{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T04:49:40Z","timestamp":1774673380344,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,5,7]],"date-time":"2022-05-07T00:00:00Z","timestamp":1651881600000},"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":["41671440"],"award-info":[{"award-number":["41671440"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["121134000000180009"],"award-info":[{"award-number":["121134000000180009"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2018YFF0215302"],"award-info":[{"award-number":["2018YFF0215302"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004428","name":"the program of Ministry of Natural Resources of China","doi-asserted-by":"publisher","award":["41671440"],"award-info":[{"award-number":["41671440"]}],"id":[{"id":"10.13039\/501100004428","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004428","name":"the program of Ministry of Natural Resources of China","doi-asserted-by":"publisher","award":["121134000000180009"],"award-info":[{"award-number":["121134000000180009"]}],"id":[{"id":"10.13039\/501100004428","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004428","name":"the program of Ministry of Natural Resources of China","doi-asserted-by":"publisher","award":["2018YFF0215302"],"award-info":[{"award-number":["2018YFF0215302"]}],"id":[{"id":"10.13039\/501100004428","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the National Key Research Development Program of China","award":["41671440"],"award-info":[{"award-number":["41671440"]}]},{"name":"the National Key Research Development Program of China","award":["121134000000180009"],"award-info":[{"award-number":["121134000000180009"]}]},{"name":"the National Key Research Development Program of China","award":["2018YFF0215302"],"award-info":[{"award-number":["2018YFF0215302"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Pavement subsidence detection based on point cloud data acquired by mobile measurement systems is very challenging. First, the uncertainty and disorderly nature of object points data results in difficulties in point cloud comparison. Second, acquiring data with kinematic laser scanners introduces errors into systems during data acquisition, resulting in a reduction in data accuracy. Third, the high-precision measurement standard of pavement subsidence raises requirements for data processing. In this article, a data processing method is proposed to detect the subcentimeter-level subsidence of urban pavements using point cloud data comparisons in multiple time phases. The method mainly includes the following steps: First, the original data preprocessing is conducted, which includes point cloud matching and pavement point segmentation. Second, the interpolation of the pavement points into a regular grid is performed to solve the problem of point cloud comparison. Third, according to the high density of the pavement points and the performance of the pavement in the rough point cloud, using a Gaussian kernel convolution to smooth the pavement point cloud data, we aim to reduce the error in comparison. Finally, we determine the subsidence area by calculating the height difference and compare it with the threshold value. The experimental results show that the smoothing process can substantially improve the accuracy of the point cloud comparison results, effectively reducing the false detection rate and showing that subcentimeter-level pavement subsidence can be effectively detected.<\/jats:p>","DOI":"10.3390\/rs14092240","type":"journal-article","created":{"date-parts":[[2022,5,8]],"date-time":"2022-05-08T23:27:25Z","timestamp":1652052445000},"page":"2240","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Subsidence Detection for Urban Roads Using Mobile Laser Scanner Data"],"prefix":"10.3390","volume":"14","author":[{"given":"Hongxia","family":"Song","sequence":"first","affiliation":[{"name":"School of Resources and Environmental Sciences, Wuhan University, Wuhan 430079, China"},{"name":"National Quality Inspection and Testing Center for Surveying and Mapping Products, Beijing 100830, China"}]},{"given":"Jixian","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Resources and Environmental Sciences, Wuhan University, Wuhan 430079, China"},{"name":"National Quality Inspection and Testing Center for Surveying and Mapping Products, Beijing 100830, China"}]},{"given":"Jianzhang","family":"Zuo","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100036, China"}]},{"given":"Xinlian","family":"Liang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"given":"Wenli","family":"Han","sequence":"additional","affiliation":[{"name":"National Quality Inspection and Testing Center for Surveying and Mapping Products, Beijing 100830, China"}]},{"given":"Juan","family":"Ge","sequence":"additional","affiliation":[{"name":"National Quality Inspection and Testing Center for Surveying and Mapping Products, Beijing 100830, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1002\/2017JF004594","article-title":"InSAR Measurements and Viscoelastic Modeling of Sinkhole Precursory Subsidence: Implications for Sinkhole Formation, Early Warning, and Sediment Properties","volume":"123","author":"Baer","year":"2018","journal-title":"J. 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