{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T21:37:22Z","timestamp":1775943442756,"version":"3.50.1"},"reference-count":107,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Warsaw Faculty of Geography and Regional Studies","award":["SWIB\/4\/2022"],"award-info":[{"award-number":["SWIB\/4\/2022"]}]},{"name":"University of Warsaw Excellence Initiative \u2013 Research University","award":["IDUB"],"award-info":[{"award-number":["IDUB"]}]},{"name":"Ministry of Education and Science (Ministerstwo Edukacji i Nauki)","award":["3934\/H2020\/2018\/2"],"award-info":[{"award-number":["3934\/H2020\/2018\/2"]}]},{"name":"Ministry of Education and Science (Ministerstwo Edukacji i Nauki)","award":["379067\/PnH\/2017"],"award-info":[{"award-number":["379067\/PnH\/2017"]}]},{"DOI":"10.13039\/501100000780","name":"European Union","doi-asserted-by":"publisher","award":["H2020-MSCA-RISE-2016 GA No. 734687"],"award-info":[{"award-number":["H2020-MSCA-RISE-2016 GA No. 734687"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Climate change and anthropopression significantly impact plant communities by leading to the spread of expansive and alien invasive plants, thus reducing their biodiversity. Due to significant elevation gradients, high-mountain plant communities in a small area allow for the monitoring of the most important environmental changes. Additionally, being a tourist attraction, they are exposed to direct human influence (e.g., trampling). Airborne hyperspectral remote sensing is one of the best data sources for vegetation mapping, but flight campaign costs limit the repeatability of surveys. A possible alternative approach is to use satellite data from the Copernicus Earth observation program. In our study, we compared multitemporal Sentinel-2 data with HySpex airborne hyperspectral images to map the plant communities on Tatra Mountains based on open-source R programing implementation of Random Forest and Support Vector Machine classifiers. As high-mountain ecosystems are adapted to topographic conditions, the input of Digital Elevation Model (DEM) derivatives on the classification accuracy was analyzed and the effect of the number of training pixels was tested to procure practical information for field campaign planning. For 13 classes (from rock scree communities and alpine grasslands to montane conifer and deciduous forests), we achieved results in the range of 76\u201390% F1-score depending on the data set. Topographic features: digital terrain model (DTM), normalized digital surface model (nDSM), and aspect and slope maps improved the accuracy of HySpex spectral images, transforming their minimum noise fraction (MNF) bands and Sentinel-2 data sets by 5\u201315% of the F1-score. Maps obtained on the basis of HySpex imagery (2 m; 430 bands) had a high similarity to maps obtained on the basis of multitemporal Sentinel-2 data (10 m; 132 bands; 11 acquisition dates), which was less than one percentage point for classifications based on 500\u20131000 pixels; for sets consisting of 50\u2013100 pixels, Random Forest (RF) offered better accuracy.<\/jats:p>","DOI":"10.3390\/rs14051209","type":"journal-article","created":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T21:25:14Z","timestamp":1646169914000},"page":"1209","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Airborne HySpex Hyperspectral Versus Multitemporal Sentinel-2 Images for Mountain Plant Communities Mapping"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2133-0984","authenticated-orcid":false,"given":"Marcin","family":"Kluczek","sequence":"first","affiliation":[{"name":"Department of Geoinformatics Cartography and Remote Sensing, Chair of Geomatics and Information Systems, Faculty of Geography and Regional Studies, University of Warsaw, 00-927 Warszawa, 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, Chair of Geomatics and Information Systems, Faculty of Geography and Regional Studies, University of Warsaw, 00-927 Warszawa, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5133-3727","authenticated-orcid":false,"given":"Marlena","family":"Kycko","sequence":"additional","affiliation":[{"name":"Department of Geoinformatics Cartography and Remote Sensing, Chair of Geomatics and Information Systems, Faculty of Geography and Regional Studies, University of Warsaw, 00-927 Warszawa, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1177\/0309133319843873","article-title":"Mountain plant communities: Uncertain sentinels?","volume":"43","author":"Malanson","year":"2019","journal-title":"Prog. 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