{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T15:51:32Z","timestamp":1776181892570,"version":"3.50.1"},"reference-count":50,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2013,10,14]],"date-time":"2013-10-14T00:00:00Z","timestamp":1381708800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Imaging using lightweight, unmanned airborne vehicles (UAVs) is one of the most rapidly developing fields in remote sensing technology. The new, tunable,  Fabry-Perot interferometer-based (FPI) spectral camera, which weighs less than 700 g, makes it possible to collect spectrometric image blocks with stereoscopic overlaps using light-weight UAV platforms. This new technology is highly relevant, because it opens up new possibilities for measuring and monitoring the environment, which is becoming increasingly important for many environmental challenges. Our objectives were to investigate the processing and use of this new type of image data in precision agriculture. We developed the entire processing chain from raw images up to georeferenced reflectance images, digital surface models and biomass estimates. The processing integrates photogrammetric and quantitative remote sensing approaches. We carried out an empirical assessment using FPI spectral imagery collected at an agricultural wheat test site in the summer of 2012. Poor weather conditions during the campaign complicated the data processing, but this is one of the challenges that are faced in operational applications. The results indicated that the camera performed consistently and that the data processing was consistent, as well. During the agricultural experiments, promising results were obtained for biomass estimation when the spectral data was used and when an appropriate radiometric correction was applied to the data. Our results showed that the new FPI technology has a great potential in precision agriculture and indicated many possible future research topics.<\/jats:p>","DOI":"10.3390\/rs5105006","type":"journal-article","created":{"date-parts":[[2013,10,14]],"date-time":"2013-10-14T11:11:20Z","timestamp":1381749080000},"page":"5006-5039","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":398,"title":["Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture"],"prefix":"10.3390","volume":"5","author":[{"given":"Eija","family":"Honkavaara","sequence":"first","affiliation":[{"name":"Finnish Geodetic Institute, Geodeetinrinne 2, P.O. Box 15, FI-02431 Masala, Finland"}]},{"given":"Heikki","family":"Saari","sequence":"additional","affiliation":[{"name":"VTT Photonic Devices and Measurement Solutions, P.O. Box 1000, FI-02044 VTT, Finland"}]},{"given":"Jere","family":"Kaivosoja","sequence":"additional","affiliation":[{"name":"MTT Agrifood Research Finland, Vakolantie 55, FI-03400 Vihti, Finland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5129-7364","authenticated-orcid":false,"given":"Ilkka","family":"P\u00f6l\u00f6nen","sequence":"additional","affiliation":[{"name":"Department of Mathematical Information Technology, University of Jyv\u00e4skyl\u00e4, P.O. Box 35,  FI-40014 Jyv\u00e4skyl\u00e4, Finland"}]},{"given":"Teemu","family":"Hakala","sequence":"additional","affiliation":[{"name":"Finnish Geodetic Institute, Geodeetinrinne 2, P.O. Box 15, FI-02431 Masala, Finland"}]},{"given":"Paula","family":"Litkey","sequence":"additional","affiliation":[{"name":"Finnish Geodetic Institute, Geodeetinrinne 2, P.O. Box 15, FI-02431 Masala, Finland"}]},{"given":"Jussi","family":"M\u00e4kynen","sequence":"additional","affiliation":[{"name":"VTT Photonic Devices and Measurement Solutions, P.O. Box 1000, FI-02044 VTT, Finland"}]},{"given":"Liisa","family":"Pesonen","sequence":"additional","affiliation":[{"name":"MTT Agrifood Research Finland, Vakolantie 55, FI-03400 Vihti, Finland"}]}],"member":"1968","published-online":{"date-parts":[[2013,10,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"290","DOI":"10.3390\/rs2010290","article-title":"Acquisition of NIR-Green-Blue digital photographs from unmanned aircraft for crop monitoring","volume":"2","author":"Hunt","year":"2010","journal-title":"Remote Sens"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3557","DOI":"10.3390\/s8053557","article-title":"Assessment of unmanned aerial vehicles imagery for quantitative monitoring of wheat crop in small plots","volume":"8","author":"Lelong","year":"2008","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"739","DOI":"10.1109\/TGRS.2008.2006505","article-title":"Near real-time orthorectification and mosaic of small UAV video flow for time-critical event response","volume":"47","author":"Zhou","year":"2009","journal-title":"IEEE Trans. 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