{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T04:06:49Z","timestamp":1776226009654,"version":"3.50.1"},"reference-count":57,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2020,2,27]],"date-time":"2020-02-27T00:00:00Z","timestamp":1582761600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The aim of this paper is to highlight how the employment of Light Detection and Ranging (LiDAR) technique can enhance greatly the performance and reliability of many monitoring systems applied to the Earth Observation (EO) and Environmental Monitoring. A short presentation of LiDAR systems, underlying their peculiarities, is first given. References to some review papers are highlighted, as they can be regarded as useful guidelines for researchers interested in using LiDARs. Two case studies are then presented and discussed, based on the use of 2D and 3D LiDAR data. Some considerations are done on the performance achieved through the use of LiDAR data combined with data from other sources. The case studies show how the LiDAR-based systems, combined with optical Very High Resolution (VHR) data, succeed in improving the analysis and monitoring of specific areas of interest, specifically how LiDAR data help in exploring external environment and extracting building features from urban areas. Moreover the discussed Case Studies demonstrate that the use of the LiDAR data, even with a low density of points, allows the development of an automatic procedure for accurate building features extraction, through object-oriented classification techniques, therefore by underlying the importance that even simple LiDAR-based systems play in EO and Environmental Monitoring.<\/jats:p>","DOI":"10.3390\/s20051285","type":"journal-article","created":{"date-parts":[[2020,2,28]],"date-time":"2020-02-28T09:30:36Z","timestamp":1582882236000},"page":"1285","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["LiDAR-Based System and Optical VHR Data for Building Detection and Mapping"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6294-0581","authenticated-orcid":false,"given":"Silvia Liberata","family":"Ullo","sequence":"first","affiliation":[{"name":"Engineering Department, University of Sannio, 82100 Benevento, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chiara","family":"Zarro","sequence":"additional","affiliation":[{"name":"Engineering Department, University of Sannio, 82100 Benevento, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6185-5465","authenticated-orcid":false,"given":"Konrad","family":"Wojtowicz","sequence":"additional","affiliation":[{"name":"Faculty of Mechatronics and Aerospace, Military University of Technology, 00-908 Warsaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2590-9806","authenticated-orcid":false,"given":"Giuseppe","family":"Meoli","sequence":"additional","affiliation":[{"name":"Mapsat, 82100 Benevento, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1408-3460","authenticated-orcid":false,"given":"Mariano","family":"Focareta","sequence":"additional","affiliation":[{"name":"Mapsat, 82100 Benevento, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,27]]},"reference":[{"key":"ref_1","unstructured":"(2004, May 24). Available online: http:\/\/www.asprs.org\/a\/society\/committees\/lidar\/Downloads\/Vertical_Accuracy_Reporting_for_Lidar_Data.pdf."},{"key":"ref_2","unstructured":"(2020, February 25). Available online: https:\/\/www.marketsandmarkets.com\/Market-Reports\/airborne-lidar-market-171546900.html."},{"key":"ref_3","first-page":"24","article-title":"Airborne LiDAR sensors","volume":"21","author":"Lemmens","year":"2007","journal-title":"GIM Int."},{"key":"ref_4","first-page":"52","article-title":"Airborne LiDAR processing software","volume":"21","author":"Lemmens","year":"2007","journal-title":"GIM Int."},{"key":"ref_5","first-page":"16","article-title":"Airborne LiDAR sensors","volume":"23","author":"Lemmens","year":"2009","journal-title":"GIM Int."},{"key":"ref_6","first-page":"14","article-title":"Airborne LiDAR processing software","volume":"24","author":"Lemmens","year":"2010","journal-title":"GIM Int."},{"key":"ref_7","unstructured":"Renslow, M.S. (2012). Manual of Airborne Topographic LiDAR, American Society for Photogrammetry and Remote Sensing (ASPRS)."},{"key":"ref_8","first-page":"256","article-title":"Results of the ISPRS benchmark on urban object detection and 3D building reconstruction","volume":"93","author":"Rottensteiner","year":"2013","journal-title":"ISPRS"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zarro, C., and Ullo, S.L. (2019, January 19\u201321). High-resolution topographic surveys and earth features extraction through LiDARs. Discussion of some Case Studies. Proceedings of the IEEE Metrology for Aerospace, Turin, Italy.","DOI":"10.1109\/MetroAeroSpace.2019.8869695"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/j.rse.2014.11.001","article-title":"Urban land cover classification using airborne LiDAR data: A review","volume":"158","author":"Yang","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Fiscante, N., Focareta, M., Galdi, C., and Ullo, S.L. (2012, January 22\u201327). Analysis and validation of high-resolution satellite DEMs generated from EROS-B data for Montaguto landslide. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2012, IGARSS 2012, Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6351884"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Ullo, S.L., Addabbo, P., Di Bisceglie, M., Galdi, C., Focareta, M., and Maffei, C. (2015, January 26\u201331). Combination of LANDSAT and EROS-B satellite images with GPS and LiDAR data for land monitoring. A case study: The Sant\u2019Arcangelo Trimonte dump. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2015, IGARSS 2015, Milan, Italy.","DOI":"10.1109\/IGARSS.2015.7325906"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/MAES.2019.2918043","article-title":"Experimental Tests of the Obstacles Detection Technique in the Hemispherical Area for an Underground Explorer UAV","volume":"34","author":"Rochala","year":"2019","journal-title":"IEEE Aerosp. Electron. Syst. Mag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3826","DOI":"10.3390\/rs70403826","article-title":"Building Extraction from Airborne Laser Scanning Data: An Analysis of the State of the Art","volume":"7","author":"Tomljenovic","year":"2015","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Jamali, A., Kumar, P., and Rahman, A.A. (2019, January 1\u20133). Automated extraction of buildings from aerial LiDAR point clouds and digital imaging datasets. Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-4\/W16, 6th International Conference on Geomatics and Geospatial Technology (GGT 2019), Kuala Lumpur, Malaysia.","DOI":"10.5194\/isprs-archives-XLII-4-W16-303-2019"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Ekhtari, N., Zoej, M.J.V., Sahebi, M.R., and Mohammadzadeh, A. (2009). Automatic building extraction from LIDAR digital elevation models and WorldView imagery. J. App. Remote Sens., 14.","DOI":"10.1117\/1.3284718"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1080\/22797254.2017.1314179","article-title":"A metaheuristic feature-level fusion strategy in classification of urban area using hyperspectral imagery and LiDAR data","volume":"50","author":"Hasani","year":"2017","journal-title":"Eur. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/19479832.2016.1160960","article-title":"Advances in fusion of optical imagery and LiDAR point cloud applied to photogrammetry and remote sensing","volume":"8","author":"Zhang","year":"2017","journal-title":"Int. J. Image Data Fusion"},{"key":"ref_19","unstructured":"(2011, December 22). Available online: http:\/\/ambiente.regione.emilia-romagna.it\/it\/geologia\/temi\/costa\/il-rilievo-lidar#autotoc-item-autotoc-7."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"73","DOI":"10.5721\/EuJRS20164905","article-title":"Accuracy of tree geometric parameters depending on the LiDAR data density","volume":"49","author":"Hadas","year":"2016","journal-title":"Eur. J. Remote Sens."},{"key":"ref_21","unstructured":"Jackson, K.F. (2012). Development and Evaluation of a Collision Avoidance System for Supervisory Control of a Micro Aerial Vehicle. [Master\u2019s Thesis, Massachusetts Institute of Thechnology]."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Lange, S., Sunderhauf, N., Neudert, P., Drews, S., and Protzel, O. (2012). Autonomous Corridor Flight of a UAV Using a Low-Cost and Light-Weight RGB-D Camera. Advances in Autonomous Mini Roobots, Springer.","DOI":"10.1007\/978-3-642-27482-4_19"},{"key":"ref_23","unstructured":"Gageik, G., Muller, T., and Montenegro, S. (2012, January 20\u201321). Obstacle detection and collision aviodance using ultrasonic distance sensors for an autonomous quadrocopter. Proceedings of the 1st microdrones International Research Workshop UAVWeek 2012, Siegen, Germany."},{"key":"ref_24","unstructured":"Rochala, Z., Wojtowicz, K., Kordowski, P., and Brzozowski, B. (2014, January 29\u201330). Distance measurement technique in hemispherical area for indoor vertical take-off and landing unmanned aerial vehicle. Proceedings of the IEEE Metrology for Aerospace (MetroAeroSpace), Benevento, Italy."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"341","DOI":"10.5772\/56813","article-title":"An Autonomous UAV with an Optical Flow Sensor for Positioning and Navigation","volume":"10","author":"Gageik","year":"2013","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Krajnik, T., Nitsche, M., Pedre, S., Preucil, L., and Mejail, M.E. (2012, January 20\u201323). A simple visual navigation system for an UAV. Proceedings of the 9th International Multi-Conference on Systems, Signals and Devices, Chemnitz, Germany.","DOI":"10.1109\/SSD.2012.6198031"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zsedrovits, T., Zarandy, A., Vanek, B., Peni, T., Bokor, J., and Roska, T. (2011, January 15\u201318). Collision avoidance for UAV using visual detection. Proceedings of the IEEE International Symposium on Circuits and Systems 2011, Rio de Janeiro, Brazil.","DOI":"10.1109\/ISCAS.2011.5938030"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Hsu, C.-M., and Shiu, C.-W. (2019). 3D LiDAR-Based Precision Vehicle Localization with Movable Region Constraints. Sensors, 19.","DOI":"10.3390\/s19040942"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Blanco-Claraco, J.L., Ma\u00f1as-Alvarez, F., Torres-Moreno, J.L., Rodriguez, F., and Gimenez-Fernandez, A. (2019). Benchmarking Particle Filter Algorithms for Efficient Velodyne-Based Vehicle Localization. Sensors, 19.","DOI":"10.3390\/s19143155"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Im, J.-H., Im, S.-H., and Jee, G.-I. (2018). Extended Line Map-Based Precise Vehicle Localization Using 3D LIDAR. Sensors, 18.","DOI":"10.3390\/s18103179"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Huang, L., Chen, S., Zhang, J., Cheng, B., and Liu, M. (2017). Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor. Sensors, 17.","DOI":"10.3390\/s17091932"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zhang, W., Qiu, W., Song, D., and Xie, B. (2019). Automatic Tunnel Steel Arches Extraction Algorithm Based on 3D LiDAR Point Cloud. Sensors, 19.","DOI":"10.3390\/s19183972"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Ren, Z., Wang, L., and Bi, L. (2019). Robust GICP-Based 3D LiDAR SLAM for Underground Mining Environment. Sensors, 19.","DOI":"10.3390\/s19132915"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.1080\/01431160110075802","article-title":"Using a time series of satellite imagery to detect land use and land cover changes in the Atlanta, Georgia metropolitan area","volume":"23","author":"Yang","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3119","DOI":"10.1080\/01431160701469065","article-title":"An object-oriented approach for analysing and characterizing urban landscape at the parcel level","volume":"29","author":"Zhou","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"928","DOI":"10.1109\/LGRS.2013.2251453","article-title":"An Object-Based Approach for Urban Land Cover Classification: Integrating LiDAR Height and Intensity Data","volume":"10","author":"Zhou","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"85","DOI":"10.5721\/EuJRS20154806","article-title":"Monitoring land use changes associated with urbanization: An object based image analysis approach","volume":"48","author":"Samal","year":"2015","journal-title":"Eur. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.isprsjprs.2009.06.004","article-title":"Object based image analysis for remote sensing","volume":"65","author":"Blaschke","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1769","DOI":"10.1016\/j.rse.2009.04.007","article-title":"Object-based land cover classification of shaded areas in high spatial resolution imagery of urban areas: A comparison study","volume":"113","author":"Zhou","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_40","unstructured":"(2020, February 25). Available online: http:\/\/www.pcn.minambiente.it\/mattm\/progetto-piano-straordinario-di-telerilevamento."},{"key":"ref_41","unstructured":"Tomljenovic, I., and Rousell, A. (2014, January 3\u201316). Influence of point cloud density on the results of automated object-based building extraction from ALS data. Proceedings of the AGILE 2014 International Conference on Geographic Information Science, Castellon, Spain."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Africani, P., Bitelli, G., Lambertini, A., Minghetti, A., and Paselli, E. (2013, January 21\u201324). Integration of LiDAR data into a municipal GIS to study solar radiation. Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1\/W1, ISPRS Hannover Workshop 2013, Hannover, Germany.","DOI":"10.5194\/isprsarchives-XL-1-W1-1-2013"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1080\/19479832.2013.848475","article-title":"From UNB PanSharp to Fuze Go\u2014The success behind the pan-sharpening algorithm","volume":"5","author":"Zhang","year":"2014","journal-title":"Int. J. Image Data Fusion"},{"key":"ref_44","unstructured":"(2020, February 25). Available online: https:\/\/dg-cms-uploads-production.s3.amazonaws.com\/uploads\/document\/file\/38\/DG_ACCURACY_WP_V3.pdf."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1893","DOI":"10.1080\/0143116031000101611","article-title":"Review article: Geometric processing of remote sensing images: Models, algorithms and methods","volume":"25","author":"Toutin","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_46","unstructured":"(2020, February 25). Available online: https:\/\/sit2.regione.campania.it\/geoportal\/catalog\/search\/resource\/details.page?uuid=r_campan%3A%7BA33AF02A-B85B-46FA-A1EE-A70A29AB1F5D%7D."},{"key":"ref_47","unstructured":"(2020, February 25). Available online: https:\/\/www.qgis.org\/en\/site\/."},{"key":"ref_48","unstructured":"Ekhtari, N., Sahebi, M.R., Valadan Zoej, M.J., and Mohammadzadeh, A. (2008, January 3\u201311). Automatic building detection from LIDAR point cloud data. Proceedings of the 21st ISPRS Congress, Commission, WG IV\/3, Beijing, China."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Han, D. (2013, January 22\u201323). Comparison of Commonly Used Image Interpolation Methods. Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013), Hangzhou, China.","DOI":"10.2991\/iccsee.2013.391"},{"key":"ref_50","unstructured":"(2020, February 25). Available online: https:\/\/docs.ecognition.com\/v9.5.0\/eCognition_documentation\/Modules\/7%20Tutorials\/Tutorial%20Overview.htm."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1002\/esp.3290120107","article-title":"Quantitative analysis of land surface topography","volume":"12","author":"Zevenbergen","year":"1987","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_52","unstructured":"Ciampalini, R., and Carnicelli, S. (2003). Analisi Comparata di Algoritmi Morfometrici in GRASS, Dipartimento di Scienza del Suolo e Nutrizione della Pianta, Universit\u00e0 degli Studi di Firenze."},{"key":"ref_53","unstructured":"Lang, S., and Blaschke, T. (2003, January 17\u201319). Hierarchical object representation\u2014Comparative multi-scale mapping of anthropogenic and natural features. Proceedings of the ISPRS Archives XXXIV (Part 3\/W8), Munich, Germany."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1876","DOI":"10.1080\/01431161.2013.879350","article-title":"Improving detailed rule-based feature extraction of urban areas from WorldView-2 image and lidar data","volume":"35","author":"Hamedianfara","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_55","unstructured":"(2020, February 25). Available online: http:\/\/www.ecognition.com\/."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Franci, F., Lambertinia, A., and Bitella, G. (2014, January 7\u201310). Integration of different geospatic data in urban areas: A casa study. Proceedings of the Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), Pafos, Cyprus.","DOI":"10.1117\/12.2066614"},{"key":"ref_57","first-page":"137","article-title":"A building extraction approach for Airborne Laser Scanner data utilizing the Object Based Image Analysis paradigm","volume":"52","author":"Tomljenovic","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/5\/1285\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:02:11Z","timestamp":1760173331000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/5\/1285"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,27]]},"references-count":57,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2020,3]]}},"alternative-id":["s20051285"],"URL":"https:\/\/doi.org\/10.3390\/s20051285","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,2,27]]}}}