E2mC: improving emergency management service practice through social media and crowdsourcing analysis in near real time
In the first hours of a disaster, up-to-date information about the area of interest is crucial for effective disaster management. However, due to the delay induced by collecting and analysing satellite imagery, disaster management systems like the Copernicus Emergency Management Service (EMS) are cu...
Gespeichert in:
| Hauptverfasser: | , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2017
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| In: |
Sensors
Year: 2017, Jahrgang: 17, Heft: 12, Pages: 1-32 |
| ISSN: | 1424-8220 |
| DOI: | 10.3390/s17122766 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.3390/s17122766 Verlag, Volltext: http://www.redi-bw.de/db/ebsco.php/search.ebscohost.com/login.aspx%3fdirect%3dtrue%26db%3da9h%26AN%3d126948760%26site%3dehost-live 
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| Verfasserangaben: | Clemens Havas, Bernd Resch, Chiara Francalanci, Barbara Pernici, Gabriele Scalia, Jose Luis Fernandez-Marquez, Tim Van Achte, Gunter Zeug, Maria Rosa (Rosy) Mondardini, Domenico Grandoni, Birgit Kirsch, Milan Kalas, Valerio Lorini, Stefan Rüping |
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| 520 | |a In the first hours of a disaster, up-to-date information about the area of interest is crucial for effective disaster management. However, due to the delay induced by collecting and analysing satellite imagery, disaster management systems like the Copernicus Emergency Management Service (EMS) are currently not able to provide information products until up to 48-72 h after a disaster event has occurred. While satellite imagery is still a valuable source for disaster management, information products can be improved through complementing them with user-generated data like social media posts or crowdsourced data. The advantage of these new kinds of data is that they are continuously produced in a timely fashion because users actively participate throughout an event and share related information. The research project Evolution of Emergency Copernicus services (E2mC) aims to integrate these novel data into a new EMS service component called Witness, which is presented in this paper. Like this, the timeliness and accuracy of geospatial information products provided to civil protection authorities can be improved through leveraging user-generated data. This paper sketches the developed system architecture, describes applicable scenarios and presents several preliminary case studies, providing evidence that the scientific and operational goals have been achieved. | ||
| 650 | 4 | |a 3D reconstruction | |
| 650 | 4 | |a architecture | |
| 650 | 4 | |a COLLECTIVE action | |
| 650 | 4 | |a crowdsourcing | |
| 650 | 4 | |a CROWDSOURCING | |
| 650 | 4 | |a disaster management | |
| 650 | 4 | |a DISTRIBUTED artificial intelligence | |
| 650 | 4 | |a EMERGENCY management | |
| 650 | 4 | |a geolocation | |
| 650 | 4 | |a geospatial analysis | |
| 650 | 4 | |a image classification | |
| 650 | 4 | |a machine learning | |
| 650 | 4 | |a near real time | |
| 650 | 4 | |a REMOTE sensing | |
| 650 | 4 | |a social media | |
| 650 | 4 | |a SOCIAL media | |
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