{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:29:15Z","timestamp":1760956155367,"version":"build-2065373602"},"reference-count":49,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,9]],"date-time":"2022-09-09T00:00:00Z","timestamp":1662681600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["41941006","41876230","42276257","2019YFC1509102"],"award-info":[{"award-number":["41941006","41876230","42276257","2019YFC1509102"]}]},{"name":"National Key Research and Development Program of China","award":["41941006","41876230","42276257","2019YFC1509102"],"award-info":[{"award-number":["41941006","41876230","42276257","2019YFC1509102"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Understanding englacial and subglacial structures is a fundamental method of inferring ice sheets\u2019 historical evolution and surface mass balance. The internal layer continuity index and the basal roughness are key parameters and indicators for the speculation of the relationship between the ice sheet\u2019s internal structure or bottom and ice flow. Several methods have been proposed in the past two decades to quantitatively calculate the continuity index of ice layer geometry and the roughness of the ice\u2013bedrock interface based on radar echo signals. These methods are mainly based on the average of the absolute value of the vertical gradient of the echo signal amplitude and the standard deviation of the horizontal fluctuation of the bedrock interface. However, these methods are limited by the amount and quality of unprocessed radar datasets and have not been widely used, which also hinders further research, such as the analysis of the englacial reflectivity, the subglacial conditions, and the history of the ice sheets. In this paper, based on geophysical processing methods for radar image denoising and deep learning for ice layer and bedrock interface extraction, we propose a new method for calculating the layer continuity index and basal roughness. Using this method, we demonstrate the ice-penetrating radar data processing and compare the imaging and calculation of the radar profiles from Dome A to Zhongshan Station, East Antarctica. We removed the noise from the processed radar data, extracted ice layer continuity features, and used other techniques to verify the calculation. The potential application of this method in the future is illustrated by several examples. We believe that this method can become an effective approach for future Antarctic geophysical and glaciological research and for obtaining more information about the history and dynamics of ice sheets from their radar-extracted internal structure.<\/jats:p>","DOI":"10.3390\/rs14184507","type":"journal-article","created":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T04:05:41Z","timestamp":1663041941000},"page":"4507","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Quantifying Basal Roughness and Internal Layer Continuity Index of Ice Sheets by an Integrated Means with Radar Data and Deep Learning"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6226-4891","authenticated-orcid":false,"given":"Xueyuan","family":"Tang","sequence":"first","affiliation":[{"name":"Key Laboratory of Polar Science of Ministry of Natural Resources (MNR), Polar Research Institute of China, Shanghai 200136, China"},{"name":"School of Oceanography, Shanghai Jiao Tong University, Shanghai 200230, China"}]},{"given":"Kun","family":"Luo","sequence":"additional","affiliation":[{"name":"Key Laboratory of Polar Science of Ministry of Natural Resources (MNR), Polar Research Institute of China, Shanghai 200136, China"},{"name":"College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5426-9262","authenticated-orcid":false,"given":"Sheng","family":"Dong","sequence":"additional","affiliation":[{"name":"Key Laboratory of Polar Science of Ministry of Natural Resources (MNR), Polar Research Institute of China, Shanghai 200136, China"},{"name":"School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China"},{"name":"Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518055, China"}]},{"given":"Zidong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Polar Science of Ministry of Natural Resources (MNR), Polar Research Institute of China, Shanghai 200136, China"},{"name":"College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China"}]},{"given":"Bo","family":"Sun","sequence":"additional","affiliation":[{"name":"Key Laboratory of Polar Science of Ministry of Natural Resources (MNR), Polar Research Institute of China, Shanghai 200136, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,9]]},"reference":[{"key":"ref_1","unstructured":"IPCC (2021, August 01). 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