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Niko Koivumäki
Niko Koivumäki
Doctoral candidate
Verified email at nls.fi
Title
Cited by
Cited by
Year
Individual tree detection and classification with UAV-based photogrammetric point clouds and hyperspectral imaging
O Nevalainen, E Honkavaara, S Tuominen, N Viljanen, T Hakala, X Yu, ...
Remote Sensing 9 (3), 185, 2017
5422017
Individual tree detection and classification with UAV-based photogrammetric point clouds and hyperspectral imaging. Remote Sens 9, article id 185
O Nevalainen, E Honkavaara, S Tuominen, N Viljanen, T Hakala, X Yu, ...
542*2017
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
4852015
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
2512018
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
2502018
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
1982018
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
1292020
Structural and photosynthetic dynamics mediate the response of SIF to water stress in a potato crop
S Xu, J Atherton, A Riikonen, C Zhang, J Oivukkamäki, A MacArthur, ...
Remote Sensing of Environment 263, 112555, 2021
1192021
Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a …
E Honkavaara, MA Eskelinen, I Pölönen, H Saari, H Ojanen, R Mannila, ...
IEEE Transactions on Geoscience and Remote Sensing 54 (9), 5440-5454, 2016
1042016
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
1002018
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
812018
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
762021
Assessing the effects of stand dynamics on stem growth allocation of individual Scots pine trees
N Saarinen, V Kankare, T Yrttimaa, N Viljanen, E Honkavaara, ...
bioRxiv, 2020
66*2020
Assessing the effects of thinning on stem growth allocation of individual Scots pine trees
N Saarinen, V Kankare, T Yrttimaa, N Viljanen, E Honkavaara, ...
Forest Ecology and Management 474, 118344, 2020
622020
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
552020
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
452022
Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables
S Tuominen, A Balazs, E Honkavaara, I Pölönen, H Saari, T Hakala, ...
Silva Fennica 51, 2017
402017
Estimating Grass Sward Quality and Quantity Parameters Using Drone Remote Sensing with Deep Neural Networks
K Karila, R Alves Oliveira, J Ek, J Kaivosoja, N Koivumäki, P Korhonen, ...
Remote Sensing 14 (11), 2692, 2022
322022
High-precision estimation of grass quality and quantity using UAS-based VNIR and SWIR hyperspectral cameras and machine learning
RA Oliveira, R Näsi, P Korhonen, A Mustonen, O Niemeläinen, ...
Precision Agriculture 25 (1), 186-220, 2024
312024
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
292018
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Articles 1–20