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

Clemens Havas,Chiara Francalanci,Domenico Grandoni,Barbara Pernici,Stefan Rüping,Bernd Resch,Tim Van Achte,Maria Mondardini,Birgit Kirsch,Gunter Zeug,Gabriele Scalia,Jose Fernandez-Marquez,Valerio Lorini,Milan Kalas

doi:10.3390/s17122766

Abstract

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.

Highlights

The Copernicus Emergency Management Service (EMS) was established in 2012 to provide information for disaster management in the four phases of the disaster management cycle: mitigation, preparedness, response and recovery
The crisis maps based on satellite information suffer from quality limitations concerning spatial, spectral and temporal resolution, analysis techniques for damage assessment, usability and costs for high spatial resolution data [4]
This paper proposes an infrastructure to exploit social media analysis and crowdsourcing capabilities to generate information layers that are relevant to disaster management in near real time

Summary

Introduction

The Copernicus Emergency Management Service (EMS) was established in 2012 to provide information for disaster management in the four phases of the disaster management cycle: mitigation, preparedness, response and recovery. They provide accurate map products based on satellite imagery and monitor and forecast natural disasters like floods or forest fires. Due to the delay in collecting and analysing satellite imagery, the information requested by EMS users can often be provided until up to 48–72 h after a disaster has occurred. The reasons for this temporal lag are either satellite tasking and orbital constraints, or weather conditions preventing the collection of optical images [3]. The thematic accuracy of optical satellite-based damage assessment after an earthquake is approximately 65% [5] and that of synthetic aperture radar satellite-based damage assessment after a flood is around 75% [6]. These figures can be significantly lower in urban or vegetated areas

Results

Discussion

Conclusion