{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:34:59Z","timestamp":1760232899009,"version":"build-2065373602"},"reference-count":54,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,8]],"date-time":"2022-12-08T00:00:00Z","timestamp":1670457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["4000128903\/1 9\/l-DT"],"award-info":[{"award-number":["4000128903\/1 9\/l-DT"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Satellite and airborne observations of surface elevation are critical in understanding climatic and glaciological processes and quantifying their impact on changes in ice masses and sea level contribution. With the growing number of dedicated airborne campaigns and experimental and operational satellite missions, the science community has access to unprecedented and ever-increasing data. Combining elevation datasets allows potentially greater spatial-temporal coverage and improved accuracy; however, combining data from different sensor types and acquisition modes is difficult by differences in intrinsic sensor properties and processing methods. This study focuses on the combination of elevation measurements derived from ICESat-2 and Operation IceBridge LIDAR instruments and from CryoSat-2\u2019s novel interferometric radar altimeter over Greenland. We develop a deep neural network based on sub-waveform information from CryoSat-2, elevation differences between radar and LIDAR, and additional inputs representing local geophysical information. A time series of maps are created showing observed LIDAR-radar differences and neural network model predictions. Mean LIDAR vs. interferometric radar adjustments and the broad spatial and temporal trends thereof are recreated by the neural network. The neural network also predicts radar-LIDAR differences with respect to waveform parameters better than a simple linear model; however, point level adjustments and the magnitudes of the spatial and temporal trends are underestimated.<\/jats:p>","DOI":"10.3390\/rs14246210","type":"journal-article","created":{"date-parts":[[2022,12,8]],"date-time":"2022-12-08T02:51:56Z","timestamp":1670467916000},"page":"6210","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Using Deep Learning to Model Elevation Differences between Radar and Laser Altimetry"],"prefix":"10.3390","volume":"14","author":[{"given":"Alex","family":"Horton","sequence":"first","affiliation":[{"name":"Earthwave Ltd., Edinburgh EH3 9DR, UK"}]},{"given":"Martin","family":"Ewart","sequence":"additional","affiliation":[{"name":"Earthwave Ltd., Edinburgh EH3 9DR, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3346-9289","authenticated-orcid":false,"given":"Noel","family":"Gourmelen","sequence":"additional","affiliation":[{"name":"School of Geosciences, University of Edinburgh, Edinburgh EH8 9YL, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4140-3813","authenticated-orcid":false,"given":"Xavier","family":"Fettweis","sequence":"additional","affiliation":[{"name":"SPHERES Research Unit, Department of Geography, University of Li\u00e8ge, 4000 Li\u00e8ge, Belgium"}]},{"given":"Amos","family":"Storkey","sequence":"additional","affiliation":[{"name":"School of Informatics, University of Edinburgh, Edinburgh EH8 9YL, UK"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1126\/science.246.4937.1587","article-title":"Growth of Greenland Ice Sheet: Measurement","volume":"246","author":"Zwally","year":"1989","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1126\/science.282.5388.456","article-title":"Antarctic Elevation Change from 1992 to 1996","volume":"282","author":"Wingham","year":"1998","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"856","DOI":"10.1126\/science.1089768","article-title":"Larsen Ice Shelf Has Progressively Thinned","volume":"302","author":"Shepherd","year":"2003","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1126\/science.291.5505.862","article-title":"Inland Thinning of Pine Island Glacier, West Antarctica","volume":"291","author":"Shepherd","year":"2001","journal-title":"Science"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"509","DOI":"10.3189\/172756505781829007","article-title":"Mass Changes of the Greenland and Antarctic Ice Sheets and Shelves and Contributions to Sea-Level Rise: 1992\u20132002","volume":"51","author":"Zwally","year":"2005","journal-title":"J. Glaciol."},{"key":"ref_6","first-page":"1627","article-title":"Mass Balance of the Antarctic Ice Sheet","volume":"364","author":"Wingham","year":"2006","journal-title":"Philos. Trans. R. Soc. Math. Phys. Eng. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1544","DOI":"10.1126\/science.1136897","article-title":"An Active Subglacial Water System in West Antarctica Mapped from Space","volume":"315","author":"Fricker","year":"2007","journal-title":"Science"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1038\/nature08471","article-title":"Extensive Dynamic Thinning on the Margins of the Greenland and Antarctic Ice Sheets","volume":"461","author":"Pritchard","year":"2009","journal-title":"Nature"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1038\/nature11324","article-title":"Contrasting Patterns of Early Twenty-First-Century Glacier Mass Change in the Himalayas","volume":"488","author":"Berthier","year":"2012","journal-title":"Nature"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"499","DOI":"10.5194\/tc-7-499-2013","article-title":"A New Bed Elevation Dataset for Greenland","volume":"7","author":"Bamber","year":"2013","journal-title":"Cryosphere"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3899","DOI":"10.1002\/2014GL060111","article-title":"Increased Ice Losses from Antarctica Detected by CryoSat-2","volume":"41","author":"McMillan","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"9796","DOI":"10.1002\/2017GL074929","article-title":"Channelized Melting Drives Thinning under a Rapidly Melting Antarctic Ice Shelf","volume":"44","author":"Gourmelen","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1016\/j.asr.2017.11.014","article-title":"CryoSat-2 Swath Interferometric Altimetry for Mapping Ice Elevation and Elevation Change","volume":"62","author":"Gourmelen","year":"2018","journal-title":"Adv. Space Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1212","DOI":"10.3390\/rs1041212","article-title":"Antarctic Ice Sheet and Radar Altimetry: A Review","volume":"1","author":"Parouty","year":"2009","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3919","DOI":"10.1002\/2015GL063296","article-title":"Greenland 2012 Melt Event Effects on CryoSat-2 Radar Altimetry","volume":"42","author":"Nilsson","year":"2015","journal-title":"Geophys. Res. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"9633","DOI":"10.1109\/TGRS.2019.2928232","article-title":"Compensating Changes in the Penetration Depth of Pulse-Limited Radar Altimetry over the Greenland Ice Sheet","volume":"57","author":"Slater","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1005","DOI":"10.5194\/tc-15-1005-2021","article-title":"Brief Communication: Glacier Run-off Estimation Using Altimetry-Derived Basin Volume Change: Case Study at Humboldt Glacier, Northwest Greenland","volume":"15","author":"Gray","year":"2021","journal-title":"Cryosphere"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"6069","DOI":"10.1038\/s41467-021-26229-4","article-title":"Increased Variability in Greenland Ice Sheet Runoff from Satellite Observations","volume":"12","author":"Slater","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"33471","DOI":"10.1029\/2001JD000498","article-title":"Controls on ERS Altimeter Measurements over Ice Sheets: Footprint-Scale Topography, Backscatter Fluctuations, and the Dependence of Microwave Penetration Depth on Satellite Orientation","volume":"106","author":"Arthern","year":"2001","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"146","DOI":"10.3389\/feart.2019.00146","article-title":"Measuring Height Change around the Periphery of the Greenland Ice Sheet with Radar Altimetry","volume":"7","author":"Gray","year":"2019","journal-title":"Front. Earth Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1537","DOI":"10.1109\/LGRS.2017.2720847","article-title":"An Accurate Semianalytical Waveform Model for Mispointed SAR Interferometric Altimeters","volume":"14","author":"Recchia","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"891","DOI":"10.5194\/tc-12-891-2018","article-title":"Improving Gridded Snow Water Equivalent Products in British Columbia, Canada: Multi-Source Data Fusion by Neural Network Models","volume":"12","author":"Snauffer","year":"2018","journal-title":"Cryosphere"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"eabj8138","DOI":"10.1126\/sciadv.abj8138","article-title":"Unexplored Antarctic Meteorite Collection Sites Revealed through Machine Learning","volume":"8","author":"Tollenaar","year":"2022","journal-title":"Sci. Adv."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2421","DOI":"10.5194\/tc-13-2421-2019","article-title":"Estimating Snow Depth on Arctic Sea Ice Using Satellite Microwave Radiometry and a Neural Network","volume":"13","author":"Donlon","year":"2019","journal-title":"Cryosphere"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1080\/1064119X.2021.1899348","article-title":"Wavelet Decomposition and Deep Learning of Altimetry Waveform Retracking for Lake Urmia Water Level Survey","volume":"40","author":"Asgari","year":"2022","journal-title":"Mar. Georesources Geotechnol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1857","DOI":"10.5194\/tc-7-1857-2013","article-title":"Interferometric Swath Processing of Cryosat Data for Glacial Ice Topography","volume":"7","author":"Gray","year":"2013","journal-title":"Cryosphere"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"L22501","DOI":"10.1029\/2009GL040416","article-title":"Ice-Sheet Elevations from across-Track Processing of Airborne Interferometric Radar Altimetry","volume":"36","author":"Hawley","year":"2009","journal-title":"Geophys. Res. Lett."},{"key":"ref_28","unstructured":"Krabill, W. (2014). IceBridge ATM L2 Icessn Elevation, Slope, and Roughness, Version 2."},{"key":"ref_29","unstructured":"Smith, B. (2020). ATLAS\/ICESat-2 L3A Land Ice Height, Version 3, National Snow and Ice Data Center."},{"key":"ref_30","unstructured":"Porter, C., Morin, P., Howat, I., Noh, M.-J., Bates, B., Peterman, K., Keesey, S., Schlenk, M., Gardiner, J., and Tomko, K. (2022, February 20). ArcticDEM, Version 3. Available online: https:\/\/dataverse.harvard.edu\/dataset.xhtml?persistentId=doi:10.7910\/DVN\/OHHUKH."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"265","DOI":"10.3189\/S002214300000321X","article-title":"Altimetric Observations of Surface Characteristics of the Antarctic Ice Sheet","volume":"43","year":"1997","journal-title":"J. Glaciol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1038\/s41592-019-0686-2","article-title":"SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python","volume":"17","author":"Virtanen","year":"2020","journal-title":"Nat. Methods"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"895","DOI":"10.5194\/tc-13-895-2019","article-title":"Sensitivity of Glacier Volume Change Estimation to DEM Void Interpolation","volume":"13","author":"McNabb","year":"2019","journal-title":"Cryosphere"},{"key":"ref_34","unstructured":"Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., and Antiga, L. (2019). PyTorch: An Imperative Style, High-Performance Deep Learning Library. Advances in Neural Information Processing Systems 32, Curran Associates, Inc."},{"key":"ref_35","first-page":"3","article-title":"Rectifier Nonlinearities Improve Neural Network Acoustic Models","volume":"30","author":"Maas","year":"2013","journal-title":"Proc. Icml."},{"key":"ref_36","unstructured":"Klambauer, G., Unterthiner, T., Mayr, A., and Hochreiter, S. (2017). Self-Normalizing Neural Networks. arXiv."},{"key":"ref_37","first-page":"1929","article-title":"Dropout: A Simple Way to Prevent Neural Networks from Overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref_38","first-page":"448","article-title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift","volume":"Volume 37","author":"Bach","year":"2015","journal-title":"Proceedings of the 32nd International Conference on Machine Learning"},{"key":"ref_39","unstructured":"Ba, J.L., Kiros, J.R., and Hinton, G.E. (2016). Layer Normalization. arXiv."},{"key":"ref_40","first-page":"1139","article-title":"On the Importance of Initialization and Momentum in Deep Learning","volume":"Volume 28","author":"Dasgupta","year":"2013","journal-title":"Proceedings of the 30th International Conference on Machine Learning"},{"key":"ref_41","unstructured":"Kingma, D.P., and Ba, J. (2014). Adam: A Method for Stochastic Optimization. arXiv."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1214\/aoms\/1177703732","article-title":"Robust Estimation of a Location Parameter","volume":"35","author":"Huber","year":"1964","journal-title":"Ann. Math. Stat."},{"key":"ref_43","first-page":"2825","article-title":"Scikit-Learn: Machine Learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_44","unstructured":"Earthwave (2022, February 20). The University of Edinburgh. isardSAT CryoTEMPO-EOLIS\u2014Elevation over Land Ice from Swath\u2014Product Handbook. Available online: https:\/\/Earth.Esa.Int\/Eogateway\/Documents\/20142\/37627\/CryoTEMPO-Thematic-Product-Handbook.Pdf."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.5194\/tc-11-1041-2017","article-title":"A Revised Calibration of the Interferometric Mode of the CryoSat-2 Radar Altimeter Improves Ice Height and Height Change Measurements in Western Greenland","volume":"11","author":"Gray","year":"2017","journal-title":"Cryosphere"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"675","DOI":"10.3189\/S0022143000016579","article-title":"A Combined Surface-and Volume-Scattering Model for Ice-Sheet Radar Altimetry","volume":"39","author":"Davis","year":"1993","journal-title":"J. Glaciol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1080\/01431168808954881","article-title":"A Model of Satellite Radar Altimeter Return from Ice Sheets","volume":"9","author":"Ridley","year":"1988","journal-title":"Int. J. Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1016\/j.asr.2005.07.027","article-title":"CryoSat: A Mission to Determine the Fluctuations in Earth\u2019s Land and Marine Ice Fields","volume":"37","author":"Wingham","year":"2006","journal-title":"Adv. Space Res."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"L24402","DOI":"10.1029\/2004GL021533","article-title":"Greenland Ice Sheet: Increased Coastal Thinning","volume":"31","author":"Krabill","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1810","DOI":"10.1109\/36.851765","article-title":"Recent Changes in the Microwave Scattering Properties of the Antarctic Ice Sheet","volume":"38","author":"Bingham","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"13072","DOI":"10.1029\/2019GL084886","article-title":"Assessment of ICESat-2 Ice Sheet Surface Heights, Based on Comparisons over the Interior of the Antarctic Ice Sheet","volume":"46","author":"Brunt","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"e2020EA001494","DOI":"10.1029\/2020EA001494","article-title":"ICESat-2 Pointing Calibration and Geolocation Performance","volume":"8","author":"Luthcke","year":"2021","journal-title":"Earth Space Sci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"3935","DOI":"10.5194\/tc-14-3935-2020","article-title":"GrSMBMIP: Intercomparison of the Modelled 1980\u20132012 Surface Mass Balance over the Greenland Ice Sheet","volume":"14","author":"Fettweis","year":"2020","journal-title":"Cryosphere"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2235","DOI":"10.5194\/tc-14-2235-2020","article-title":"The Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) High-Priority Candidate Mission","volume":"14","author":"Kern","year":"2020","journal-title":"Cryosphere"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/24\/6210\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:36:10Z","timestamp":1760146570000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/24\/6210"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,8]]},"references-count":54,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["rs14246210"],"URL":"https:\/\/doi.org\/10.3390\/rs14246210","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,12,8]]}}}