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We performed a two\u2010step classification process of automatic image segmentation and object\u2010based classification to distinguish between four pre\u2010defined classes (waterlogged bare peat, <jats:italic><jats:styled-content style=\"fixed-case\">S<\/jats:styled-content>phagnum<\/jats:italic> spp., <jats:italic><jats:styled-content style=\"fixed-case\">E<\/jats:styled-content>riophorum vaginatum<\/jats:italic> and <jats:italic><jats:styled-content style=\"fixed-case\">B<\/jats:styled-content>etula pubescens<\/jats:italic>. An independent validation procedure was performed to evaluate the accuracy of the classification.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A set\u2010up composed of decision rules for reflectance, geometry and textural features was applied for identification of the four classes. The presented classification revealed an overall accuracy level of 91%. Most reliable attribution was obtained for waterlogged bare peat and <jats:italic><jats:styled-content style=\"fixed-case\">S<\/jats:styled-content>phagnum<\/jats:italic>\u2010covered surfaces, revealing producer accuracies of 95% and 91%, respectively. Lower but still feasible accuracy levels were obtained for <jats:italic><jats:styled-content style=\"fixed-case\">E<\/jats:styled-content>riophorum vaginatum<\/jats:italic> and <jats:italic><jats:styled-content style=\"fixed-case\">B<\/jats:styled-content>etula pubescens<\/jats:italic> individuals (89% and 84%, respectively).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p><jats:styled-content style=\"fixed-case\">UAV<\/jats:styled-content>\u2010based <jats:styled-content style=\"fixed-case\">NIR<\/jats:styled-content> remote sensing is a promising tool for monitoring the restoration of cut\u2010over bogs and has the potential to significantly reduce laborious field surveys. <jats:styled-content style=\"fixed-case\">UAV<\/jats:styled-content>s may increasingly play a significant role in future ecological monitoring studies, since they are small in size, highly flexible, easy to handle, non\u2010emissive and available at a comparatively low cost.<\/jats:p><\/jats:sec>","DOI":"10.1111\/avsc.12024","type":"journal-article","created":{"date-parts":[[2013,1,25]],"date-time":"2013-01-25T14:08:39Z","timestamp":1359122919000},"page":"509-517","source":"Crossref","is-referenced-by-count":106,"title":["Unmanned aerial vehicles as innovative remote sensing platforms for high\u2010resolution infrared imagery to support restoration monitoring in cut\u2010over bogs"],"prefix":"10.1111","volume":"16","author":[{"given":"Christian","family":"Knoth","sequence":"first","affiliation":[{"name":"Institute for Geoinformatics University of M\u00fcnster Weseler Stra\u00dfe 253 48151 M\u00fcnster Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Birte","family":"Klein","sequence":"additional","affiliation":[{"name":"Institute for Geoinformatics University of M\u00fcnster Weseler Stra\u00dfe 253 48151 M\u00fcnster Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Torsten","family":"Prinz","sequence":"additional","affiliation":[{"name":"Institute for Geoinformatics University of M\u00fcnster Weseler Stra\u00dfe 253 48151 M\u00fcnster Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Till","family":"Kleinebecker","sequence":"additional","affiliation":[{"name":"Institute of Landscape Ecology University of M\u00fcnster Robert\u2010Koch Str. 28 48149 M\u00fcnster Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2013,1,25]]},"reference":[{"key":"e_1_2_8_2_1","volume-title":"Small\u2010format aerial photography. 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