Conference Agenda

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Session Overview
Session
S.2.1: COASTAL ZONES & OCEANS
Time:
Wednesday, 13/Sept/2023:
9:00am - 10:30am

Session Chair: Prof. Ferdinando Nunziata
Session Chair: Prof. Junsheng Li
Room: 314 - Continuing Education College (CEC)


57192 - RESCCOME

57979 - MAC-OS


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Presentations
9:00am - 9:45am
Oral
ID: 266 / S.2.1: 1
Oral Presentation
Ocean and Coastal Zones: 57192 - RS of Changing Coastal Marine Environments (Resccome)

Remote Sensing of Changing Coastal Marine Environments – A Midterm Report

Martin Gade1, Merete Badger2, Krystallia Dimitriadou2, Xiaoming Li3, Abdalmenem Owda2, Sebastian Peters1, Simon Schäfers1, Di Zhang1

1Universität Hamburg, Germany; 2Technical University of Denmark, Denmark; 3Aerospace Research Information Institute, Chinese Academy of Sciences, China

Within the joint Sino-European project “Remote Sensing of Changing Coastal Marine Environments” (ReSCCoME) we are developing techniques for the use of Synthetic Aperture Radar (SAR) data for the monitoring of European and Chinese coastal areas. We demonstrate that a classification of sediments on exposed intertidal flats is possible, when complex SAR data acquired at different radar bands is used. Single-band SAR data can already be used to generate Digital Elevation Maps (DEM) through an identification of waterlines at different water levels. Here, two approaches, including a new neural network, are used to are yielding promising results. We further demonstrate that SAR wind fields yield a useful and robust tool to assess the potential of possible future wind farms, and to demonstrate the impact of existing windfarms on their surrounding environment, particularly the deficit in local wind speed.

266-Gade-Martin-Oral_Cn_version.pdf
266-Gade-Martin-Oral_PDF.pdf


9:45am - 10:30am
Oral
ID: 112 / S.2.1: 2
Oral Presentation
Ocean and Coastal Zones: 57979 - Monitoring Harsh Coastal Environments and Ocean Surveillance Using Radar RS (MAC-OS)

Monitoring Harsh Coastal Environments and Ocean Surveillance Using Radar Remote Sensing

Ferdinando Nunziata1, Xiaofeng Yang2

1Universita' di Napoli Parthenope, Italy; 2State Key Laboratory of remote Sensing, ScienceChinese Academy of Science, Beijing

The project aims at exploiting microwave satellite measurements to generate innovative added-value products to observe coastal areas characterized by harsh environments, even under extreme weather conditions. The following added-values products are addressed: water pollution, intertidal area monitoring, ship and metallic target observation, NN methods to retrieve wind direction from SAR imagery.

The following activities have been addressed:

Water pollution

Previous activities: Theoretical scattering models (under monostatic and bistatic configurations) have been developed to predict sea surface scattering with or without surfactants. In the monostatic case, theoretical predictions have been contrasted with actual measurements collected by the Synthetic Aperture Radar.

New activities: A model has been developed to shed light in the prediction of oil-sea contrast using different combinations of scattering (AIEM and two scale BPM) and damping (Marangoni and MLB) models.

Target detection

Previous activities: Multi-polarization backscattering from a known ship observed at different incidence angles. The analysis is carried on using metrics based on both power and phase information.

New activities: A new metric is defined, namely the polarization signature of the degree of polarization, that can be used to better asses the scattering variability at the variance of incidence angle for both sea and targets.

The polSAR backscatter from PAZ imagery acquired over the Robin Riggs wind farm is analysed to estimate blade rotation using sub-aperture analysis

Intertidal area monitoring

New activities: A data set that consists of X-band (CosmoSkyMed and PAZ), L-band (ALOS-2) and C-band (RadarSAT-2 and Sentinel-1) polarimetric SAR scenes has been acquired in the Scottish Solway Firth intertidal area to discuss the variability of the polarimetric scattering against SAR frequency and incidence angle over a common area.

Wind speed

Previous activities: SAR and ancillary scatterometer and model-based information are used to estimate the wind vector from SAR scenes under moderate and extreme weather conditions.

New activities: A new processing chain that exploits NN to estimate wind direction from the SAR imagery is proposed and tested using X-band CosmoSkyMed SAR imagery augmented with ancillary ASCAT and ECMWF info.

All this matter will be detailed in the proposed piece of study.

112-Nunziata-Ferdinando-Oral_Cn_version.pdf
112-Nunziata-Ferdinando-Oral_PDF.pdf


 
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