{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T14:08:07Z","timestamp":1776521287296,"version":"3.51.2"},"reference-count":87,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T00:00:00Z","timestamp":1620691200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004488","name":"Hrvatska Zaklada za Znanost","doi-asserted-by":"publisher","award":["HRZZ IP-2016-06-7686"],"award-info":[{"award-number":["HRZZ IP-2016-06-7686"]}],"id":[{"id":"10.13039\/501100004488","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Horizon 2020","award":["776045"],"award-info":[{"award-number":["776045"]}]},{"DOI":"10.13039\/100008993","name":"Sveu\u010dili\u0161te u Zagrebu","doi-asserted-by":"publisher","award":["RS4ENVIRO"],"award-info":[{"award-number":["RS4ENVIRO"]}],"id":[{"id":"10.13039\/100008993","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Quality tree species information gathering is the basis for making proper decisions in forest management. By applying new technologies and remote sensing methods, very high resolution (VHR) satellite imagery can give sufficient spatial detail to achieve accurate species-level classification. In this study, the influence of pansharpening of the WorldView-3 (WV-3) satellite imagery on classification results of three main tree species (Quercus robur L., Carpinus betulus L., and Alnus glutinosa (L.) Geartn.) has been evaluated. In order to increase tree species classification accuracy, three different pansharpening algorithms (Bayes, RCS, and LMVM) have been conducted. The LMVM algorithm proved the most effective pansharpening technique. The pixel- and object-based classification were applied to three pansharpened imageries using a random forest (RF) algorithm. The results showed a very high overall accuracy (OA) for LMVM pansharpened imagery: 92% and 96% for tree species classification based on pixel- and object-based approach, respectively. As expected, the object-based exceeded the pixel-based approach (OA increased by 4%). The influence of fusion on classification results was analyzed as well. Overall classification accuracy was improved by the spatial resolution of pansharpened images (OA increased by 7% for pixel-based approach). Also, regardless of pixel- or object-based classification approaches, the influence of the use of pansharpening is highly beneficial to classifying complex, natural, and mixed deciduous forest areas.<\/jats:p>","DOI":"10.3390\/rs13101868","type":"journal-article","created":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T11:30:16Z","timestamp":1620732616000},"page":"1868","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["An Evaluation of Pixel- and Object-Based Tree Species Classification in Mixed Deciduous Forests Using Pansharpened Very High Spatial Resolution Satellite Imagery"],"prefix":"10.3390","volume":"13","author":[{"given":"Martina","family":"Deur","sequence":"first","affiliation":[{"name":"Institute for Spatial Planning of \u0160ibenik-Knin County, Vladimira Nazora 1\/IV, 22000 \u0160ibenik, Croatia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2345-7882","authenticated-orcid":false,"given":"Mateo","family":"Ga\u0161parovi\u0107","sequence":"additional","affiliation":[{"name":"Chair of Photogrammetry and Remote Sensing, Faculty of Geodesy, University of Zagreb, 10000 Zagreb, Croatia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7422-753X","authenticated-orcid":false,"given":"Ivan","family":"Balenovi\u0107","sequence":"additional","affiliation":[{"name":"Division for Forest Management and Forestry Economics, Croatian Forest Research Institute, Trnjanska cesta 35, 10000 Zagreb, Croatia"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Balenovi\u0107, I., Simic Milas, A., and Marjanovi\u0107, H. 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