{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T16:11:02Z","timestamp":1772208662577,"version":"3.50.1"},"reference-count":79,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,2,3]],"date-time":"2024-02-03T00:00:00Z","timestamp":1706918400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Polish National Centre for Research and Development","award":["DZP\/BIOSTRATEG-II\/390\/2015"],"award-info":[{"award-number":["DZP\/BIOSTRATEG-II\/390\/2015"]}]},{"name":"Polish National Centre for Research and Development","award":["SWIB 2\/2024"],"award-info":[{"award-number":["SWIB 2\/2024"]}]},{"name":"Faculty of Geography and Regional Studies of the University of Warsaw","award":["DZP\/BIOSTRATEG-II\/390\/2015"],"award-info":[{"award-number":["DZP\/BIOSTRATEG-II\/390\/2015"]}]},{"name":"Faculty of Geography and Regional Studies of the University of Warsaw","award":["SWIB 2\/2024"],"award-info":[{"award-number":["SWIB 2\/2024"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The mapping of invasive plant species is essential for effective ecosystem control and planning, especially in protected areas. One of the widespread invasive plants that threatens the species richness of Natura 2000 habitats in Europe is the large-leaved lupine (Lupinus polyphyllus). In our study, this species was identified at two Natura 2000 sites in southern Poland using airborne HySpex hyperspectral images, and support vector machine (SVM) and random forest (RF) classifiers. Aerial and field campaigns were conducted three times during the 2016 growing season (May, August, and September). An iterative accuracy assessment was performed, and the influence of the number of minimum noise fraction (MNF) bands on the obtained accuracy of lupine identification was analyzed. The highest accuracies were obtained for the August campaign using 30 MNF bands as input data (median F1 score for lupine was 0.82\u20130.85), with lower accuracies for the May (F1 score: 0.77\u20130.81) and September (F1 score: 0.78\u20130.80) campaigns. The use of more than 30 MNF bands did not significantly increase the classification accuracy. The SVM and RF algorithms allowed us to obtain comparable results in both research areas (OA: 89\u201394%). The method of the multiple classification and thresholding of frequency images allowed the results of many predictions to be included in the final map.<\/jats:p>","DOI":"10.3390\/rs16030580","type":"journal-article","created":{"date-parts":[[2024,2,5]],"date-time":"2024-02-05T09:31:58Z","timestamp":1707125518000},"page":"580","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Airborne Hyperspectral Images and Machine Learning Algorithms for the Identification of Lupine Invasive Species in Natura 2000 Meadows"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8954-5047","authenticated-orcid":false,"given":"Anita","family":"Sabat-Tomala","sequence":"first","affiliation":[{"name":"Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, ul. Krakowskie Przedmie\u015bcie 30, 00-927 Warsaw, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4843-9955","authenticated-orcid":false,"given":"Edwin","family":"Raczko","sequence":"additional","affiliation":[{"name":"Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, ul. Krakowskie Przedmie\u015bcie 30, 00-927 Warsaw, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7882-5318","authenticated-orcid":false,"given":"Bogdan","family":"Zagajewski","sequence":"additional","affiliation":[{"name":"Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, ul. Krakowskie Przedmie\u015bcie 30, 00-927 Warsaw, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4128","DOI":"10.1111\/gcb.13021","article-title":"Global Trade Will Accelerate Plant Invasions in Emerging Economies under Climate Change","volume":"21","author":"Seebens","year":"2015","journal-title":"Glob. Chang. Biol."},{"key":"ref_2","first-page":"103158","article-title":"Which Factors Determine the Invasion of Plant Species? Machine Learning Based Habitat Modelling Integrating Environmental Factors and Climate Scenarios","volume":"116","author":"Sittaro","year":"2023","journal-title":"Int. J. Appl. Earth Obs. 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