{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T19:40:55Z","timestamp":1774986055038,"version":"3.50.1"},"reference-count":98,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010665","name":"H2020 Marie Sk\u0142odowska-Curie Actions","doi-asserted-by":"publisher","award":["H2020-MSCA-RISE-2016: innoVation in geospatial and 3D data\u2014VOLTA, grant agreement No. 734687"],"award-info":[{"award-number":["H2020-MSCA-RISE-2016: innoVation in geospatial and 3D data\u2014VOLTA, grant agreement No. 734687"]}],"id":[{"id":"10.13039\/100010665","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004569","name":"Ministerstwo Nauki i Szkolnictwa Wy\u017cszego","doi-asserted-by":"publisher","award":["No. 3934\/H2020\/2018\/2"],"award-info":[{"award-number":["No. 3934\/H2020\/2018\/2"]}],"id":[{"id":"10.13039\/501100004569","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004569","name":"Ministerstwo Nauki i Szkolnictwa Wy\u017cszego","doi-asserted-by":"publisher","award":["379067\/PnH\/2017 in the period 2017\u20132021"],"award-info":[{"award-number":["379067\/PnH\/2017 in the period 2017\u20132021"]}],"id":[{"id":"10.13039\/501100004569","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Mountain forests are exposed to extreme conditions (e.g., strong winds and intense solar radiation) and various types of damage by insects such as bark beetles, which makes them very sensitive to climatic changes. Therefore, continuous monitoring is crucial, and remote-sensing techniques allow the monitoring of transboundary areas where a common policy is needed to protect and monitor the environment. In this study, we used Sentinel-2 and Landsat 8 open data to assess the forest stands classification of the UNESCO Krkono\u0161e\/Karkonosze Transboundary Biosphere Reserve, which is undergoing dynamic changes in recovering woodland vegetation due to an ecological disaster that led to damage and death of a large portion of the forests. Currently, in this protected area, dry big trunks and branches coexist with naturally occurring young forests. This heterogeneity generates mixes, which hinders the automation of classification. Thus, we used three machine learning algorithms\u2014Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN)\u2014to classify dominant tree species (birch, beech, larch and spruce). The best results were obtained for the SVM RBF classifier, which offered an average median F1-score that oscillated around 67.2\u201391.5% depending on the species. The obtained maps, which were based on multispectral satellite images, were also compared with classifications made for the same area on the basis of hyperspectral APEX imagery (288 spectral bands with three-meter resolution), indicating high convergence in the recognition of woody species.<\/jats:p>","DOI":"10.3390\/rs13132581","type":"journal-article","created":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T12:03:27Z","timestamp":1625141007000},"page":"2581","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":70,"title":["Comparison of Random Forest, Support Vector Machines, and Neural Networks for Post-Disaster Forest Species Mapping of the Krkono\u0161e\/Karkonosze Transboundary Biosphere Reserve"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7882-5318","authenticated-orcid":false,"given":"Bogdan","family":"Zagajewski","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\/0000-0003-2133-0984","authenticated-orcid":false,"given":"Marcin","family":"Kluczek","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\/0000-0003-4843-9955","authenticated-orcid":false,"given":"Edwin","family":"Raczko","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"}]},{"given":"Ajda","family":"Njegovec","sequence":"additional","affiliation":[{"name":"Geodetski Zavod Celje d.o.o., 3000 Celje, Slovenia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6020-8634","authenticated-orcid":false,"given":"Anca","family":"Dabija","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":[[2021,7,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-020-15881-x","article-title":"Topography and human pressure in mountain ranges alter expected species responses to climate change","volume":"11","author":"Elsen","year":"2020","journal-title":"Nat. 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