{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T09:36:38Z","timestamp":1777541798248,"version":"3.51.4"},"reference-count":24,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2019,4,5]],"date-time":"2019-04-05T00:00:00Z","timestamp":1554422400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002745","name":"Bayerische Forschungsstiftung","doi-asserted-by":"publisher","award":["AZ-1184-15"],"award-info":[{"award-number":["AZ-1184-15"]}],"id":[{"id":"10.13039\/501100002745","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>This article proposes a method for registration of two different point clouds with different point densities and noise recorded by airborne sensors in rural areas. In particular, multi-sensor point clouds with different point densities are considered. The proposed method is marker-less and uses segmented ground areas for registration.Therefore, the proposed approach offers the possibility to fuse point clouds of different sensors in rural areas within an accuracy of fine registration. In general, such registration is solved with extensive use of control points. The source point cloud is used to calculate a DEM of the ground which is further used to calculate point to raster distances of all points of the target point cloud. Furthermore, each cell of the raster DEM gets a height variance, further addressed as reconstruction accuracy, by calculating the grid. An outlier removal based on a dynamic threshold of distances is used to gain more robustness against noise and small geometry variations. The transformation parameters are calculated with an iterative least-squares optimization of the distances weighted with respect to the reconstruction accuracies of the grid. Evaluations consider two flight campaigns of the Mangfall area inBavaria, Germany, taken with different airborne LiDAR sensors with different point density. The accuracy of the proposed approach is evaluated on the whole flight strip of approximately eight square kilometers as well as on selected scenes in a closer look. For all scenes, it obtained an accuracy of rotation parameters below one tenth degrees and accuracy of translation parameters below the point spacing and chosen cell size of the raster. Furthermore, the possibility of registration of airborne LiDAR and photogrammetric point clouds from UAV taken images is shown with a similar result. The evaluation also shows the robustness of the approach in scenes where a classical iterative closest point (ICP) fails.<\/jats:p>","DOI":"10.3390\/ijgi8040178","type":"journal-article","created":{"date-parts":[[2019,4,5]],"date-time":"2019-04-05T11:36:01Z","timestamp":1554464161000},"page":"178","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Registration of Multi-Sensor Bathymetric Point Clouds in Rural Areas Using Point-to-Grid Distances"],"prefix":"10.3390","volume":"8","author":[{"given":"Richard","family":"Boerner","sequence":"first","affiliation":[{"name":"Photogrammetry and Remote Sensing, Technical University of Munich, 80333 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5571-7808","authenticated-orcid":false,"given":"Yusheng","family":"Xu","sequence":"additional","affiliation":[{"name":"Photogrammetry and Remote Sensing, Technical University of Munich, 80333 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ramona","family":"Baran","sequence":"additional","affiliation":[{"name":"Steinbacher Consult Ingenieurgesellschaft GmbH &amp; Co. KG, Neusaess, 86356 Augsburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frank","family":"Steinbacher","sequence":"additional","affiliation":[{"name":"Steinbacher Consult Ingenieurgesellschaft GmbH &amp; Co. KG, Neusaess, 86356 Augsburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ludwig","family":"Hoegner","sequence":"additional","affiliation":[{"name":"Photogrammetry and Remote Sensing, Technical University of Munich, 80333 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1184-0924","authenticated-orcid":false,"given":"Uwe","family":"Stilla","sequence":"additional","affiliation":[{"name":"Photogrammetry and Remote Sensing, Technical University of Munich, 80333 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Besl, P.J., and McKay, N.D. (1992). Method for registration of 3-D shapes. Robotics-DL Tentative, International Society for Optics and Photonics.","DOI":"10.1117\/12.57955"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"109","DOI":"10.5194\/isprs-archives-XLII-2-109-2018","article-title":"DEM based registration of multi-sensor airborne point clouds exemplary shown on a river side in non urban area","volume":"XLII-2","author":"Boerner","year":"2018","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"51","DOI":"10.5194\/isprs-archives-XLII-1-51-2018","article-title":"Registration of UAV DATA and ALS data using point to DEM distances for bathymetric change detection","volume":"42","author":"Boerner","year":"2018","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_4","first-page":"6","article-title":"A comparative analysis of two approaches for multiple-surface registration of irregular point clouds","volume":"38","author":"Habib","year":"2010","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"135","DOI":"10.14358\/PERS.79.2.135","article-title":"A framework for the registration and segmentation of heterogeneous lidar data","volume":"79","author":"Habib","year":"2013","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_6","unstructured":"B\u00f6hm, J., and Becker, S. (2007, January 9\u201312). Automatic marker-free registration of terrestrial laser scans using reflectance. Proceedings of the 8th Conference on Optical 3D Measurement Techniques, Zurich, Switzerland."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"S62","DOI":"10.1016\/j.isprsjprs.2011.09.010","article-title":"Fast and automatic image-based registration of TLS data","volume":"66","author":"Weinmann","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.isprsjprs.2014.06.015","article-title":"Keypoint-based 4-Points Congruent Sets-Automated marker-less registration of laser scans","volume":"96","author":"Theiler","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.isprsjprs.2014.12.014","article-title":"Automatic registration of unordered point clouds acquired by Kinect sensors using an overlap heuristic","volume":"102","author":"Weber","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"173","DOI":"10.5194\/isprsannals-I-3-173-2012","article-title":"Automatic registration of terrestrial laser scanner point clouds using natural planar surfaces","volume":"3","author":"Theiler","year":"2012","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.isprsjprs.2015.12.005","article-title":"Automatic registration of large-scale urban scene point clouds based on semantic feature points","volume":"113","author":"Yang","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.isprsjprs.2017.06.011","article-title":"Automatic markerless registration of point clouds with semantic-keypoint-based 4-points congruent sets","volume":"130","author":"Ge","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.isprsjprs.2014.05.012","article-title":"Automated registration of dense terrestrial laser-scanning point clouds using curves","volume":"95","author":"Yang","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"699","DOI":"10.14358\/PERS.71.6.699","article-title":"Photogrammetric and LiDAR data registration using linear features","volume":"71","author":"Habib","year":"2005","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_15","unstructured":"Stamos, I., and Leordeanu, M. (2003, January 18\u201320). Automated feature-based range registration of urban scenes of large scale. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Madison, WI, USA."},{"key":"ref_16","first-page":"78","article-title":"Registration of terrestrial laser scanning data using planar patches and image data","volume":"36","author":"Dold","year":"2006","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_17","first-page":"105","article-title":"Robust automatic marker-free registration of terrestrial scan data","volume":"36","year":"2006","journal-title":"Proc. Photogramm. Comput. Vis."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Xiao, J., Adler, B., and Zhang, H. (2012, January 13\u201315). 3D point cloud registration based on planar surfaces. Proceedings of the 2012 IEEE Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), Hamburg, Germany.","DOI":"10.1109\/MFI.2012.6343035"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.isprsjprs.2013.09.005","article-title":"Change detection in urban areas by object-based analysis and on-the-fly comparison of multi-view ALS data","volume":"86","author":"Hebel","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"97","DOI":"10.5194\/isprs-annals-III-5-97-2016","article-title":"Coarse point cloud registration by egi matching of voxel clusters","volume":"III","author":"Wang","year":"2016","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"185","DOI":"10.5194\/isprs-annals-IV-2-W4-185-2017","article-title":"Automated coarse registration of point clouds in 3d urban scenes using voxel based plane constraint","volume":"IV-2\/W4","author":"Xu","year":"2017","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"107","DOI":"10.5194\/isprs-archives-XLII-1-W1-107-2017","article-title":"Voxel based segmentation of large airborne topobathymetric lidar data","volume":"XLII-1\/W1","author":"Boerner","year":"2017","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.patrec.2017.12.016","article-title":"Voxel-based segmentation of 3D point clouds from construction sites using a probabilistic connectivity model","volume":"102","author":"Xu","year":"2018","journal-title":"Pattern Recognit. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.autcon.2018.09.018","article-title":"Spatial compactness metrics and Constrained Voxel Automata development for analyzing 3D densification and applying to point clouds: A synthetic review","volume":"96","author":"Shirowzhan","year":"2018","journal-title":"Autom. Constr."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/8\/4\/178\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:43:13Z","timestamp":1760186593000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/8\/4\/178"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,5]]},"references-count":24,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2019,4]]}},"alternative-id":["ijgi8040178"],"URL":"https:\/\/doi.org\/10.3390\/ijgi8040178","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,5]]}}}