{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T06:55:11Z","timestamp":1775112911504,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2021,10,13]],"date-time":"2021-10-13T00:00:00Z","timestamp":1634083200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100012774","name":"Innovationsfonden","doi-asserted-by":"publisher","award":["6180-00016B"],"award-info":[{"award-number":["6180-00016B"]}],"id":[{"id":"10.13039\/100012774","id-type":"DOI","asserted-by":"publisher"}]},{"name":"EU Bonus Ecomap","award":["---"],"award-info":[{"award-number":["---"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Boulders on the seabed in coastal marine environments provide key geo- and ecosystem functions and services. They serve as natural coastal protection by dissipating wave energy, and they form an important hard substrate for macroalgae, and hence for coastal marine reefs that serve as important habitats for fish. The aim of this study was to investigate the possibility of developing an automated method to classify boulders from topo-bathymetric LiDAR data in coastal marine environments. The R\u00f8dsand lagoon in Denmark was used as study area. A 100 m \u00d7 100 m test site was divided into a training and a test set. The classification was performed using the random forest machine learning algorithm. Different tuning parameters were tested. The study resulted in the development of a nearly automated method to classify boulders from topo-bathymetric LiDAR data. Different measure scores were used to evaluate the performance. For the best parameter combination, the recall of the boulders was 57%, precision was 27%, and F-score 37%, while the accuracy of the points was 99%. The most important tuning parameters for boulder classification were the subsampling level, the choice of the neighborhood radius, and the features. Automatic boulder detection will enable transparent, reproducible, and fast detection and mapping of boulders.<\/jats:p>","DOI":"10.3390\/rs13204101","type":"journal-article","created":{"date-parts":[[2021,10,13]],"date-time":"2021-10-13T21:48:39Z","timestamp":1634161719000},"page":"4101","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Classification of Boulders in Coastal Environments Using Random Forest Machine Learning on Topo-Bathymetric LiDAR Data"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9933-841X","authenticated-orcid":false,"given":"Signe Schilling","family":"Hansen","sequence":"first","affiliation":[{"name":"Department of Geosciences and Natural Resource Management, University of Copenhagen, DK-1350 Copenhagen, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0849-2938","authenticated-orcid":false,"given":"Verner Brandbyge","family":"Ernstsen","sequence":"additional","affiliation":[{"name":"Department of Geosciences and Natural Resource Management, University of Copenhagen, DK-1350 Copenhagen, Denmark"},{"name":"Department of Marine Geology, Geological Survey of Denmark and Greenland, C.F. M\u00f8llers All\u00e9 8, Bygning 1110, DK-8000 Aarhus, Denmark"}]},{"given":"Mikkel Skovgaard","family":"Andersen","sequence":"additional","affiliation":[{"name":"Department of Marine Geology, Geological Survey of Denmark and Greenland, C.F. M\u00f8llers All\u00e9 8, Bygning 1110, DK-8000 Aarhus, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7448-017X","authenticated-orcid":false,"given":"Zyad","family":"Al-Hamdani","sequence":"additional","affiliation":[{"name":"Department of Marine Geology, Geological Survey of Denmark and Greenland, C.F. M\u00f8llers All\u00e9 8, Bygning 1110, DK-8000 Aarhus, Denmark"}]},{"given":"Ramona","family":"Baran","sequence":"additional","affiliation":[{"name":"Airborne HydroMapping GmbH, Feldstr. 1b, 6020 Innsbruck, Austria"}]},{"given":"Manfred","family":"Niederwieser","sequence":"additional","affiliation":[{"name":"Airborne HydroMapping GmbH, Feldstr. 1b, 6020 Innsbruck, Austria"}]},{"given":"Frank","family":"Steinbacher","sequence":"additional","affiliation":[{"name":"Airborne HydroMapping GmbH, Feldstr. 1b, 6020 Innsbruck, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9419-2327","authenticated-orcid":false,"given":"Aart","family":"Kroon","sequence":"additional","affiliation":[{"name":"Department of Geosciences and Natural Resource Management, University of Copenhagen, DK-1350 Copenhagen, Denmark"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,13]]},"reference":[{"key":"ref_1","unstructured":"Al-Hamdani, Z., Jensen, J.B., Skar, S., N\u00f8rgaard-Pedersen, N., Leth, J.O., Lomholt, S., Bennike, O., Granat, H., Andersen, M.S., and R\u00f6del, L.G. 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