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However, due to the influence of the atmospheric environment, water quality and color, the system itself and other factors, the photon point cloud introduces survey noise, which restricts the survey accuracy and reliability of nearshore water depth. Therefore, in this study, we presented a photon denoising algorithm for layered processing of submarine surface. Firstly, rough denoising of the original photon data was completed by smoothing filtering. Then, elevation histogram statistics were carried out on the photon data, two peaks of the histogram were fitted by a double Gaussian function, and the intersection of two curves was then taken to separate the water surface and underwater photons. The surface photons were denoised by the DBSCAN clustering algorithm. Then according to the distribution characteristics of underwater signal photons, a single-photon point cloud filtering bathymetric method was proposed based on improved local distance statistics (LDSBM), which was used for fine denoising of underwater point cloud data. Finally, the Gaussian function was used to fit the frequency histogram, and the signal photons were screened to extract the water depth information. In this study, 13 groups of the ATL03 dataset from the Xisha Islands, the St. Thomas and the Acklins Island were used for denoising. The denoising results were compared with the signal photons manually marked and the signal photons extracted by the official built-in method (OM). The experimental results showed that, compared with the official method results of ATL03, the LDSBM had a higher F value (comprehensive evaluation index), with an average of more than 96.70%. In conclusion, the proposed underwater single-photon point cloud filtering bathymetric method was superior to the traditional algorithm and could recover terrain information accurately.<\/jats:p>","DOI":"10.3390\/rs15112828","type":"journal-article","created":{"date-parts":[[2023,5,30]],"date-time":"2023-05-30T02:04:21Z","timestamp":1685412261000},"page":"2828","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Denoising and Accuracy Evaluation of ICESat-2\/ATLAS Photon Data for Nearshore Waters Based on Improved Local Distance Statistics"],"prefix":"10.3390","volume":"15","author":[{"given":"Junfeng","family":"Xie","sequence":"first","affiliation":[{"name":"School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China"},{"name":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, China"}]},{"given":"Jincheng","family":"Zhong","sequence":"additional","affiliation":[{"name":"School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China"},{"name":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, China"}]},{"given":"Fan","family":"Mo","sequence":"additional","affiliation":[{"name":"School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China"},{"name":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3759-6613","authenticated-orcid":false,"given":"Ren","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China"}]},{"given":"Xiang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}]},{"given":"Xiaomeng","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}]},{"given":"Junze","family":"Zeng","sequence":"additional","affiliation":[{"name":"School of Smart City, Chongqing Jiaotong University, Chongqing 400074, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,29]]},"reference":[{"key":"ref_1","first-page":"1271","article-title":"Remote sensing of clear-water, shallow, gravel-bed rivers using digital photogrammetry","volume":"67","author":"Westaway","year":"2001","journal-title":"Photogramm. 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