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A Coastal Monitoring System Based on Satellite Observation for Ocean and Coast Sustainability

Jacobsen, Sven and Singha, Suman and Li, Xiaoming and Velotto, Domenico and Zeng, Kan (2019) A Coastal Monitoring System Based on Satellite Observation for Ocean and Coast Sustainability. 2019 Dragon 4 Results Symposium, 24.-28. Juni 2019, Ljubljana, Slovenia.

Full text not available from this repository.

Official URL: http://dragon4.esa.int/2019-symp/

Abstract

Nearly ¾ of the world's mega cities are by the sea and almost 80% of the global population live within 100km from the coast. These numbers make very clear that coastal regions worldwide are not only socially important but also economically critical with e.g. harbours, fish farms and exploitation sites for natural resources (oil/gas rigs or offshore wind farms). Moreover the seaside is important for recreational activities and as a natural habitat for local marine life. With respect to the extreme importance of the coastline, constant monitoring of this region is compulsory. Just like the diversity of perspectives in the coastal areas, the diversity of maritime information is complex. Many parameters and layers of information are needed to obtain a comprehensive picture for a given application. Driven by the self-evident advantages of Earth observation methods to monitor large areas while keeping costs at a reasonable level, numerous methods have been developed and improved by the Chinese and German Dragon partners to extract maritime information from satellite-based sensors and will be outlined in the presentation. While most of the information is only available separately, the combination of different information layers is needed to generate a holistic maritime situation awareness. For this an integrated platform is needed to simultaneously visualize and generate a synopsis of different types of information, selected according to the respective application. We present a prototype of a web-based near-real-time information platform to combine information such as sea state, wind information, AIS messages, SAR-based ship detections and sea ice information to obtain a thorough maritime situation awareness. The system can be expanded for oil spill detection and other relevant information and can thus serve as a powerful decision support system for national or international authorities e.g. in catastrophy or disaster management. The platform can help uncover exceptional conditions or behavior and represents an important constituent in sustainable coastal management.

Item URL in elib:https://elib.dlr.de/127194/
Document Type:Conference or Workshop Item (Speech)
Additional Information:Presenting Author: Suman Singha
Title:A Coastal Monitoring System Based on Satellite Observation for Ocean and Coast Sustainability
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Jacobsen, SvenSven.Jacobsen (at) dlr.dehttps://orcid.org/0000-0003-4810-4186
Singha, SumanSuman.Singha (at) dlr.dehttps://orcid.org/0000-0002-1880-6868
Li, XiaomingInstitute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Haidian, Beijing, China;UNSPECIFIED
Velotto, DomenicoDomenico.Velotto (at) dlr.dehttps://orcid.org/0000-0002-8592-0652
Zeng, KanOcean University of China, Qingdao, Shandong, ChinaUNSPECIFIED
Date:June 2019
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Series Name:ESA Special Publications
Status:Published
Keywords:SAR, Oceanography
Event Title:2019 Dragon 4 Results Symposium
Event Location:Ljubljana, Slovenia
Event Type:international Conference
Event Dates:24.-28. Juni 2019
Organizer:European Space Agency (ESA), National Remote Sensing Center of China (NRSCC), Ministry of Economic Development and Technology, Slovenia
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - SAR-Methodology
Location: Bremen , Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Kaps, Ruth
Deposited On:26 Apr 2019 10:42
Last Modified:29 Nov 2019 09:34

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