{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T04:40:08Z","timestamp":1766983208441,"version":"build-2065373602"},"reference-count":63,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,4,7]],"date-time":"2018-04-07T00:00:00Z","timestamp":1523059200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004569","name":"Ministerstwo Nauki i Szkolnictwa Wyzszego","doi-asserted-by":"publisher","award":["501-D119-64-0180200-15"],"award-info":[{"award-number":["501-D119-64-0180200-15"]}],"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>Mapping plant communities is a difficult and time consuming endeavor. Methods relying on field surveys deliver high quality data but are usually limited to relatively small areas. In this paper we apply airborne hyperspectral data to vegetation mapping in remote and hard to reach areas. We classified 22 vegetation communities in the Giant Mountains on 3.12-m Airborne Prism Experiment (APEX) hyperspectral images, registered in 288 spectral bands (10 September 2012). As the classification algorithm, Support Vector Machines (SVM) was used. APEX data were corrected geometrically and atmospherically, and three dimensionality reduction methods were performed to select the best dataset. As reference we used a non-forest vegetation map containing vegetation communities of Polish Karkonosze National Park from 2002, orthophotomap and field surveys data from 2013 to 2014. We obtained the post-classification maps of 22 vegetation communities, lakes and areas without any vegetation. Iterative accuracy assessment repeated 100 times was used to obtain the most objective results for individual communities. The median value of overall accuracy (OA) was 84%. Fourteen out of twenty-four classes were classified of more than 80% of producer accuracy (PA) and sixteen out of twenty-four of user accuracy (UA). APEX data and SVM with the use of iterative accuracy assessment are useful for the mountain communities classification. This can support both Polish and Czech national parks management by giving the information about diversity of communities in the whole transboundary area, helping with identification especially in changing environment caused by humans.<\/jats:p>","DOI":"10.3390\/rs10040570","type":"journal-article","created":{"date-parts":[[2018,4,10]],"date-time":"2018-04-10T13:06:08Z","timestamp":1523365568000},"page":"570","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Classification of High-Mountain Vegetation Communities within a Diverse Giant Mountains Ecosystem Using Airborne APEX Hyperspectral Imagery"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9080-3899","authenticated-orcid":false,"given":"Adriana","family":"Marcinkowska-Ochtyra","sequence":"first","affiliation":[{"name":"Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw (UW), Krakowskie Przedmiescie 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 (UW), Krakowskie Przedmiescie 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 (UW), Krakowskie Przedmiescie 30, 00-927 Warsaw, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4799-8093","authenticated-orcid":false,"given":"Adrian","family":"Ochtyra","sequence":"additional","affiliation":[{"name":"Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw (UW), Krakowskie Przedmiescie 30, 00-927 Warsaw, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3610-4656","authenticated-orcid":false,"given":"Anna","family":"Jaroci\u0144ska","sequence":"additional","affiliation":[{"name":"Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw (UW), Krakowskie Przedmiescie 30, 00-927 Warsaw, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2018,4,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"K\u00f6rner, C. (1994). Impact of atmospheric changes on high mountain vegetation. Mountain Environments in Changing Climates, Routledge.","DOI":"10.4324\/9780203424957_chapter_9"},{"key":"ref_2","first-page":"1","article-title":"Strefy przej\u015bcia mi\u0119dzy uk\u0142adami ro\u015blinnymi-analiza wieloskalowa (na przyk\u0142adzie roslinno\u015bci g\u00f3rskiej)","volume":"Volume 215","year":"2008","journal-title":"Prace Geograficzne"},{"key":"ref_3","unstructured":"Mirek, Z. (1996). Zbiorowiska ro\u015blinne. Przyroda Tatrza\u0144skiego Parku Narodowego, Tatrza\u0144ski Park Narodowy."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1007\/s11258-005-0063-3","article-title":"Use of digital aerial photography for sub-alpine vegetation mapping: A case study from the Krkono\u0161e Mts., Czech Republic","volume":"175","year":"2005","journal-title":"Plant Ecol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1111\/j.1467-8306.1983.tb01399.x","article-title":"Biophysical remote sensing","volume":"73","author":"Jensen","year":"1983","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_6","first-page":"1","article-title":"Assessment of neural networks and Imaging Spectroscopy for vegetation classification of the High Tatras","volume":"43","author":"Zagajewski","year":"2010","journal-title":"Teledetekcja \u015arodowiska"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1007\/s13157-012-0373-x","article-title":"Object-based vegetation mapping in the Kissimmee River watershed using HyMap data and machine learning techniques","volume":"33","author":"Zhang","year":"2013","journal-title":"Wetlands"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2046","DOI":"10.3390\/rs70202046","article-title":"Classification of herbaceous vegetation using airborne hyperspectral imagery","volume":"7","author":"Burai","year":"2015","journal-title":"Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1080\/22797254.2017.1274573","article-title":"Classification of Tundra Vegetation in the Krkono\u0161e Mts. National Park Using APEX, AISA Dual and Sentinel-2A Data","volume":"50","author":"Zagajewski","year":"2017","journal-title":"Eur. J. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1016\/S0034-4257(02)00133-5","article-title":"Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data","volume":"84","author":"Kokaly","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1016\/j.rse.2005.11.007","article-title":"Fuzzy learning vector quantization for hyperspectral coastal vegetation classification","volume":"100","author":"Filippi","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3609","DOI":"10.1080\/01431160701469099","article-title":"Mapping an inland wetland complex using hyperspectral imagery","volume":"29","author":"Jollineau","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2999","DOI":"10.1016\/j.rse.2008.02.011","article-title":"Evaluation of Random Forest and Adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery","volume":"112","author":"Chan","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_14","first-page":"125","article-title":"Wykorzystanie obraz\u00f3w hiperspektralnych do klasyfikacji pokrycia terenu zlewni Bystrzanki","volume":"40","author":"Olesiuk","year":"2008","journal-title":"Teledetekcja \u015arodowiska"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Delalieux, S., Somers, B., Haest, B., Kooistra, L., M\u00fccher, C.A., and Vanden Borre, J. (2010, January 14\u201316). Monitoring heathland habitat status using hyperspectral image classification and unmixing. Proceedings of the 2nd Whispers on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Iceland.","DOI":"10.1109\/WHISPERS.2010.5594895"},{"key":"ref_16","first-page":"49","article-title":"A framework for mapping tree species combining hyperspectral and LiDAR data: Role of selected classifiers and sensor across three spatial scales","volume":"26","author":"Ghosh","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2547","DOI":"10.1109\/JSTARS.2014.2329390","article-title":"Comparison of feature reduction algorithms for classifying tree species with hyperspectral data on three central European test sites","volume":"7","author":"Fassnacht","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_18","first-page":"28","article-title":"Forest species mapping using airborne hyperspectral APEX data","volume":"20","author":"Tagliabue","year":"2016","journal-title":"Misc. Geogr."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1080\/22797254.2017.1299557","article-title":"Comparison of Support Vector Machine, Random Forest and Neural Network Classifiers for Tree Species Classification on Airborne Hyperspectral APEX images","volume":"50","author":"Raczko","year":"2017","journal-title":"Eur. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1016\/j.rse.2006.10.007","article-title":"Mapping mixed vegetation communities in salt marshes using airborne spectral data","volume":"107","author":"Wang","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.isprsjprs.2007.01.004","article-title":"Discrimination of blackberry (Rubus fruticosus sp. agg.) using hyperspectral imagery in Kosciuszko National Park, NSW, Australia","volume":"62","author":"Dehaan","year":"2007","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1530","DOI":"10.1109\/TGRS.2004.827262","article-title":"Robust support vector method for hyperspectral data classification and knowledge discovery","volume":"42","author":"Moreno","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","first-page":"13","article-title":"An evaluation of ensemble classifiers for mapping Natura 2000 heathland in Belgium using spaceborne angular hyperspectral (CHRIS\/Proba) imagery","volume":"18","author":"Chan","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2895","DOI":"10.1080\/01431160500185227","article-title":"Some issues in the classification of DAIS hyperspectral data","volume":"27","author":"Pal","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1778","DOI":"10.1109\/TGRS.2004.831865","article-title":"Classification of Hyperspectral Remote Sensing Images with Support Vector Machines","volume":"42","author":"Melgani","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","unstructured":"Marcinkowska-Ochtyra, A., Zagajewski, B., Ochtyra, A., Jaroci\u0144ska, A., Raczko, E., and Wojtu\u0144, B. (2016, January 20\u201324). Mapping subalpine and alpine vegetation using APEX hyperspectral data. Proceedings of the 36th EARSeL Symposium 2016, Bonn, Germany."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"6235","DOI":"10.3390\/s8106235","article-title":"APEX\u2014The hyperspectral ESA airborne prism experiment","volume":"8","author":"Itten","year":"2008","journal-title":"Sensors"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"5344","DOI":"10.1364\/AO.53.005344","article-title":"Impacts of dichroic prism coatings on radiometry of the airborne imaging spectrometer APEX","volume":"53","author":"Hueni","year":"2014","journal-title":"Appl. Opt."},{"key":"ref_29","first-page":"16","article-title":"Atmospheric correction of APEX hyperspectral data","volume":"20","author":"Sterckx","year":"2016","journal-title":"Misc Geogr."},{"key":"ref_30","first-page":"11","article-title":"Geometric correction of APEX hyperspectral data","volume":"20","author":"Vreys","year":"2016","journal-title":"Misc Geogr."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.isprsjprs.2013.10.012","article-title":"Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping","volume":"87","author":"Demarchi","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_32","first-page":"23","article-title":"Mapping vegetation communities of Karkonosze National Park using APEX hyperspectral data and Support Vector Machines","volume":"18","author":"Marcinkowska","year":"2014","journal-title":"Misc. Geogr."},{"key":"ref_33","first-page":"21","article-title":"The application of APEX images in the assessment of the state of non-forest vegetation in the Karkonosze Mountains","volume":"20","author":"Kacprzyk","year":"2016","journal-title":"Misc. Geogr."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1839","DOI":"10.1080\/01431161.2016.1274447","article-title":"Subalpine and Alpine Vegetation Classification based on Hyperspectral APEX and Simulated EnMAP images","volume":"38","author":"Zagajewski","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_35","first-page":"113","article-title":"Classification of vegetation above the tree line in the Krkono\u0161e Mts. National Park using remote sensing multispectral data","volume":"51","year":"2016","journal-title":"Acta Univ. Carol. Geogr."},{"key":"ref_36","unstructured":"Knapik, R., and Raj, A. (2013). Ro\u015blinno\u015b\u0107 Subalpejska I Alpejska. Przyroda Karkonoskiego Parku Narodowego, Karkonoski Park Narodowy."},{"key":"ref_37","first-page":"5","article-title":"Arctic-alpine tundra in the Krkono\u0161e, the Sudetes","volume":"32","author":"Sekyra","year":"1995","journal-title":"Opera Corcon."},{"key":"ref_38","unstructured":"Knapik, R., and Raj, A. (2013). Klimat. Przyroda Karkonoskiego Parku Narodowego, Karkonoski Park Narodowy."},{"key":"ref_39","unstructured":"Dunajski, A. (2016, January 12\u201314). Huge dieback of the tall fern community (Athyrietum distentifolii). Proceedings of the 9th Conference Geoecological Problems of the Krkono\u0161e\/Karkonosze Mountains: The International Scientific Conference: Past, Present and Future of Transboundary Cooperation in Research and Management, Karkonoski Park Narodowy, Szklarska Por\u0119ba, Poland."},{"key":"ref_40","unstructured":"Paw\u0142owski, B. (1967). Flora Polska, PWN."},{"key":"ref_41","unstructured":"\u017bo\u0142nierz, L., Wojtu\u0144, B., and Przewo\u017anik, L. (2012). Ekosystemy Niele\u015bne Karkonoskiego Parku Narodowego, Karkonoski Park Narodowy."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1016\/j.flora.2010.04.019","article-title":"Control of Molinia caerulea by cutting management on sub-alpine grassland","volume":"205","author":"Hejcman","year":"2010","journal-title":"Flora Morphol. Distrib. Funct. Ecol. Plants"},{"key":"ref_43","first-page":"45","article-title":"Mapa zbiorowisk ro\u015blinnych Karkonoskiego Parku Narodowego","volume":"40","author":"Matuszkiewicz","year":"1974","journal-title":"Ochr. Przyr."},{"key":"ref_44","unstructured":"Knapik, R., and Raj, A. (2013). Lasy. Przyroda Karkonoskiego Parku Narodowego, Karkonoski Park Narodowy."},{"key":"ref_45","unstructured":"Wojtu\u0144, B., and \u017bo\u0142nierz, L. (2002). Plan Ochrony Ekosystem\u00f3w Niele\u015bnych\u2014Inwentaryzacja Zbiorowisk, Plan Ochrony Karkonoskiego Parku Narodowego."},{"key":"ref_46","unstructured":"Itten, K.I., Schaepman, M., De Vos, L., Hermans, L., Schlaepfer, H., Space, O.C., and Droz, F. (1997, January 7\u201310). APEX\u2013airborne prism experiment a new concept for an airborne imaging spectrometer. Proceedings of the Third International Airborne Remote Sensing Conference and Exhibition, Copenhagen, Denmark."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.rse.2011.10.028","article-title":"Object-based cloud and cloud shadow detection in Landsat imagery","volume":"118","author":"Zhu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1037\/h0071325","article-title":"Analysis of a complex of statistical variables into principal components","volume":"24","author":"Hotelling","year":"1933","journal-title":"J. Educat. Psychol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1109\/36.3001","article-title":"A transformation for ordering multispectral data in terms of image quality with implications for noise removal","volume":"26","author":"Green","year":"1988","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"John, G.H., Kohavi, R., and Pfleger, K. (1994, January 10\u201313). Irrelevant features and the subset selection problem. Proceedings of the Eleventh International Machine Learning Conference, Rutgers University, New Brunswick, NJ, USA.","DOI":"10.1016\/B978-1-55860-335-6.50023-4"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Vapnik, V.N. (1995). The Nature of Statistical Learning Theory, Springer.","DOI":"10.1007\/978-1-4757-2440-0"},{"key":"ref_52","unstructured":"Gualtieri, J.A., and Cromp, R.F. Support vector machines for hyperspectral remote sensing classification. Proceedings of the 27th AIPR Workshop: Advances in Computer Assisted Recognition;."},{"key":"ref_53","unstructured":"Hsu, C.W., Chang, C.C., and Lin, C.J. (2010). A Practical Guide to Support Vector Classification, National Taiwan University. Available online: https:\/\/ntu.csie.org\/~cjlin\/papers\/guide\/guide.pdf."},{"key":"ref_54","unstructured":"Liao, R. (2016, September 05). Support Vector Machines, CSC 411 Tutorial. Available online: https:\/\/.cs.toronto.edu\/~urtasun\/courses\/CSC411\/tutorial9.pdf."},{"key":"ref_55","unstructured":"Meyer, D., Dimitriadou, E., Hornik, K., Weingessel, A., and Leisch, F. (2017, December 15). e1071: Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien. Available online: https:\/\/CRAN.R-project.org\/package=e1071."},{"key":"ref_56","unstructured":"R Core Team (2017). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. Available online: https:\/\/www.R-project.org\/."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(91)90048-B","article-title":"A review of assessing the accuracy of classifications of remotely sensed data","volume":"37","author":"Congalton","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_58","unstructured":"Marcinkowska-Ochtyra, A. (2016). Assessment of APEX Hyperspectral Images and Support Vector Machines for Karkonosze Subalpine and Alpine Vegetation Classification. [Ph.D. Thesis, University of Warsaw]."},{"key":"ref_59","first-page":"593","article-title":"Forest species identification of Mount Chojnik (Karkonoski National Park) using airborne hyperspectal APEX data","volume":"159","author":"Raczko","year":"2015","journal-title":"Sylwan"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1109\/TGRS.2004.827257","article-title":"A relative evaluation of multi-class image classification by support vector machines","volume":"42","author":"Foody","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1505","DOI":"10.1016\/j.asoc.2007.10.012","article-title":"Parameter determination of support vector machine and feature selection using simulated annealing approach","volume":"8","author":"Lin","year":"2008","journal-title":"Appl. Soft Comput."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"2880","DOI":"10.1109\/TGRS.2010.2041784","article-title":"Sensitivity of Support Vector Machines to Random Feature Selection in Classification of Hyperspectral Data","volume":"48","author":"Waske","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_63","unstructured":"Kotarba, A., and Koz\u0142owska, A. (1999). Problemy kartowania ro\u015blinno\u015bci wysokog\u00f3rskiej w skali szczeg\u00f3\u0142owej (na przyk\u0142adzie map ro\u015blinno\u015bci Kot\u0142a G\u0105sienicowego i Goryczkowego \u015awi\u0144skiego). Badania Geoekologiczne w Otoczeniu Kasprowego Wierchu, Wydawnictwo Continuo. Prace Geograficzne, Volume 174."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/4\/570\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:59:54Z","timestamp":1760194794000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/4\/570"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4,7]]},"references-count":63,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2018,4]]}},"alternative-id":["rs10040570"],"URL":"https:\/\/doi.org\/10.3390\/rs10040570","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2018,4,7]]}}}