{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:45:35Z","timestamp":1760237135727,"version":"build-2065373602"},"reference-count":49,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,3,11]],"date-time":"2020-03-11T00:00:00Z","timestamp":1583884800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41890854; 41372330; 41671436"],"award-info":[{"award-number":["41890854; 41372330; 41671436"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Trajectory data are often used as important auxiliary information in preprocessing and extracting the target from mobile laser scanning data. However, the trajectory data stored independently may be lost and destroyed for various reasons, making the data unavailable for the relevant models. This study proposes recovering the trajectory of the scanner from point cloud data following the scanning principles of a rotating mirror. Two approaches are proposed from different input conditions: Ordered three-dimensional coordinates of point cloud data, with and without acquisition time. We recovered the scanner\u2019s ground track through road point density analysis and restored the position of the center of emission of the laser based on plane reconstruction on a single scanning line. The validity and reliability of the proposed approaches were verified in the four typical urban, rural, winding, and viaduct road environments using two systems from different manufacturers. The result deviations of the ground track and scanner trajectory from their actual position were a few centimeters and less than 1 decimeter, respectively. Such an error is sufficiently small for the trajectory data to be used in the relevant algorithms.<\/jats:p>","DOI":"10.3390\/rs12060899","type":"journal-article","created":{"date-parts":[[2020,3,12]],"date-time":"2020-03-12T04:13:57Z","timestamp":1583986437000},"page":"899","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Recovering Missing Trajectory Data for Mobile Laser Scanning Systems"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5151-8892","authenticated-orcid":false,"given":"Mianqing","family":"Zhong","sequence":"first","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information Engineering, Chang\u2019an University, Xi\u2019an 710054, China"}]},{"given":"Lichun","family":"Sui","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information Engineering, Chang\u2019an University, Xi\u2019an 710054, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6776-2910","authenticated-orcid":false,"given":"Zhihua","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1643-8480","authenticated-orcid":false,"given":"Xiaomei","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China"}]},{"given":"Chuanshuai","family":"Zhang","sequence":"additional","affiliation":[{"name":"The First Topographic Surveying Brigade of Ministry of Natural Resource of P.R.C., Xi\u2019an 710054, China"}]},{"given":"Nan","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information Engineering, Chang\u2019an University, Xi\u2019an 710054, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7799","DOI":"10.1109\/TGRS.2019.2916625","article-title":"A Novel Octree-Based 3-D Fully Convolutional Neural Network for Point Cloud Classification in Road Environment","volume":"57","author":"Xiang","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1080\/15481603.2013.866815","article-title":"Detecting road poles from mobile terrestrial laser scanning data","volume":"50","author":"Lichti","year":"2013","journal-title":"GIScience Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.isprsjprs.2019.08.010","article-title":"Recovery of urban 3D road boundary via multi-source data","volume":"156","author":"Wen","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1904","DOI":"10.1109\/LGRS.2019.2910546","article-title":"3-D Deep Feature Construction for Mobile Laser Scanning Point Cloud Registration","volume":"16","author":"Zhang","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"864","DOI":"10.1080\/15481603.2019.1581475","article-title":"A literature synthesis of LiDAR applications in transportation: Feature extraction and geometric assessments of highways","volume":"56","author":"Gargoum","year":"2019","journal-title":"GIScience Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/j.isprsjprs.2017.06.007","article-title":"3D local feature BKD to extract road information from mobile laser scanning point clouds","volume":"130","author":"Yang","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.isprsjprs.2017.02.014","article-title":"Computing multiple aggregation levels and contextual features for road facilities recognition using mobile laser scanning data","volume":"126","author":"Yang","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1080\/2150704X.2015.1117156","article-title":"Automated extraction of ground surface along urban roads from mobile laser scanning point clouds","volume":"7","author":"Wu","year":"2016","journal-title":"Remote Sens. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1016\/j.ufug.2013.06.002","article-title":"Tree mapping using airborne, terrestrial and mobile laser scanning\u2014A case study in a heterogeneous urban forest","volume":"12","author":"Holopainen","year":"2013","journal-title":"Urban For. Urban Green."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"5839","DOI":"10.1080\/01431161.2012.674229","article-title":"Automated extraction of street-scene objects from mobile lidar point clouds","volume":"33","author":"Yang","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ma, L., Li, Y., Li, J., Wang, C., Wang, R., and Chapman, M. (2018). Mobile Laser Scanned Point-Clouds for Road Object Detection and Extraction: A Review. Remote Sens., 10.","DOI":"10.3390\/rs10101531"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4655","DOI":"10.1080\/01431161.2017.1320451","article-title":"Extraction of road surface from mobile LiDAR data of complex road environment","volume":"38","author":"Yadav","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2085","DOI":"10.1109\/LGRS.2015.2449074","article-title":"Road Boundaries Detection Based on Local Normal Saliency From Mobile Laser Scanning Data","volume":"12","author":"Hanyun","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"S28","DOI":"10.1016\/j.isprsjprs.2011.08.006","article-title":"Recognizing basic structures from mobile laser scanning data for road inventory studies","volume":"66","author":"Pu","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Zai, D., Guo, Y., Li, J., Luo, H., and Cheng, W. (2016, January 10\u201315). 3D Road Surface Extraction From Mobile Laser Scanning Point Clouds. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China.","DOI":"10.1109\/IGARSS.2016.7729407"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"802","DOI":"10.1109\/TITS.2017.2701403","article-title":"3-D Road Boundary Extraction From Mobile Laser Scanning Data via Supervoxels and Graph Cuts","volume":"19","author":"Zai","year":"2018","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"4805","DOI":"10.1109\/JSTARS.2015.2467160","article-title":"Pole-Like Road Object Detection from Mobile Lidar System Using a Coarse-to-Fine Approach","volume":"8","author":"Teo","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Balado, J., Martinez-Sanchez, J., Arias, P., and Novo, A. (2019). Road Environment Semantic Segmentation with Deep Learning from MLS Point Cloud Data. Sensors, 19.","DOI":"10.3390\/s19163466"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"287","DOI":"10.5194\/isprs-annals-IV-2-W4-287-2017","article-title":"Point clouds to indoor\/outdoor accessibility diagnosis","volume":"IV-2\/W4","author":"Balado","year":"2017","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.isprsjprs.2013.01.016","article-title":"Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds","volume":"79","author":"Yang","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2018.11.012","article-title":"Efficient and robust lane marking extraction from mobile lidar point clouds","volume":"147","author":"Jung","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.autcon.2014.12.009","article-title":"An approach to detect and delineate street curbs from MLS 3D point cloud data","volume":"51","author":"Alonso","year":"2015","journal-title":"Autom. Constr."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"584","DOI":"10.3390\/rs5020584","article-title":"A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data","volume":"5","author":"Wu","year":"2013","journal-title":"Remote Sens."},{"key":"ref_24","unstructured":"McElhinney, C.P., Kumar, P., Cahalane, C., and McCarthy, T. (2010). Initial results from European road safety inspection (eursi) mobile mapping project. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, International Society of Photogrammetry and Remote Sensing (ISPRS). Available online: http:\/\/mural.maynoothuniversity.ie\/9271\/."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.isprsjprs.2014.06.017","article-title":"An automated approach to vertical road characterisation using mobile LiDAR systems: Longitudinal profiles and cross-sections","volume":"96","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.isprsjprs.2013.11.005","article-title":"Using mobile laser scanning data for automated extraction of road markings","volume":"87","author":"Guan","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2457","DOI":"10.1109\/TITS.2015.2409192","article-title":"Using Mobile LiDAR Data for Rapidly Updating Road Markings","volume":"16","author":"Guan","year":"2015","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1042","DOI":"10.1080\/2150704X.2014.994716","article-title":"Automated extraction of manhole covers using mobile LiDAR data","volume":"5","author":"Guan","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1109\/JSTARS.2014.2347276","article-title":"Learning Hierarchical Features for Automated Extraction of Road Markings From 3-D Mobile LiDAR Point Clouds","volume":"8","author":"Yu","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.tust.2016.06.010","article-title":"A semi-automated method for extracting vertical clearance and cross sections in tunnels using mobile LiDAR data","volume":"59","author":"Puente","year":"2016","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Gargoum, S., and El-Basyouny, K. (2017, January 8\u201310). Automated Extractaion of Road Features Using LiDAR Data: A Review of LiDAR Applications in Transportation. Proceedings of the 2017 4th International Conference on Transportation Information and Safety (ICTIS), Banff, AB, Canada.","DOI":"10.1109\/ICTIS.2017.8047822"},{"key":"ref_32","unstructured":"Xin, C., Kohlmeyer, B., Stroila, M., Alwar, N., and Bach, J. (2009, January 4\u20136). Next generation map making: Geo-referenced ground-level LIDAR point clouds for automatic retro-reflective road feature extraction. Proceedings of the 17th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems, ACM-GIS 2009, Seattle, WA, USA."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"29623","DOI":"10.1109\/ACCESS.2019.2902170","article-title":"A 3D LiDAR Data-Based Dedicated Road Boundary Detection Algorithm for Autonomous Vehicles","volume":"7","author":"Sun","year":"2019","journal-title":"IEEE Access"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.isprsjprs.2016.01.019","article-title":"Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory","volume":"114","author":"Riveiro","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.autcon.2015.07.017","article-title":"Automatic reconstruction of road surface features by using terrestrial mobile lidar","volume":"58","author":"Guo","year":"2015","journal-title":"Autom. Constr."},{"key":"ref_36","unstructured":"Wang, H., Cai, Z., Luo, H., Cheng, W., and Li, J. (2012, January 16\u201318). Automatic road extraction from mobile laser scanning data. Proceedings of the International Conference on Computer Vision in Remote Sensing, Xiamen, China."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Yan, L., Liu, H., Tan, J., Li, Z., Xie, H., and Chen, C. (2016). Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds. Sensors, 16.","DOI":"10.3390\/s16060903"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.isprsjprs.2013.08.003","article-title":"An automated algorithm for extracting road edges from terrestrial mobile LiDAR data","volume":"85","author":"Kumar","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Hervieu, A., and Soheilian, B. (2013, January 23\u201326). Road side detection and reconstruction using LIDAR sensor. Proceedings of the 2013 IEEE Intelligent Vehicles Symposium (IV), Gold Coast, Australia.","DOI":"10.1109\/IVS.2013.6629637"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.3390\/s130101102","article-title":"A new curb detection method for unmanned ground vehicles using 2D sequential laser data","volume":"13","author":"Liu","year":"2013","journal-title":"Sensors"},{"key":"ref_41","first-page":"125","article-title":"Automated road markings extraction from mobile laser scanning data","volume":"32","author":"Kumar","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"5238","DOI":"10.3390\/s8095238","article-title":"Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping","volume":"8","author":"Jaakkola","year":"2008","journal-title":"Sensors"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.autcon.2018.08.015","article-title":"Automated assessment of vertical clearance on highways scanned using mobile LiDAR technology","volume":"95","author":"Gargoum","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"G\u00e9zero, L., and Antunes, C. (2019). Automated Road Curb Break Lines Extraction from Mobile LiDAR Point Clouds. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8110476"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"193","DOI":"10.5194\/isprsarchives-XXXIX-B5-193-2012","article-title":"Curb-based street floor extraction from mobile terrestrial lidar point cloud","volume":"39","author":"Ibrahim","year":"2012","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2167","DOI":"10.1109\/TITS.2015.2399492","article-title":"Automated Extraction of Urban Road Facilities Using Mobile Laser Scanning Data","volume":"16","author":"Yu","year":"2015","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_47","first-page":"717","article-title":"Rapid inspection of pavement markings using mobile lidar point clouds","volume":"XLI-B1","author":"Zhang","year":"2016","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"025105","DOI":"10.1088\/1361-6501\/ab455a","article-title":"A single-shot pose estimation approach for a 2D laser rangefinder","volume":"31","author":"Li","year":"2019","journal-title":"Meas. Sci. Technol."},{"key":"ref_49","unstructured":"Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., and Stuetzle, W. (, January July). Surface reconstruction from unorganized points. Proceedings of the 19th Annual Conference on Computer Graphics and Interactive Techniques, Association for Computing Machinery, New York, NY, USA. Available online: https:\/\/dl.acm.org\/doi\/abs\/10.1145\/133994.134011."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/6\/899\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:06:11Z","timestamp":1760173571000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/6\/899"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,11]]},"references-count":49,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2020,3]]}},"alternative-id":["rs12060899"],"URL":"https:\/\/doi.org\/10.3390\/rs12060899","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2020,3,11]]}}}