{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T20:55:02Z","timestamp":1777496102756,"version":"3.51.4"},"reference-count":10,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    This paper provides an overview of a small research project. The object of the research was a 16 km\n                    <jats:sup>2<\/jats:sup>\n                    forested area located in the territory of J\u00e4rvselja Study and Experimental Forest, Estonia, which was damaged by storms in June 2021. The aim of the study was to investigate whether it is possible and reasonable to estimate the area of storm damage using orthophotos created from photographs collected from unmanned aircraft. The surveying was carried out on July 13\u201315, 2021. The data was collected via unmanned aerial vehicles with RGB-cameras on board. A multi-rotor drone DJI Phantom 3 Professional and a fixed-wing unmanned aircraft eBee X were used. In total, the eBee drone was flown 11 times to obtain 11,989 photos and the DJI drone 18 times to obtain 2,471 photos. During the project, it became clear that if there are open fields available, it is more efficient to use a fixed-wing type drone for this kind of research. However, in more difficult conditions where there are no clearances suitable for take-off and landing, a multi-rotor drone, such as the DJI, can be used instead. It can be concluded from the results of the work that although it is possible to use an unmanned aircraft for aerial photography of large forested areas, it takes a considerable amount of time for both photography and post-processing. It took 96 man-hours to collect the data and four working weeks to process the data.\n                  <\/jats:p>","DOI":"10.2478\/fsmu-2022-0007","type":"journal-article","created":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T09:39:00Z","timestamp":1676885940000},"page":"99-105","source":"Crossref","is-referenced-by-count":1,"title":["J\u00e4rvselja metsade tormikahjustuste seire mehitamata \u00f5hus\u00f5idukitega"],"prefix":"10.2478","volume":"76","author":[{"given":"Kaupo","family":"Kokam\u00e4gi","sequence":"first","affiliation":[{"name":"Estonian University of Life Sciences , Institute of Agricultural and Environmental Sciences , Kreutzwaldi 5 , Tartu , Estonia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rauno","family":"K\u00fcnnapuu","sequence":"additional","affiliation":[{"name":"Estonian University of Life Sciences , Institute of Forestry and Engineering , Kreutzwaldi 5 , Tartu , Estonia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natalja","family":"Liba","sequence":"additional","affiliation":[{"name":"Estonian University of Life Sciences , Institute of Forestry and Engineering , Kreutzwaldi 5 , Tartu , Estonia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2023,2,20]]},"reference":[{"key":"2026042802452451283_j_fsmu-2022-0007_ref_001","doi-asserted-by":"crossref","unstructured":"Brovkina, O., Cienciala, E., Surov\u00fd, P., Janata, P. 2018. Unmanned aerial vehicles (UAV) for assessment of qualitative classification of Norway spruce in temperate forest stands. \u2013 Geo-spatial Information Science, 21(1), 12\u201320. https:\/\/doi.org\/10.1080\/10095020.2017.1416994.","DOI":"10.1080\/10095020.2017.1416994"},{"key":"2026042802452451283_j_fsmu-2022-0007_ref_002","unstructured":"DJI. [WWW document]. \u2013 URL https:\/\/www.dji.com\/ee\/phantom-3-pro. [Accessed 7 June 2022]."},{"key":"2026042802452451283_j_fsmu-2022-0007_ref_003","unstructured":"Keskkonnaamet. 2010. Nature protection management plan 2012\u20132021 for J\u00e4rvselja nature reserve. (J\u00e4rvselja looduskaitseala kaitsekorralduskava 2012\u20132021). [WWW document]. \u2013 URL https:\/\/infoleht.keskkonnainfo.ee\/GetFile.aspx?fail=-406250147. [Accessed 7 June 2022]. (In Estonian)."},{"key":"2026042802452451283_j_fsmu-2022-0007_ref_004","unstructured":"Kokam\u00e4gi, K., T\u00fcrk, K., Liba, N. 2020. UAV photogrammetry for volume calculations. \u2013 Agronomy Research, 18(3), 2087\u22122102."},{"key":"2026042802452451283_j_fsmu-2022-0007_ref_005","doi-asserted-by":"crossref","unstructured":"Laurin, G.V., Francini, S., Luti, T., Chirici, G., Pirotti, F., Papale, D. 2021. Satellite open data to monitor forest damage caused by extreme climate-induced events: a case study of the Vaia storm in Northern Italy. \u2013 Forestry: An International Journal of Forest Research, 94(3), 407\u2013416. https:\/\/doi.org\/10.1093\/forestry\/cpaa043.","DOI":"10.1093\/forestry\/cpaa043"},{"key":"2026042802452451283_j_fsmu-2022-0007_ref_006","doi-asserted-by":"crossref","unstructured":"Mina\u0159\u00edk, R., Langhammer, J. 2016. Use of a multispectral UAV photogrammetry for detection and tracking of forest disturbance dynamics. \u2013 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B8, 711\u2013718. http:\/\/dx.doi.org\/10.5194\/isprsarchives-XLI-B8-711-2016.","DOI":"10.5194\/isprs-archives-XLI-B8-711-2016"},{"key":"2026042802452451283_j_fsmu-2022-0007_ref_007","unstructured":"Rahu, O., Siim, K. 2022. Assessment of storm damage in the J\u00e4rvselja Training and Experimental Forestry District by photogrammetric methods. (J\u00e4rvselja \u00f5ppeja katsemetskonna tormikahjude hindamine fotogrammmeetriliste meetoditega). \u2013 Master thesis. Tartu, Estonian University of Life Sciences. 91 pp. (In Estonian with English summary)."},{"key":"2026042802452451283_j_fsmu-2022-0007_ref_008","unstructured":"SenseFly. [WWW document]. \u2013 URL https:\/\/www.sensefly.com\/drone\/ebee-x-fixed-wing-drone\/. [Accessed 7 June 2022]."},{"key":"2026042802452451283_j_fsmu-2022-0007_ref_009","doi-asserted-by":"crossref","unstructured":"Tang, L., Shao, G. 2015. Drone remote sensing for forestry research and practices. \u2013 Journal of Forestry Research, 26, 791\u2013797. https:\/\/doi.org\/10.1007\/s11676-015-0088-y.","DOI":"10.1007\/s11676-015-0088-y"},{"key":"2026042802452451283_j_fsmu-2022-0007_ref_010","doi-asserted-by":"crossref","unstructured":"Tomppo, E., Ronoud, G., Antropov, O., Hyt\u00f6nen, H., Praks, J. 2021. Detection of forest windstorm damages with multitemporal SAR data \u2013 A case study: Finland. \u2013 Remote Sensing, 13(3), 383. https:\/\/doi.org\/10.3390\/rs13030383.","DOI":"10.3390\/rs13030383"}],"container-title":["Forestry Studies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/reference-global.com\/pdf\/10.2478\/fsmu-2022-0007","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T15:02:59Z","timestamp":1777388579000},"score":1,"resource":{"primary":{"URL":"https:\/\/reference-global.com\/article\/10.2478\/fsmu-2022-0007"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,1]]},"references-count":10,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,2,20]]},"published-print":{"date-parts":[[2022,12,1]]}},"alternative-id":["10.2478\/fsmu-2022-0007"],"URL":"https:\/\/doi.org\/10.2478\/fsmu-2022-0007","relation":{},"ISSN":["1736-8723"],"issn-type":[{"value":"1736-8723","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,1]]}}}