{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:49:53Z","timestamp":1760143793749,"version":"build-2065373602"},"reference-count":12,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,2,29]],"date-time":"2024-02-29T00:00:00Z","timestamp":1709164800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006769","name":"Russian Science Foundation","doi-asserted-by":"publisher","award":["23-77-10064"],"award-info":[{"award-number":["23-77-10064"]}],"id":[{"id":"10.13039\/501100006769","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The method for sea ice detection using the data from the Dual-frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM) satellite data is suggested. The approach is based on the analysis of the shape of normalized radar cross-section dependence on the incidence angle. The coefficient of kurtosis of surface slopes probability density function is introduced as a parameter to distinguish between open water and ice cover. The approach was validated using the data on sea ice concentration from the AMSR-2 radiometer in the Antarctic region.<\/jats:p>","DOI":"10.3390\/rs16050859","type":"journal-article","created":{"date-parts":[[2024,2,29]],"date-time":"2024-02-29T08:13:44Z","timestamp":1709194424000},"page":"859","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Sea Ice Detection Method Using the Dependence of the Radar Cross-Section on the Incidence Angle"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3795-0347","authenticated-orcid":false,"given":"Maria","family":"Panfilova","sequence":"first","affiliation":[{"name":"Institute of Applied Physics, Russian Academy of Sciences, 603950 Nizhny Novgorod, Russia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4054-4905","authenticated-orcid":false,"given":"Vladimir","family":"Karaev","sequence":"additional","affiliation":[{"name":"Institute of Applied Physics, Russian Academy of Sciences, 603950 Nizhny Novgorod, Russia"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"838","DOI":"10.1364\/JOSA.44.000838","article-title":"Measurement of the roughness of the sea surface from photographs of the sun\u2019s glitter","volume":"44","author":"Cox","year":"1954","journal-title":"J. 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(2022). Arctic Sea Ice Classification Based on CFOSAT SWIM Data at Multiple Small Incidence Angles. Remote Sens., 14.","DOI":"10.3390\/rs14010091"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e2021EA002046","DOI":"10.1029\/2021EA002046","article-title":"Sea-Ice Detection from Near-Nadir Ku-Band Echoes From CFOSAT\/SWIM Scatterometer","volume":"9","author":"Peureux","year":"2022","journal-title":"Earth Space Sci."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Panfilova, M., and Karaev, V. (2023). Sea Ice Detection by an Unsupervised Method Using Ku- and Ka-Band Radar Data at Low Incidence Angles: First Results. Remote Sens., 15.","DOI":"10.3390\/rs15143530"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"C02S03","DOI":"10.1029\/2005JC003384","article-title":"Sea ice remote sensing using AMSR-E 89-GHz channels","volume":"113","author":"Spreen","year":"2008","journal-title":"J. Geophys. Res. 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The Concise Encyclopedia of Statistics, Springer."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/5\/859\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:07:12Z","timestamp":1760105232000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/5\/859"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,29]]},"references-count":12,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2024,3]]}},"alternative-id":["rs16050859"],"URL":"https:\/\/doi.org\/10.3390\/rs16050859","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2024,2,29]]}}}