Search Results - Holopainen, Roope

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  1. 1
    Efficacy of immersive extended reality (XR) interventions on different symptom domains of schizophrenia spectrum disorders. A systematic review

    Efficacy of immersive extended reality (XR) interventions on different symptom domains of schizophrenia spectrum disorders. A systematic review by Holopainen, Roope, Tiihonen, Jari, Lähteenvuo, Markku

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  2. 2
    Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level

    Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level by Näsi, Roope, Honkavaara, Eija, Lyytikäinen-Saarenmaa, Päivi, Blomqvist, Minna, Litkey, Paula, Hakala, Teemu, Viljanen, Niko, Kantola, Tuula, Tanhuanpää, Topi, Holopainen, Markus

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  3. 3
    Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft

    Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft by Näsi, Roope, Honkavaara, Eija, Blomqvist, Minna, Lyytikäinen-Saarenmaa, Päivi, Hakala, Teemu, Viljanen, Niko, Kantola, Tuula, Holopainen, Markus

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  4. 4
    Multispectral Imagery Provides Benefits for Mapping Spruce Tree Decline Due to Bark Beetle Infestation When Acquired Late in the Season

    Multispectral Imagery Provides Benefits for Mapping Spruce Tree Decline Due to Bark Beetle Infestation When Acquired Late in the Season by Junttila, Samuli, Näsi, Roope, Koivumäki, Niko, Imangholiloo, Mohammad, Saarinen, Ninni, Raisio, Juha, Holopainen, Markus, Hyyppä, Hannu, Hyyppä, Juha, Lyytikäinen-Saarenmaa, Päivi, Vastaranta, Mikko, Honkavaara, Eija

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  5. 5
    Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

    Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging by Saarinen, Ninni, Vastaranta, Mikko, Näsi, Roope, Rosnell, Tomi, Hakala, Teemu, Honkavaara, Eija, Wulder, Michael, Luoma, Ville, Tommaselli, Antonio, Imai, Nilton, Ribeiro, Eduardo, Guimarães, Raul, Holopainen, Markus, Hyyppä, Juha

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  6. 6
    Characterizing Seedling Stands Using Leaf-Off and Leaf-On Photogrammetric Point Clouds and Hyperspectral Imagery Acquired from Unmanned Aerial Vehicle

    Characterizing Seedling Stands Using Leaf-Off and Leaf-On Photogrammetric Point Clouds and Hyperspectral Imagery Acquired from Unmanned Aerial Vehicle by Imangholiloo, Mohammad, Saarinen, Ninni, Markelin, Lauri, Rosnell, Tomi, Näsi, Roope, Hakala, Teemu, Honkavaara, Eija, Holopainen, Markus, Hyyppä, Juha, Vastaranta, Mikko

    Published in Forests
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  7. 7
    Close-Range Remote Sensing of Forests: The state of the art, challenges, and opportunities for systems and data acquisitions

    Close-Range Remote Sensing of Forests: The state of the art, challenges, and opportunities for systems and data acquisitions by Liang, Xinlian, Kukko, Antero, Balenovic, Ivan, Saarinen, Ninni, Junttila, Samuli, Kankare, Ville, Holopainen, Markus, Mokros, Martin, Surovy, Peter, Kaartinen, Harri, Jurjevic, Luka, Honkavaara, Eija, Nasi, Roope, Liu, Jingbin, Hollaus, Markus, Tian, Jiaojiao, Yu, Xiaowei, Pan, Jie, Cai, Shangshu, Virtanen, Juho-Pekka, Wang, Yunsheng, Hyyppa, Juha

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  8. 8
    Data for estimating spruce tree health using drone-based RGB and multispectral imagery

    Data for estimating spruce tree health using drone-based RGB and multispectral imagery by Junttila, Samuli, Näsi, Roope, Koivumäki, Niko, Imangholiloo, Mohammad, Saarinen, Ninni, Raisio, Juha, Holopainen, Markus, Hyyppä, Hannu, Hyyppä, Juha, Lyytikäinen-Saarenmaa, Päivi, Vastaranta, Mikko, Honkavaara, Eija

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