{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/detecting-volcano-deformation-in-insar-using","title":"Detecting Volcano Deformation in InSAR using Deep learning","arxiv_id":"1803.00380","date":"2018-01-21","proceeding":null,"authors":["N. Anantrasirichai","F. Albino","P. Hill","D. Bull","J. Biggs"],"abstract":"Globally 800 million people live within 100 km of a volcano and currently\n1500 volcanoes are considered active, but half of these have no ground-based\nmonitoring. Alternatively, satellite radar (InSAR) can be employed to observe\nvolcanic ground deformation, which has shown a significant statistical link to\neruptions. Modern satellites provide large coverage with high resolution\nsignals, leading to huge amounts of data. The explosion in data has brought\nmajor challenges associated with timely dissemination of information and\ndistinguishing volcano deformation patterns from noise, which currently relies\non manual inspection. Moreover, volcano observatories still lack expertise to\nexploit satellite datasets, particularly in developing countries. This paper\npresents a novel approach to detect volcanic ground deformation automatically\nfrom wrapped-phase InSAR images. Convolutional neural networks (CNN) are\nemployed to detect unusual patterns within the radar data.","url_abs":"http://arxiv.org/abs/1803.00380v1","url_pdf":"http://arxiv.org/pdf/1803.00380v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"detecting-volcano-deformation-in-insar-using","repo_url":"https://github.com/pui-nantheera/volcano_deform_detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"event-detection","task_name":"Event Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}