{"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/change-detection-between-multimodal-remote","title":"Change Detection between Multimodal Remote Sensing Data Using Siamese CNN","arxiv_id":"1807.09562","date":"2018-07-25","proceeding":null,"authors":["Zhenchao Zhang","George Vosselman","Markus Gerke","Devis Tuia","Michael Ying Yang"],"abstract":"Detecting topographic changes in the urban environment has always been an\nimportant task for urban planning and monitoring. In practice, remote sensing\ndata are often available in different modalities and at different time epochs.\nChange detection between multimodal data can be very challenging since the data\nshow different characteristics. Given 3D laser scanning point clouds and 2D\nimagery from different epochs, this paper presents a framework to detect\nbuilding and tree changes. First, the 2D and 3D data are transformed to image\npatches, respectively. A Siamese CNN is then employed to detect candidate\nchanges between the two epochs. Finally, the candidate patch-based changes are\ngrouped and verified as individual object changes. Experiments on the urban\ndata show that 86.4\\% of patch pairs can be correctly classified by the model.","url_abs":"http://arxiv.org/abs/1807.09562v1","url_pdf":"http://arxiv.org/pdf/1807.09562v1.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":"change-detection-between-multimodal-remote","repo_url":"https://github.com/lazharkhelifi/deeplearning_changedetection_remotesensing_review","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"change-detection","task_name":"Change 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}