E2mC: Improving Emergency Management Service Practice through Social Media and Crowdsourcing Analysis in Near Real Time

Sensors

Maria Rosa (Rosy) Mondardini¹  Jose Luis Fernandez-Marquez¹  Chiara Francalanci²  Barbara Pernici²  Gabriele Scalia²  Clemens Havas³  Bernd Resch³  Stefan Rüping⁴  Birgit Kirsch⁴  Valerio Lorini⁵  Milan Kalas⁵  Tim Van Achte⁶  Gunter Zeug⁷  Domenico Grandoni⁸ 

[1] Citizen Cyberlab, Centre Universitaire d’Informatique (CUI), University of Geneva, route de Drize CH-1227 Carouge, Switzerland;Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20131 Milano, Italy;Department of Geoinformatics–Z_GIS, University of Salzburg, Schillerstrasse 30, 5020 Salzburg, Austria;Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven, 53757 Sankt Augustin, Germany;KAJO s. r. o., Sladkovicova 228/8, 01401 Bytca, Slovakia;PM Risk Crisis Change, K. M. Hendrikaplein 57, 9000 Ghent, Belgium;Terranea, Bahnhofstr. 120, 82269 Geltendorf, Germany;e-GEOS S.p.A, Via Tiburtina 965, 00156, Rome, Italy;

关键词: social media;    crowdsourcing;    geospatial analysis;    machine learning;    image classification;    geolocation;    3D reconstruction;    architecture;    disaster management;    near real time;   

DOI  :  10.3390/s17122766

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown