Accesso pubblico

Technical notes: A detailed study for the provision of measurement uncertainty and traceability for goniospectrometers

JI Peltoniemi, T Hakala, J Suomalainen, E Honkavaara, L Markelin, ...

Journal of Quantitative Spectroscopy and Radiative Transfer 146 (October …, 2014

Mandati: European Commission

UAV-based hyperspectral monitoring of small freshwater area

I Pölönen, HH Puupponen, E Honkavaara, A Lindfors, H Saari, L Markelin, ...

SPIE. 9239, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI …, 2014

Mandati: Finnish Funding Agency for Innovation

Disponibili pubblicamente: 19

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

Mandati: Academy of Finland

[HTML] sciencedirect.com

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

Mandati: Business Finland

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), 2018

Mandati: Academy of Finland, UK Natural Environment Research Council

[HTML] sciencedirect.com

Direct reflectance transformation methodology for drone-based hyperspectral imaging

J Suomalainen, R A. Oliveira, T Hakala, N Koivumäki, L Markelin, R Näsi, ...

Remote Sensing of Environment 266, 112691, 2021

Mandati: Academy of Finland

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

Mandati: Academy of Finland

[HTML] silvafennica.fi

Tree species identification in aerial image data using directional reflectance signatures

I Korpela, L Mehtätalo, L Markelin, A Seppänen, A Kangas

Silva Fennica 48 (3), 2014

Mandati: Academy of Finland, Finnish Funding Agency for Innovation

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

Mandati: Academy of Finland

[PDF] mdpi.com

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

Mandati: Academy of Finland, Business Finland

Autonomous hyperspectral UAS photogrammetry for environmental monitoring applications

E Honkavaara, T Hakala, L Markelin, A Jaakkola, H Saari, H Ojanen, ...

The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2014

Mandati: Finnish Funding Agency for Innovation

Atmospheric correction performance of hyperspectral airborne imagery over a small eutrophic lake under changing cloud cover

L Markelin, SGH Simis, PD Hunter, E Spyrakos, AN Tyler, D Clewley, ...

Remote Sensing 9 (1), 2, 2016

Mandati: UK Natural Environment Research Council

[PDF] iop.org

Flat-field calibration method for hyperspectral frame cameras

A Kokka, T Pulli, E Honkavaara, L Markelin, P Kärhä, E Ikonen

Metrologia 56 (5), 055001, 2019

Mandati: Academy of Finland

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

Mandati: Academy of Finland, Finnish Funding Agency for Innovation

Assessment of RGB and hyperspectral UAV remote sensing for grass quantity and quality estimation

RA Oliveira, R Näsi, O Niemeläinen, L Nyholm, K Alhonoja, J Kaivosoja, ...

The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2019

Mandati: Business Finland

Optimizing radiometric processing and feature extraction of drone based hyperspectral frame format imagery for estimation of yield quantity and quality of a grass sward

R Näsi, N Viljanen, R Oliveira, J Kaivosoja, O Niemeläinen, T Hakala, ...

The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2018

Mandati: Business Finland

[PDF] ugent.be

Reconstructing the digital twin of forests from a 3D library: Quantifying trade-offs for radiative transfer modeling

C Liu, K Calders, N Origo, M Disney, F Meunier, W Woodgate, ...

Remote Sensing of Environment 298, 113832, 2023

Mandati: Academy of Finland, UK Natural Environment Research Council, European Commission

Methodology for direct reflectance measurement from a drone: system description, radiometric calibration and latest results

L Markelin, J Suomalainen, T Hakala, R Oliveira, N Viljanen, R Näsi, ...

International Archives of the Photogrammetry, Remote Sensing & Spatial …, 2018

Mandati: Academy of Finland

Combining YOLO V5 and Transfer Learning for Smoke-Based Wildfire Detection in Boreal Forests

AM Raita-Hakola, S Rahkonen, J Suomalainen, L Markelin, R Oliveira, ...

The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2023

Mandati: Academy of Finland