E
Eija Honkavaara
Researcher at Finnish Geodetic Institute
Publications - 175
Citations - 5819
Eija Honkavaara is an academic researcher from Finnish Geodetic Institute. The author has contributed to research in topics: Hyperspectral imaging & Photogrammetry. The author has an hindex of 37, co-authored 160 publications receiving 4493 citations. Previous affiliations of Eija Honkavaara include National Land Survey of Finland.
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Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight UAV spectral camera for precision agriculture
Eija Honkavaara,Heikki Saari,Jere Kaivosoja,Ilkka Pölönen,Teemu Hakala,Paula Litkey,Jussi Mäkynen,Liisa Pesonen +7 more
TL;DR: This work carried out an empirical assessment using FPI spectral imagery collected at an agricultural wheat test site in the summer of 2012, and developed the entire processing chain from raw images up to georeferenced reflectance images, digital surface models and biomass estimates.
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Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows
TL;DR: This review evaluates the state-of-the-art methods in UAV spectral remote sensing and discusses sensor technology, measurement procedures, geometric processing, and radiometric calibration based on the literature and more than a decade of experimentation.
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Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging
Olli Nevalainen,Eija Honkavaara,Sakari Tuominen,Niko Viljanen,Teemu Hakala,Xiaowei Yu,Juha Hyyppä,Heikki Saari,Ilkka Pölönen,Nilton Nobuhiro Imai,Antonio Maria Garcia Tommaselli +10 more
TL;DR: Results were promising, indicating that hyperspectral 3D remote sensing was operational from a UAV platform even in very difficult conditions, and are expected to provide a powerful tool for automating various environmental close-range remote sensing tasks in the very near future.
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Using UAV-based photogrammetry and hyperspectral imaging for mapping bark beetle damage at tree-level
Roope Näsi,Eija Honkavaara,Päivi Lyytikäinen-Saarenmaa,Minna Blomqvist,Paula Litkey,Teemu Hakala,Niko Viljanen,Tuula Kantola,Topi-Mikko Tapio Tanhuanpää,Markus Holopainen +9 more
TL;DR: A new processing method for analyzing spectral characteristic for high spatial resolution photogrammetric and hyperspectral images in forested environments, as well as for identifying individual anomalous trees, which will be of a high practical value for forest health management.
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Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera
Tomi Rosnell,Eija Honkavaara +1 more
TL;DR: Recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation are given.