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ID.57979: Monitoring Harsh Coastal environments and Ocean Surveillance using radar remote sensing (MAC-OS)

Oceans and coastal zones


The proposed project aims at demonstrating the benefits of radar products for coastal area monitoring and, therefore, it is framed into the ÔÇ£Ocean & coastal zoneÔÇØ Dragon-5 thematic area. The various sub-topics addressed within this domain include the understanding of ÔÇ£marine dynamic environmentÔÇØ, the analysis of ÔÇ£sea surface characteristicsÔÇØ and the EO support for ÔÇ£marine disastersÔÇØ management. These applications are of paramount importance for both the scientific and the end-user communities. In particular, the project aims at exploiting Synthetic Aperture Radar (SAR) satellite measurements to generate innovative added-value products to observe coastal areas characterised by harsh environments, even under extreme weather conditions. The project relies on a deep co-operation between Chinese and European (including Italy, UK and Spain) partners that call for a complementary expertise which is a key resource to publish co-authored results and to train European and Chinese YSs. This co-operation has been already successfully experienced during the Dragon-4 project 32235. Master and PhD students will actively take part in the modeling and analysis of the phenomena under study, i.e. coastal water pollution, coastal erosion, in-land water body observation, metallic target detection, typhoon/cyclone monitoring, etc., as well as in the development of effective and reliable algorithms for the generation of added-value products from remotely sensed measurements. The project also aims at stimulating the use of complementary microwave satellite instruments, including scatterometer and radiometer on-board of operational and planned missions operated by ESA, ESA TPM and Chinese EO.The proposed piece of research will involve the development of tailored models of the processes under study combined with Artificial Intelligence (AI) methodologies that allow the interpretation and the processing of multi-pol (MP) SAR measurements, collected under different imaging modes, in order to derive the above-mentioned user friendly added-value products. The latter include, but are not limited to, maps of metallic targets at sea, e.g., ships and wind farms, as well as aquacultures, wetland coastal erosion/accretion trends due to both anthropogenic and natural phenomena, mapping marine pollutants, modeling, tracking and forecasting extreme weather events as cyclones/typhoons.Summarizing, this research project will address the following main assets:a) Promoting an “intelligent”, i.e., physically-based, exploitation of MP SAR measurements for generating end-user friendly added-values products in the context of harsh coastal zone management; b) Developing new AI-based models/methods to deal with the synergistic exploitation of microwave satellite measurements to address key issues for coastal area monitoring; c) Boosting the co-operation between Chinese and European partners by taking full advantage of their respective expertise, including the training of YS.ProjectÔÇÖs outcomes will be disseminated through publications to be submitted to Dragon 5 symposia at mid-term and final stages, as well as annual progress reports on the status of the projects will be provided during Dragon 5 symposia. The main achievements will be also presented at dedicated workshops and international symposia and will be submitted on peer-reviewed journals and refereed conferences. The proposed project is financially backed on Sino-European funds, e.g. ÔÇ£Development of algorithms to analyse and processing signals and images in the complex domainÔÇØ, funded by the European Fund for Regional Development (DING127), “On-board processing and remote sensing for meteorological and marine disasters”, funded by the National Key R&D Program of China (2017YFB0502803) and “Objective Tropical Cyclone Intensity Estimation from Remotely Sensed Passive and Active Microwave Observations”, funded by the National Natural Science Foundation of China (41871268).


PI Europe
Prof.. Ferdinando Nunziata, Univ degli studi di Napoli Parthenope, ITALY
Co-PIs Europe
Dr. Andrea Buono, Università, ITALY
Dr. Valeria Corcione, Università, ITALY
Dr. Marcos Portabella, ICM, SPAIN
Prof. Armando Marino, University, UK
Prof. Shuo Wang, University, UK
PI China
Prof.. Xiaofeng Yang, State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Ac, CHINA
Co-PIs China
Le Gao, Institute of, CHINA
Guoqiang Zhong, Ocean Un, CHINA
Jie Guo, Yantai Inst, CHINA
Weizeng Shao, Zhejiang O, CHINA
Qing Xu, Hohai Uni, CHINA