{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T21:01:34Z","timestamp":1774126894775,"version":"3.50.1"},"reference-count":29,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,12,25]],"date-time":"2023-12-25T00:00:00Z","timestamp":1703462400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China Projects","award":["41876105"],"award-info":[{"award-number":["41876105"]}]},{"name":"National Natural Science Foundation of China Projects","award":["41371436"],"award-info":[{"award-number":["41371436"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The refraction phenomenon causes ICESat-2 nearshore bathymetry errors by deviating seafloor photons\u2019 coordinates. A refraction correction method based on ATL03 photon parameter tracking was proposed to improve the ICESat-2 bathymetry accuracy. The method begins by searching for sea\u2013air intersections using photon parameters. Instead of relying on mathematical operations, it uses logical relations to establish a relationship between the seafloor and the surface, which improves efficiency. Then, a refraction correction model is designed based on Snell\u2019s law for different sea surface fluctuations. This model is clear and suitable for scholars new to refraction correction. The results show the effectiveness of the proposed method since the RMSE is reduced by 1.8842 m~5.2319 m compared with the raw data. Our method has better tolerance than other methods at different water depth ranges.<\/jats:p>","DOI":"10.3390\/rs16010084","type":"journal-article","created":{"date-parts":[[2023,12,25]],"date-time":"2023-12-25T23:00:12Z","timestamp":1703545212000},"page":"84","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Refraction Correction Based on ATL03 Photon Parameter Tracking for Improving ICESat-2 Bathymetry Accuracy"],"prefix":"10.3390","volume":"16","author":[{"given":"Li","family":"Chen","sequence":"first","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}]},{"given":"Shuai","family":"Xing","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1112-1963","authenticated-orcid":false,"given":"Guoping","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"},{"name":"Key Laboratory of Spatiotemporal Perception and Intelligent Processing, Ministry of Natural Resources, Zhengzhou 450001, China"},{"name":"Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains, Zhengzhou 450001, China"}]},{"given":"Songtao","family":"Guo","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}]},{"given":"Ming","family":"Gao","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.isprsjprs.2019.09.011","article-title":"Coral reef geomorphology of the Spratly Islands: A simple method based on time-series of Landsat-8 multi-band inundation maps","volume":"157","author":"Dong","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"135316","DOI":"10.1016\/j.scitotenv.2019.135316","article-title":"Relative impacts of multiple human stressors in estuaries and coastal waters in the North Sea-Baltic Sea transition zone","volume":"704","author":"Andersen","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2449","DOI":"10.1109\/JSTARS.2022.3153681","article-title":"Nearshore Bathymetry Based on ICESat-2 and Multispectral Images: Comparison Between Sentinel-2, Landsat-8, and Testing Gaofen-2","volume":"15","author":"Zhang","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"59","DOI":"10.15302\/J-SSCAE-2019.06.010","article-title":"Remote Sensing Application in China\u2019s Coastal Zones and Islands: Recent Progress and Some Suggestions","volume":"21","author":"Wang","year":"2019","journal-title":"Strateg. Study CAE"},{"key":"ref_5","first-page":"191","article-title":"Assessment of depth and turbidity with airborne Lidar bathymetry and multiband satellite imagery in shallow water bodies of the Alaskan North Slope","volume":"58","author":"Saylam","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"7883","DOI":"10.1109\/TGRS.2019.2917012","article-title":"Deriving High-Resolution Reservoir Bathymetry from ICESat-2 Prototype Photon-Counting Lidar and Landsat Imagery","volume":"57","author":"Li","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2019.02.002","article-title":"Design and evaluation of a full-wave surface and bottom-detection algorithm for LiDAR bathymetry of very shallow waters","volume":"150","author":"Schwarz","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.rse.2016.12.029","article-title":"The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): Science requirements, concept, and implementation","volume":"190","author":"Markus","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"103936","DOI":"10.1016\/j.coastaleng.2021.103936","article-title":"On the use of Sentinel-2 satellites and lidar surveys for the change detection of shallow bathymetry: The case study of North Carolina inlets","volume":"169","author":"Caballero","year":"2021","journal-title":"Coast. Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"e2020GL090629","DOI":"10.1029\/2020GL090629","article-title":"ICESat-2 Elevation Retrievals in Support of Satellite-Derived Bathymetry for Global Science Applications","volume":"48","author":"Babbel","year":"2021","journal-title":"Geophys. Res. Lett."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2021.05.012","article-title":"A semi-empirical scheme for bathymetric mapping in shallow water by ICESat-2 and Sentinel-2: A case study in the South China Sea","volume":"178","author":"Hsu","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"13107","DOI":"10.1029\/2019GL085032","article-title":"Tibetan Plateau\u2019s lake level and volume changes from NASA\u2019s ICESat\/ICESat-2 and Landsat Missions","volume":"46","author":"Zhang","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1109\/JPROC.2009.2034765","article-title":"The ICESat-2 Laser Altimetry Mission","volume":"98","author":"Abdalati","year":"2010","journal-title":"Proc. IEEE"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1109\/LGRS.2020.2987778","article-title":"Nearshore Bathymetry from Fusion of Sentinel-2 and ICESat-2 Observations","volume":"18","author":"Albright","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Parrish, C.E., Magruder, L.A., Neuenschwander, A.L., Forfinski-Sarkozi, N., Alonzo, M., and Jasinski, M. (2019). Validation of ICESat-2 ATLAS Bathymetry and Analysis of ATLAS\u2019s Bathymetric Mapping Performance. Remote Sens., 11.","DOI":"10.3390\/rs11141634"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4708109","DOI":"10.1109\/TGRS.2022.3192825","article-title":"A Purely Spaceborne Open Source Approach for Regional Bathymetry Mapping","volume":"60","author":"Thomas","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","first-page":"103207","article-title":"A noise removal algorithm based on adaptive elevation difference thresholding for ICESat-2 photon-counting data","volume":"117","author":"Wang","year":"2023","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"6141","DOI":"10.1109\/TGRS.2017.2721442","article-title":"Refraction Correction of Airborne LiDAR Bathymetry Based on Sea Surface Profile and Ray Tracing","volume":"55","author":"Yang","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Xu, N., Ma, Y., Zhang, W., Wang, X.H., Yang, F., and Su, D. (2020). Monitoring Annual Changes of Lake Water Levels and Volumes over 1984-2018 Using Landsat Imagery and ICESat-2 Data. Remote Sens., 12.","DOI":"10.3390\/rs12234004"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"112047","DOI":"10.1016\/j.rse.2020.112047","article-title":"Satellite-derived bathymetry using the ICESat-2 lidar and Sentinel-2 imagery datasets","volume":"250","author":"Ma","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"111287","DOI":"10.1016\/j.rse.2019.111287","article-title":"Estimating water levels and volumes of lakes dated back to the 1980s using Landsat imagery and photon-counting lidar datasets","volume":"232","author":"Ma","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Liu, C., Qi, J., Li, J., Tang, Q., Xu, W., Zhou, X., and Meng, W. (2021). Accurate Refraction Correction-Assisted Bathymetric Inversion Using ICESat-2 and Multispectral Data. Remote Sens., 13.","DOI":"10.3390\/rs13214355"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.isprsjprs.2022.02.020","article-title":"Refraction and coordinate correction with the JONSWAP model for ICESat-2 bathymetry","volume":"186","author":"Zhang","year":"2022","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2411","DOI":"10.1364\/OE.409941","article-title":"Refraction correction and coordinate displacement compensation in nearshore bathymetry using ICESat-2 lidar data and remote-sensing images","volume":"29","author":"Chen","year":"2021","journal-title":"Opt. Express"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2783","DOI":"10.1080\/01431161.2020.1862441","article-title":"An active-passive fusion strategy and accuracy evaluation for shallow water bathymetry based on ICESat-2 ATLAS laser point cloud and satellite remote sensing imagery","volume":"42","author":"Cao","year":"2021","journal-title":"Int. J. Remote Sens."},{"key":"ref_26","first-page":"1500305","article-title":"A Method to Derive Bathymetry for Dynamic Water Bodies Using ICESat-2 and GSWD Data Sets","volume":"19","author":"Xu","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"112756","DOI":"10.1016\/j.oceaneng.2022.112756","article-title":"A global evaluation of the JONSWAP spectra suitability on coastal areas","volume":"266","author":"Menendez","year":"2022","journal-title":"Ocean. Eng."},{"key":"ref_28","first-page":"6501905","article-title":"A Noise-Removal Algorithm Without Input Parameters Based on Quadtree Isolation for Photon-Counting LiDAR","volume":"19","author":"Zhang","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"113244","DOI":"10.1016\/j.rse.2022.113244","article-title":"Consistency analysis of forest height retrievals between GEDI and ICESat-2","volume":"281","author":"Zhu","year":"2022","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/1\/84\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:41:39Z","timestamp":1760132499000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/1\/84"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,25]]},"references-count":29,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["rs16010084"],"URL":"https:\/\/doi.org\/10.3390\/rs16010084","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,25]]}}}