{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T09:50:53Z","timestamp":1778233853438,"version":"3.51.4"},"reference-count":26,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,28]],"date-time":"2021-12-28T00:00:00Z","timestamp":1640649600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Recently, remotely sensed data obtained via laser technology has gained great importance due to its wide use in several fields, especially in 3D urban modeling. In fact, 3D city models in urban environments are efficiently employed in many fields, such as military operations, emergency management, building and height mapping, cadastral data upgrading, monitoring of changes as well as virtual reality. These applications are essentially composed of models of structures, urban elements, ground surface and vegetation. This paper presents a workflow for modeling the structure of buildings by using laser-scanned data (LiDAR) and multi-spectral images in order to develop a 3D web service for a smart city concept. Optical vertical photography is generally utilized to extract building class, while LiDAR data is used as a source of information to create the structure of the 3D building. The building reconstruction process presented in this study can be divided into four main stages: building LiDAR points extraction, piecewise horizontal roof clustering, boundaries extraction and 3D geometric modeling. Finally, an architecture for a 3D smart service based on the CityGML interchange format is proposed.<\/jats:p>","DOI":"10.3390\/rs14010114","type":"journal-article","created":{"date-parts":[[2021,12,28]],"date-time":"2021-12-28T06:55:03Z","timestamp":1640674503000},"page":"114","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Graph-Based Classification and Urban Modeling of Laser Scanning and Imagery: Toward 3D Smart Web Services"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3417-6277","authenticated-orcid":false,"given":"Slim","family":"Namouchi","sequence":"first","affiliation":[{"name":"Software Engineering, Distributed Applications, Decision Systems and Intelligent Imaging Research Laboratory (RIADI), National School of Computer Science (ENSI), University of Manouba, Manouba 2010, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9114-5659","authenticated-orcid":false,"given":"Imed","family":"Farah","sequence":"additional","affiliation":[{"name":"Software Engineering, Distributed Applications, Decision Systems and Intelligent Imaging Research Laboratory (RIADI), National School of Computer Science (ENSI), University of Manouba, Manouba 2010, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Li, L., Yao, J., Tu, J., Liu, X., Li, Y., and Guo, L. (2020). Roof Plane Segmentation from Airborne LiDAR Data Using Hierarchical Clustering and Boundary Relabeling. Remote Sens., 12.","DOI":"10.3390\/rs12091363"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1080\/19479832.2013.811124","article-title":"3D building modeling using images and LiDAR: A review","volume":"4","author":"Wang","year":"2013","journal-title":"Int. J. Image Data Fusion"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Namouchi, S., Vallet, B., Farah, I.R., and Ismail, H. (August, January 28). Piecewise Horizontal 3D Roof Reconstruction from Aerial Lidar. Proceedings of the IGARSS 2019\u20132019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan.","DOI":"10.1109\/IGARSS.2019.8898650"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.isprsjprs.2003.09.006","article-title":"Reconstruction of 3D building models from aerial images and maps","volume":"58","author":"Suveg","year":"2004","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2016.04.005","article-title":"3D building reconstruction from ALS data using unambiguous decomposition into elementary structures","volume":"118","author":"Borkowski","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_6","unstructured":"Verma, V., Kumar, R., and Hsu, S. (2006, January 17\u201322). 3D building detection and modeling from aerial LIDAR data. Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR\u201906), New York, NY, USA."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Jarzabek-Rychard, M., and Maas, H.G. (2016, January 14\u201316). Aerial image based geometric refinement of building models derived from airborne lidar data. Proceedings of the GEOBIA 2016: Solutions and Synergies, Enschede, The Netherlands.","DOI":"10.3990\/2.422"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Albeaik, S., Alrished, M., Aldawood, S., Alsubaiee, S., and Alfaris, A. (2017, January 6\u20139). Virtual Cities: 3D Urban Modeling from Low Resolution LiDAR Data. Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Association for Computing Machinery, New York, NY, USA.","DOI":"10.1145\/3139958.3140025"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Nouvel, R., Schulte, C., Eicker, U., Pietruschka, D., and Coors, V. (2013, January 26\u201328). CityGML-based 3D City Model for Energy Diagnostics and Urban Energy Policy Support. Proceedings of the BS2013: 13th Conference of International Building Performance Simulation Association, Chamb\u00e9ry, France.","DOI":"10.26868\/25222708.2013.989"},{"key":"ref_10","first-page":"601","article-title":"3D web visualization of huge CityGML models","volume":"XL-3\/W3","author":"Prandi","year":"2015","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_11","first-page":"W1","article-title":"Using citygml to deploy smart-city services for urban ecosystems","volume":"4","author":"Prandi","year":"2013","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_12","first-page":"73","article-title":"Virtual 3d City Modeling: Techniques and Applications","volume":"XL-2\/W2","author":"Singh","year":"2013","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_13","unstructured":"(2018, September 12). ISPRS Test Project on Urban Classification, 3D Building Reconstruction and Semantic Labeling. Available online: http:\/\/www2.isprs.org\/commissions\/comm3\/wg4\/tests.html."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2842","DOI":"10.3390\/ijgi4042842","article-title":"Applications of 3D City Models: State of the Art Review","volume":"4","author":"Biljecki","year":"2015","journal-title":"ISPRS Int. J. Geo-Inf."},{"key":"ref_15","unstructured":"(2019, February 12). ISPRS Test Project on Urban Classification and 3D Building Reconstruction. Available online: https:\/\/www2.isprs.org\/media\/komfssn5\/complexscenes_revision_v4.pdf."},{"key":"ref_16","unstructured":"(2018, September 12). Berlin 3D Building Models in Level of Detail 2 (LoD 2). Available online: Https:\/\/fbinter.stadt-berlin.de\/fb\/index.jsp."},{"key":"ref_17","first-page":"1384","article-title":"Cut Pursuit: Fast algorithms to learn piecewise constant functions","volume":"51","author":"Landrieu","year":"2016","journal-title":"Artif. Intell. Stat."},{"key":"ref_18","unstructured":"Whaten-Dunn, W. (1967). A Transformation for Extracting New Descriptors of Shape. Symposium on Models forSpeech and Visual Form, MIT Press."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Megahed, Y., Shaker, A., and Yan, W.Y. (2021). Fusion of Airborne LiDAR Point Clouds and Aerial Images for Heterogeneous Land-Use Urban Mapping. Remote Sens., 13.","DOI":"10.3390\/rs13040814"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Rusu, R.B., and Cousins, S. (2011, January 9\u201313). 3D is here: Point Cloud Library (PCL). Proceedings of the 2011 IEEE International Conference on Robotics and Automation, Shanghai, China.","DOI":"10.1109\/ICRA.2011.5980567"},{"key":"ref_21","unstructured":"(2018, November 12). The Computational Geometry Algorithms Library (CGAL). Available online: https:\/\/www.cgal.org\/."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/S0146-664X(72)80017-0","article-title":"An iterative procedure for the polygonal approximation of plane curves","volume":"1","author":"Ramer","year":"1972","journal-title":"Comput. Graph. Image Process."},{"key":"ref_23","unstructured":"(2018, November 12). Cloud Compare Software for 3D Point Cloud and Triangular Mesh Processing Tool. Available online: http:\/\/cloudcompare.org."},{"key":"ref_24","unstructured":"Sithole, G., and Vosselman, G. (2021, June 12). Report: ISPRS comparison of filters. ISPRS Comm. III Work. Group, Available online: https:\/\/studylib.net\/doc\/11841668\/comparison-of-filtering-algorithms-george-sithole--george."},{"key":"ref_25","unstructured":"(2021, July 12). 3D Geospatial Visualization for the Web. Available online: Https:\/\/cesium.com\/platform\/cesiumjs\/."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.compenvurbsys.2016.04.005","article-title":"An improved LOD specification for 3D building models","volume":"59","author":"Biljecki","year":"2016","journal-title":"Comput. Environ. Urban"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/114\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:54:42Z","timestamp":1760169282000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/114"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,28]]},"references-count":26,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["rs14010114"],"URL":"https:\/\/doi.org\/10.3390\/rs14010114","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,28]]}}}