{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T07:40:02Z","timestamp":1770277202439,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T00:00:00Z","timestamp":1629244800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100011690","name":"UK Space Agency","doi-asserted-by":"publisher","award":["ST\/S001891\/1"],"award-info":[{"award-number":["ST\/S001891\/1"]}],"id":[{"id":"10.13039\/100011690","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100011690","name":"UK Space Agency","doi-asserted-by":"publisher","award":["ST\/R003025\/1"],"award-info":[{"award-number":["ST\/R003025\/1"]}],"id":[{"id":"10.13039\/100011690","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000271","name":"Science and Technology Facilities Council","doi-asserted-by":"publisher","award":["ST\/K000977\/1"],"award-info":[{"award-number":["ST\/K000977\/1"]}],"id":[{"id":"10.13039\/501100000271","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2019M663073"],"award-info":[{"award-number":["2019M663073"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>We demonstrate an end-to-end application of the in-house deep learning-based surface modelling system, called MADNet, to produce three large area 3D mapping products from single images taken from the ESA Mars Express\u2019s High Resolution Stereo Camera (HRSC), the NASA Mars Reconnaissance Orbiter\u2019s Context Camera (CTX), and the High Resolution Imaging Science Experiment (HiRISE) imaging data over the ExoMars 2022 Rosalind Franklin rover\u2019s landing site at Oxia Planum on Mars. MADNet takes a single orbital optical image as input, provides pixelwise height predictions, and uses a separate coarse Digital Terrain Model (DTM) as reference, to produce a DTM product from the given input image. Initially, we demonstrate the resultant 25 m\/pixel HRSC DTM mosaic covering an area of 197 km \u00d7 182 km, providing fine-scale details to the 50 m\/pixel HRSC MC-11 level-5 DTM mosaic. Secondly, we demonstrate the resultant 12 m\/pixel CTX MADNet DTM mosaic covering a 114 km \u00d7 117 km area, showing much more detail in comparison to photogrammetric DTMs produced using the open source in-house developed CASP-GO system. Finally, we demonstrate the resultant 50 cm\/pixel HiRISE MADNet DTM mosaic, produced for the first time, covering a 74.3 km \u00d7 86.3 km area of the 3-sigma landing ellipse and partially the ExoMars team\u2019s geological characterisation area. The resultant MADNet HiRISE DTM mosaic shows fine-scale details superior to existing Planetary Data System (PDS) HiRISE DTMs and covers a larger area that is considered difficult for existing photogrammetry and photoclinometry pipelines to achieve, especially given the current limitations of stereo HiRISE coverage. All of the resultant DTM mosaics are co-aligned with each other, and ultimately with the Mars Global Surveyor\u2019s Mars Orbiter Laser Altimeter (MOLA) DTM, providing high spatial and vertical congruence. In this paper, technical details are presented, issues that arose are discussed, along with a visual evaluation and quantitative assessments of the resultant DTM mosaic products.<\/jats:p>","DOI":"10.3390\/rs13163270","type":"journal-article","created":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T22:51:00Z","timestamp":1629327060000},"page":"3270","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Large Area High-Resolution 3D Mapping of Oxia Planum: The Landing Site for the ExoMars Rosalind Franklin Rover"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9170-6655","authenticated-orcid":false,"given":"Yu","family":"Tao","sequence":"first","affiliation":[{"name":"Imaging Group, Mullard Space Science Laboratory, Department of Space and Climate Physics, University College London, Holmbury St Mary, Surrey RH5 6NT, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5077-3736","authenticated-orcid":false,"given":"Jan-Peter","family":"Muller","sequence":"additional","affiliation":[{"name":"Imaging Group, Mullard Space Science Laboratory, Department of Space and Climate Physics, University College London, Holmbury St Mary, Surrey RH5 6NT, UK"}]},{"given":"Susan J.","family":"Conway","sequence":"additional","affiliation":[{"name":"Laboratoire de Plan\u00e9tologie et G\u00e9odynamique, CNRS, UMR 6112, Universit\u00e9 de Nantes, 44300 Nantes, France"}]},{"given":"Siting","family":"Xiong","sequence":"additional","affiliation":[{"name":"College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China"},{"name":"Ministry of Natural Resources Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,18]]},"reference":[{"key":"ref_1","first-page":"17","article-title":"HRSC: The high resolution stereo camera of Mars Express","volume":"1240","author":"Neukum","year":"2004","journal-title":"Sci. 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