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Multi-scale drift characteristics of Ulva prolifera in the Yellow Sea derived from deep learning-based MODIS and Sentinel-1 observations.

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Title: Multi-scale drift characteristics of Ulva prolifera in the Yellow Sea derived from deep learning-based MODIS and Sentinel-1 observations.
Authors: Geng X; School of Geographical Sciences, Hebei Normal University, Shijiazhuang, 050024, China; Key Laboratory of Marine Ecological Monitoring and Restoration Technology, Ministry of Natural Resources, Shanghai, 200062, China; Hebei Technology Innovation Center for Remote Sensing Identification of Environmental Change, Hebei Normal University, Shijiazhuang, 050024, China., Li H; School of Geographical Sciences, Hebei Normal University, Shijiazhuang, 050024, China; Hebei Technology Innovation Center for Remote Sensing Identification of Environmental Change, Hebei Normal University, Shijiazhuang, 050024, China. Electronic address: lihuiru@hebtu.edu.cn., Fan R; School of Geographical Sciences, Hebei Normal University, Shijiazhuang, 050024, China; Hebei Technology Innovation Center for Remote Sensing Identification of Environmental Change, Hebei Normal University, Shijiazhuang, 050024, China., Zhao Y; School of Geographical Sciences, Hebei Normal University, Shijiazhuang, 050024, China; Hebei Technology Innovation Center for Remote Sensing Identification of Environmental Change, Hebei Normal University, Shijiazhuang, 050024, China., Guo E; School of Geographical Sciences, Hebei Normal University, Shijiazhuang, 050024, China; Hebei Technology Innovation Center for Remote Sensing Identification of Environmental Change, Hebei Normal University, Shijiazhuang, 050024, China., Qi R; Natural Resources Services Centre of Liaoning Province-BasicSurveying and Mapping Institute of Liaoning Province, Jinzhou, 121000, China.
Source: Marine pollution bulletin [Mar Pollut Bull] 2026 Jul; Vol. 228, pp. 119516. Date of Electronic Publication: 2026 Mar 18.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: England NLM ID: 0260231 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-3363 (Electronic) Linking ISSN: 0025326X NLM ISO Abbreviation: Mar Pollut Bull Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-3363
DOI:10.1016/j.marpolbul.2026.119516