
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