Roope Näsi
Roope Näsi
Research Scientist, Finnish Geospatial Research Institute (National Land Survey of Finland)
Verified email at - Homepage
Cited by
Cited by
Using UAV-based photogrammetry and hyperspectral imaging for mapping bark beetle damage at tree-level
R Näsi, E Honkavaara, P Lyytikäinen-Saarenmaa, M Blomqvist, P Litkey, ...
Remote Sensing 7 (11), 15467-15493, 2015
Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft
R Näsi, E Honkavaara, M Blomqvist, P Lyytikäinen-Saarenmaa, T Hakala, ...
Urban Forestry & Urban Greening 30, 72-83, 2018
A novel machine learning method for estimating biomass of grass swards using a photogrammetric canopy height model, images and vegetation indices captured by a drone
N Viljanen, E Honkavaara, R Näsi, T Hakala, O Niemeläinen, J Kaivosoja
Agriculture 8 (5), 70, 2018
Estimating biomass and nitrogen amount of barley and grass using UAV and aircraft based spectral and photogrammetric 3D features
R Näsi, N Viljanen, J Kaivosoja, K Alhonoja, T Hakala, L Markelin, ...
Remote Sensing 10 (7), 1082, 2018
Assessing biodiversity in boreal forests with UAV-based photogrammetric point clouds and hyperspectral imaging
N Saarinen, M Vastaranta, R Näsi, T Rosnell, T Hakala, E Honkavaara, ...
Remote Sensing 10 (2), 338, 2018
Machine learning estimators for the quantity and quality of grass swards used for silage production using drone-based imaging spectrometry and photogrammetry
RA Oliveira, R Näsi, O Niemeläinen, L Nyholm, K Alhonoja, J Kaivosoja, ...
Remote Sensing of Environment 246, 111830, 2020
Direct reflectance measurements from drones: Sensor absolute radiometric calibration and system tests for forest reflectance characterization
T Hakala, L Markelin, E Honkavaara, B Scott, T Theocharous, ...
Sensors 18 (5), 1417, 2018
Assessment of classifiers and remote sensing features of hyperspectral imagery and stereo-photogrammetric point clouds for recognition of tree species in a forest area of high …
S Tuominen, R Näsi, E Honkavaara, A Balazs, T Hakala, N Viljanen, ...
Remote Sensing 10 (5), 714, 2018
Characterizing seedling stands using leaf-off and leaf-on photogrammetric point clouds and hyperspectral imagery acquired from unmanned aerial vehicle
M Imangholiloo, N Saarinen, L Markelin, T Rosnell, R Näsi, T Hakala, ...
Forests 10 (5), 415, 2019
Radiometric block adjustment of hyperspectral image blocks in the Brazilian environment
GT Miyoshi, NN Imai, AMG Tommaselli, E Honkavaara, R Näsi, ...
International journal of remote sensing 39 (15-16), 4910-4930, 2018
Direct reflectance transformation methodology for drone-based hyperspectral imaging
J Suomalainen, RA Oliveira, T Hakala, N Koivumäki, L Markelin, R Näsi, ...
Remote Sensing of Environment 266, 112691, 2021
Close-range remote sensing of forests: The state of the art, challenges, and opportunities for systems and data acquisitions
X Liang, A Kukko, I Balenović, N Saarinen, S Junttila, V Kankare, ...
IEEE geoscience and remote sensing magazine 10 (3), 32-71, 2022
Using multitemporal hyper-and multispectral UAV imaging for detecting bark beetle infestation on norway spruce
E Honkavaara, R Näsi, R Oliveira, N Viljanen, J Suomalainen, ...
The international archives of the photogrammetry, remote sensing and spatial …, 2020
Reference measurements in developing UAV systems for detecting pests, weeds, and diseases
J Kaivosoja, J Hautsalo, J Heikkinen, L Hiltunen, P Ruuttunen, R Näsi, ...
Remote sensing 13 (7), 1238, 2021
Multispectral imagery provides benefits for mapping spruce tree decline due to bark beetle infestation when acquired late in the season
S Junttila, R Näsi, N Koivumäki, M Imangholiloo, N Saarinen, J Raisio, ...
Remote Sensing 14 (4), 909, 2022
A novel tilt correction technique for irradiance sensors and spectrometers on-board unmanned aerial vehicles
J Suomalainen, T Hakala, R Alves de Oliveira, L Markelin, N Viljanen, ...
Remote Sensing 10 (12), 2068, 2018
Autonomous hyperspectral UAS photogrammetry for environmental monitoring applications
E Honkavaara, T Hakala, L Markelin, A Jaakkola, H Saari, H Ojanen, ...
ISPRS Archives, 2014
UAS based tree species identification using the novel FPI based hyperspectral cameras in visible, NIR and SWIR spectral ranges
R Näsi, E Honkavaara, S Tuominen, H Saari, I Pölönen, T Hakala, ...
The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2016
A clustering framework for monitoring circadian rhythm in structural dynamics in plants from terrestrial laser scanning time series
E Puttonen, M Lehtomäki, P Litkey, R Näsi, Z Feng, X Liang, S Wittke, ...
Frontiers in Plant Science 10, 430216, 2019
Assessment of various remote sensing technologies in biomass and nitrogen content estimation using an agricultural test field
R Näsi, N Viljanen, J Kaivosoja, T Hakala, M Pandžić, L Markelin, ...
The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2017
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