{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T04:33:55Z","timestamp":1780634035126,"version":"3.54.1"},"reference-count":92,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2020,12,4]],"date-time":"2020-12-04T00:00:00Z","timestamp":1607040000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["269661170"],"award-info":[{"award-number":["269661170"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Mapping planetary surfaces is an intricate task that forms the basis for many geologic, geomorphologic, and geographic studies of planetary bodies. In this work, we present a method to automate a specific type of planetary mapping, geomorphic mapping, taking machine learning as a basis. Additionally, we introduce a novel dataset, termed DoMars16k, which contains 16,150 samples of fifteen different landforms commonly found on the Martian surface. We use a convolutional neural network to establish a relation between Mars Reconnaissance Orbiter Context Camera images and the landforms of the dataset. Afterwards, we employ a sliding-window approach in conjunction with a Markov Random field smoothing to create maps in a weakly supervised fashion. Finally, we provide encouraging results and carry out automated geomorphological analyses of Jezero crater, the Mars2020 landing site, and Oxia Planum, the prospective ExoMars landing site.<\/jats:p>","DOI":"10.3390\/rs12233981","type":"journal-article","created":{"date-parts":[[2020,12,7]],"date-time":"2020-12-07T21:37:42Z","timestamp":1607377062000},"page":"3981","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["DoMars16k: A Diverse Dataset for Weakly Supervised Geomorphologic Analysis on Mars"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2691-4129","authenticated-orcid":false,"given":"Thorsten","family":"Wilhelm","sequence":"first","affiliation":[{"name":"Image Analysis Group, TU Dortmund University, 44227 Dortmund, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melina","family":"Geis","sequence":"additional","affiliation":[{"name":"Image Analysis Group, TU Dortmund University, 44227 Dortmund, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jens","family":"P\u00fcttschneider","sequence":"additional","affiliation":[{"name":"Image Analysis Group, TU Dortmund University, 44227 Dortmund, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timo","family":"Sievernich","sequence":"additional","affiliation":[{"name":"Image Analysis Group, TU Dortmund University, 44227 Dortmund, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tobias","family":"Weber","sequence":"additional","affiliation":[{"name":"Image Analysis Group, TU Dortmund University, 44227 Dortmund, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4324-1459","authenticated-orcid":false,"given":"Kay","family":"Wohlfarth","sequence":"additional","affiliation":[{"name":"Image Analysis Group, TU Dortmund University, 44227 Dortmund, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0715-0955","authenticated-orcid":false,"given":"Christian","family":"W\u00f6hler","sequence":"additional","affiliation":[{"name":"Image Analysis Group, TU Dortmund University, 44227 Dortmund, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hargitai, H. 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