Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/33081
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Microwave Satellite Measurements for Coastal Area and Extreme Weather Monitoring
Author(s): Nunziata, Ferdinando
Li, Xiaofeng
Marino, Armando
Shao, Weizeng
Portabella, Marcos
Yang, Xiaofeng
Buono, Andrea
Contact Email: armando.marino@stir.ac.uk
Keywords: microwave satellites
multipolarization
multifrequency
oceans
coastal areas
coastline
sea wind field
ocean pollution
ships
Issue Date: Aug-2021
Date Deposited: 11-Aug-2021
Citation: Nunziata F, Li X, Marino A, Shao W, Portabella M, Yang X & Buono A (2021) Microwave Satellite Measurements for Coastal Area and Extreme Weather Monitoring. Remote Sensing, 13 (16), Art. No.: 3126. https://doi.org/10.3390/rs13163126
Abstract: In this project report, the main outcomes relevant to the Sino-European Dragon-4 cooperation project ID 32235 “Microwave satellite measurements for coastal area and extreme weather monitoring” are reported. The project aimed at strengthening the Sino-European research cooperation in the exploitation of European Space Agency, Chinese and third-party mission Earth Observation (EO) microwave satellite data. The latter were exploited to perform an effective monitoring of coastal areas, even under extreme weather conditions. An integrated multifrequency/polarization approach based on complementary microwave sensors (e.g., Synthetic Aperture Radar, scatterometer, radiometer), together with ancillary information coming from independent sources, i.e., optical imagery, numerical simulations and ground measurements, was designed. In this framework, several tasks were addressed including marine target detection, sea pollution, sea surface wind estimation and coastline extraction/classification. The main outcomes are both theoretical (i.e., new models and algorithms were developed) and applicative (i.e., user-friendly maps were provided to the end-user community of coastal area management according to smart processing of remotely sensed data). The scientific relevance consists in the development of new algorithms, the effectiveness and robustness of which were verified on actual microwave measurements, and the improvement of existing methodologies to deal with challenging test cases.
DOI Link: 10.3390/rs13163126
Rights: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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