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
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
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
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
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
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
Autonomous hyperspectral UAS photogrammetry for environmental monitoring applications
E Honkavaara, T Hakala, L Markelin, A Jaakkola, H Saari, H Ojanen, ...
ISPRS Archives, 2014
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
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, 486, 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
The system can't perform the operation now. Try again later.
Articles 1–20