Seuraa
Samuli Junttila
Samuli Junttila
Associate Professor, School of Forest Sciences, University of Eastern Finland
Vahvistettu sähköpostiosoite verkkotunnuksessa uef.fi - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
The potential of dual-wavelength terrestrial lidar in early detection of Ips typographus (L.) infestation–Leaf water content as a proxy
S Junttila, M Holopainen, M Vastaranta, P Lyytikäinen-Saarenmaa, ...
Remote Sensing of Environment 231, 111264, 2019
402019
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
372022
Measuring leaf water content with dual-wavelength intensity data from terrestrial laser scanners
S Junttila, M Vastaranta, X Liang, H Kaartinen, A Kukko, S Kaasalainen, ...
Remote Sensing 9 (1), 8, 2016
372016
Can leaf water content be estimated using multispectral terrestrial laser scanning? A case study with Norway spruce seedlings
S Junttila, J Sugano, M Vastaranta, R Linnakoski, H Kaartinen, A Kukko, ...
Frontiers in plant science 9, 299, 2018
322018
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
272022
Understanding 3D structural complexity of individual Scots pine trees with different management history
N Saarinen, K Calders, V Kankare, T Yrttimaa, S Junttila, V Luoma, ...
Ecology and Evolution 11 (6), 2561-2572, 2021
272021
Investigating bi-temporal hyperspectral LiDAR measurements from declined trees—Experiences from laboratory test
S Junttila, S Kaasalainen, M Vastaranta, T Hakala, O Nevalainen, ...
Remote Sensing 7 (10), 13863-13877, 2015
272015
Close-range hyperspectral spectroscopy reveals leaf water content dynamics
S Junttila, T Hölttä, N Saarinen, V Kankare, T Yrttimaa, J Hyyppä, ...
Remote Sensing of Environment 277, 113071, 2022
232022
Structural changes in boreal forests can be quantified using terrestrial laser scanning
T Yrttimaa, V Luoma, N Saarinen, V Kankare, S Junttila, M Holopainen, ...
Remote Sensing 12 (17), 2672, 2020
232020
UAV-based reference data for the prediction of fractional cover of standing deadwood from Sentinel time series
F Schiefer, S Schmidtlein, A Frick, J Frey, R Klinke, K Zielewska-Büttner, ...
ISPRS Open Journal of Photogrammetry and Remote Sensing 8, 100034, 2023
202023
Effects of water availability on a forestry pathosystem: fungal strain-specific variation in disease severity
R Linnakoski, J Sugano, S Junttila, P Pulkkinen, FO Asiegbu, KM Forbes
Scientific reports 7 (1), 13501, 2017
202017
Deep learning enables image-based tree counting, crown segmentation, and height prediction at national scale
S Li, M Brandt, R Fensholt, A Kariryaa, C Igel, F Gieseke, T Nord-Larsen, ...
PNAS nexus 2 (4), pgad076, 2023
172023
Exploring tree growth allometry using two-date terrestrial laser scanning
T Yrttimaa, V Luoma, N Saarinen, V Kankare, S Junttila, M Holopainen, ...
Forest Ecology and Management 518, 120303, 2022
172022
Effect of forest structure and health on the relative surface temperature captured by airborne thermal imagery–Case study in Norway Spruce-dominated stands in Southern Finland
S Junttila, M Vastaranta, J Hämäläinen, P Latva-Käyrä, M Holopainen, ...
Scandinavian Journal of Forest Research 32 (2), 154-165, 2017
152017
Terrestrial laser scanning intensity captures diurnal variation in leaf water potential
S Junttila, T Hölttä, E Puttonen, M Katoh, M Vastaranta, H Kaartinen, ...
Remote Sensing of Environment 255, 112274, 2021
132021
Airborne laser scanning outperforms the alternative 3D techniques in capturing variation in tree height and forest density in southern boreal forests
M Vastaranta, T Yrttimaa, N Saarinen, X Yu, M Karjalainen, K Nurminen, ...
Baltic forestry 24 (2), 268-277, 2018
122018
Capturing seasonal radial growth of boreal trees with terrestrial laser scanning
T Yrttimaa, S Junttila, V Luoma, K Calders, V Kankare, N Saarinen, ...
Forest Ecology and Management 529, 120733, 2023
112023
Effects of stem density on crown architecture of Scots Pine trees
N Saarinen, V Kankare, S Huuskonen, J Hynynen, S Bianchi, T Yrttimaa, ...
Frontiers in plant science 13, 817792, 2022
72022
StrucNet: a global network for automated vegetation structure monitoring
K Calders, B Brede, G Newnham, D Culvenor, J Armston, H Bartholomeus, ...
Remote Sensing in Ecology and Conservation 9 (5), 587-598, 2023
62023
Deep learning enables image-based tree counting, crown segmentation, and height prediction at national scale. PNAS Nexus 2
S Li, M Brandt, R Fensholt, A Kariryaa, C Igel, F Gieseke, T Nord-Larsen, ...
62023
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Artikkelit 1–20