{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:25:21Z","timestamp":1760149521344,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2023,8,13]],"date-time":"2023-08-13T00:00:00Z","timestamp":1691884800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42161060","41801325","20192BAB217010","20202BABL202045","2019M661858"],"award-info":[{"award-number":["42161060","41801325","20192BAB217010","20202BABL202045","2019M661858"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42161060","41801325","20192BAB217010","20202BABL202045","2019M661858"],"award-info":[{"award-number":["42161060","41801325","20192BAB217010","20202BABL202045","2019M661858"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004479","name":"Natural Science Foundation of Jiangxi Province","doi-asserted-by":"publisher","award":["42161060","41801325","20192BAB217010","20202BABL202045","2019M661858"],"award-info":[{"award-number":["42161060","41801325","20192BAB217010","20202BABL202045","2019M661858"]}],"id":[{"id":"10.13039\/501100004479","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004479","name":"Natural Science Foundation of Jiangxi Province","doi-asserted-by":"publisher","award":["42161060","41801325","20192BAB217010","20202BABL202045","2019M661858"],"award-info":[{"award-number":["42161060","41801325","20192BAB217010","20202BABL202045","2019M661858"]}],"id":[{"id":"10.13039\/501100004479","id-type":"DOI","asserted-by":"publisher"}]},{"name":"China Post-Doctoral Science Foundation","award":["42161060","41801325","20192BAB217010","20202BABL202045","2019M661858"],"award-info":[{"award-number":["42161060","41801325","20192BAB217010","20202BABL202045","2019M661858"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Filtering from airborne LiDAR datasets in urban area is one important process during the building of digital and smart cities. However, the existing filters encounter poor filtering performance and heavy computational burden when processing large-scale and complicated urban environments. To tackle this issue, a self-adaptive filtering method based on object primitive global energy minimization is proposed in this paper. In this paper, mode points were first acquired for generating the mode graph. The mode points were the cluster centers of the LiDAR data obtained in a mean shift algorithm. The graph constructed with mode points was named \u201cmode graph\u201d in this paper. By defining the energy function based on the mode graph, the filtering process is transformed to iterative global energy minimization. In each iteration, the graph cuts technique was adopted to achieve global energy minimization. Meanwhile, the probability of each point belonging to the ground was updated, which would lead to a new refined ground surface using the points whose probabilities were greater than 0.5. This process was iterated until two successive fitted ground surfaces were determined to be close enough. Four urban samples with different urban environments were adopted for verifying the effectiveness of the filter developed in this paper. Experimental results indicate that the developed filter obtained the best filtering performance. Both the total error and the Kappa coefficient are superior to those of the other three classical filtering methods.<\/jats:p>","DOI":"10.3390\/rs15164013","type":"journal-article","created":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T10:40:31Z","timestamp":1692009631000},"page":"4013","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Self-Adaptive Filtering for Ultra-Large-Scale Airborne LiDAR Data in Urban Environments Based on Object Primitive Global Energy Minimization"],"prefix":"10.3390","volume":"15","author":[{"given":"Zhenyang","family":"Hui","sequence":"first","affiliation":[{"name":"Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China"},{"name":"School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China"}]},{"given":"Zhuoxuan","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China"},{"name":"School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China"}]},{"given":"Dajun","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China"},{"name":"School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China"}]},{"given":"Yanan","family":"Xu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China"},{"name":"School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4122-066X","authenticated-orcid":false,"given":"Yuqian","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China"},{"name":"School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Jia, J., Sun, H., Jiang, C., Karila, K., Karjalainen, M., Ahokas, E., Khoramshahi, E., Hu, P., Chen, C., and Xue, T. 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