{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T01:54:28Z","timestamp":1780451668640,"version":"3.54.1"},"reference-count":53,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T00:00:00Z","timestamp":1702512000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"DEFRA"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>In the face of increasing flood risks intensified by climate change, accurate flood inundation mapping is pivotal for effective disaster management. This study introduces a novel explainable deep learning architecture designed to generate precise flood inundation maps from diverse satellite data sources. A comprehensive evaluation of the proposed model is conducted, comparing it with state-of-the-art models across various fusion configurations of Multispectral Optical and Synthetic Aperture Radar (SAR) images. The proposed model consistently outperforms other models across both Sentinel-1 and Sentinel-2 images, achieving an Intersection Over Union (IOU) of 0.5862 and 0.7031, respectively. Furthermore, analysis of the different fusion combinations reveals that the use of Sentinel-1 in combination with RGB, NIR, and SWIR achieves the highest IOU of 0.7053 and that the inclusion of the SWIR band has the greatest positive impact on the results. Gradient-weighted class activation mapping is employed to provide insights into its decision-making processes, enhancing transparency and interpretability. This research contributes significantly to the field of flood inundation mapping, offering an efficient model suitable for diverse applications. This study not only advances flood inundation mapping but also provides a valuable tool for improved understanding of deep learning decision-making in this area, ultimately contributing to improved disaster management strategies.<\/jats:p>","DOI":"10.3390\/info14120660","type":"journal-article","created":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T03:58:02Z","timestamp":1702526282000},"page":"660","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Optimal Fusion of Multispectral Optical and SAR Images for Flood Inundation Mapping through Explainable Deep Learning"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-5724-6637","authenticated-orcid":false,"given":"Jacob","family":"Sanderson","sequence":"first","affiliation":[{"name":"Department of Computer and Information Sciences, Northumbria University, Newcastle Upon Tyne NE1 8ST, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Mao","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Northumbria University, Newcastle Upon Tyne NE1 8ST, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3340-8489","authenticated-orcid":false,"given":"Mohammed A. M.","family":"Abdullah","sequence":"additional","affiliation":[{"name":"Computer and Information Engineering Department, Electronics Engineering College, Ninevah University, Mosul 41002, Iraq"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raid Rafi Omar","family":"Al-Nima","sequence":"additional","affiliation":[{"name":"Technical Engineering College of Mosul, Northern Technical University, Mosul 41001, Iraq"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8698-7605","authenticated-orcid":false,"given":"Wai Lok","family":"Woo","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Northumbria University, Newcastle Upon Tyne NE1 8ST, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4018004","DOI":"10.1061\/(ASCE)HE.1943-5584.0001614","article-title":"Communicating the impacts of projected climate change on heavy rainfall using a weighted ensemble approach","volume":"23","author":"Markus","year":"2018","journal-title":"J. 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