{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T09:00:33Z","timestamp":1771664433800,"version":"3.50.1"},"reference-count":45,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T00:00:00Z","timestamp":1687996800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Faculty of Geoengi neering of the University of Warmia and Mazury in Olsztyn, Poland","award":["No. 29.610.008-110"],"award-info":[{"award-number":["No. 29.610.008-110"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The development of autonomous navigation systems requires digital building models at the LoD3 level. Buildings with atypically shaped features, such as turrets, domes, and chimneys, should be selected as landmark objects in these systems. The aim of this study was to develop a method that automatically transforms segmented LiDAR (Light Detection And Ranging) point cloud to create such landmark building models. A detailed solution was developed for selected buildings that are solids of revolution. The algorithm relies on new methods for determining building axes and cross-sections. To handle the gaps in vertical cross-sections due to the absence of continuous measurement data, a new strategy for filling these gaps was proposed based on their automatic interpretation. In addition, potential points associated with building ornaments were used to improve the model. The results were presented in different stages of the modeling process in graphic models and in a matrix recording. Our work demonstrates that complicated buildings can be represented with a light and regular data structure. Further investigations are needed to estimate the constructed building model with vectorial models.<\/jats:p>","DOI":"10.3390\/rs15133324","type":"journal-article","created":{"date-parts":[[2023,6,30]],"date-time":"2023-06-30T01:02:41Z","timestamp":1688086961000},"page":"3324","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Modeling Multi-Rotunda Buildings at LoD3 Level from LiDAR Data"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4952-4350","authenticated-orcid":false,"given":"Fayez","family":"Tarsha Kurdi","sequence":"first","affiliation":[{"name":"School of Surveying and Built Environment, Faculty of Health, Engineering and Sciences, University of Southern Queensland, Springfield Campus, Springfield, QLD 4300, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8847-2835","authenticated-orcid":false,"given":"El\u017cbieta","family":"Lewandowicz","sequence":"additional","affiliation":[{"name":"Faculty of Geoengineering, Institute of Geodesy and Civil Engineering, Department of Geoinformation and Cartography, University Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0913-151X","authenticated-orcid":false,"given":"Zahra","family":"Gharineiat","sequence":"additional","affiliation":[{"name":"School of Surveying and Built Environment, Faculty of Health, Engineering and Sciences, University of Southern Queensland, Springfield Campus, Springfield, QLD 4300, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1948-9657","authenticated-orcid":false,"given":"Jie","family":"Shan","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Richa, J.P., Deschaud, J.-E., Goulette, F., and Dalmasso, N. 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