{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,16]],"date-time":"2025-12-16T12:29:17Z","timestamp":1765888157379,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2019,5,17]],"date-time":"2019-05-17T00:00:00Z","timestamp":1558051200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2016YFB0502203"],"award-info":[{"award-number":["2016YFB0502203"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41701519"],"award-info":[{"award-number":["41701519"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2017A030310544"],"award-info":[{"award-number":["2017A030310544"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Research Fund Program of State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing","award":["16I02"],"award-info":[{"award-number":["16I02"]}]},{"name":"Shenzhen Future Industry Development Funding Program","award":["201507211219247860"],"award-info":[{"award-number":["201507211219247860"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Automatic ground filtering is an essential step for Digital Elevation Model (DEM) generation, which has significant application value. However, extraction and classification of ground points from the Light Detection and Ranging (LiDAR) data, especially in multitudinous terrain situations, is a challenging task because it is difficult to determine the set of optimal parameters for removing various non-ground features. In this paper, a new ground filtering technique based on an improved Ball Pivot Algorithm (BPA) is proposed. At the beginning, the LiDAR point cloud dataset was divided into different subsets based on the 2D regular grid. The lowest point in each grid was selected as the seed point to build a single-layer surface. After that, the improved BPA was executed to remove points on the higher location. Then, the rest of the points were calculated and selected as a new seed point according to the spatial relationship with the initial surface. Finally, non-ground points were filtered by means of improved BPA traversing all the grids. Our experimental results on the Benchmark dataset provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) Working Group III\/3 showed high accuracy (with a mean kappa coefficient over 80%) in terms of completeness, correctness, and quality for DEM generation. The experimental results demonstrated the proposed method is robust to various terrain situations, as it is more effective and feasible for ground filtering.<\/jats:p>","DOI":"10.3390\/rs11101179","type":"journal-article","created":{"date-parts":[[2019,5,17]],"date-time":"2019-05-17T11:06:46Z","timestamp":1558091206000},"page":"1179","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["An Improved Ball Pivot Algorithm-Based Ground Filtering Mechanism for LiDAR Data"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4077-5372","authenticated-orcid":false,"given":"Wei","family":"Ma","sequence":"first","affiliation":[{"name":"College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China"},{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China"},{"name":"Key Laboratory for Geo-Environment Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen 518060, China"}]},{"given":"Qingquan","family":"Li","sequence":"additional","affiliation":[{"name":"College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China"},{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China"},{"name":"Key Laboratory for Geo-Environment Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen 518060, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.measurement.2017.03.007","article-title":"A revised progressive TIN densification for filtering airborne LiDAR data","volume":"104","author":"Sheng","year":"2017","journal-title":"Measurement"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.isprsjprs.2013.04.001","article-title":"Filtering airborne LiDAR data by embedding smoothness-constrained segmentation in progressive TIN densification","volume":"81","author":"Zhang","year":"2013","journal-title":"ISPRS J. 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