AuthorsK. Ahmad, M. Riegler, K. Pogorelov, P. Halvorsen and F. De Natale
TitleJORD: A System for Collecting Information and Monitoring Natural Disasters by Linking Social Media with Satellite Imagery
AfilliationCommunication Systems
Project(s)Efficient EONS: Execution of Large Workloads on Elastic Heterogeneous Resources
StatusPublished
Publication TypeProceedings, refereed
Year of Publication2017
Conference NameProceedings of the 15th International Workshop on Content-Based Multimedia Indexing - CBMI '17
Pagination12:1--12:6
PublisherACM Press
Place PublishedNew York, USA
ISBN Number9781450353335
Abstract

Gathering information, and continuously monitoring the affected areas after a natural disaster can be crucial to assess the damage, and speed up the recovery process. Satellite imagery is being considered as one of the most productive sources to monitor the after effects of a natural disaster; however, it also comes with a lot of challenges and limitations, due to slow update. It would be beneficiary to link remote sensed data with social media for the damage assessment, and obtaining detailed information about a disaster. The additional information, which are obtainable by social media, can enrich remote-sensed data, and overcome its limitations. To tackle this, we present a system called JORD that is able to autonomously collect social media data about natural disasters, and link it automatically to remote-sensed data. In addition, we demonstrate that queries in local languages that are relevant to the exact position of natural disasters retrieve more accurate information about a disaster event. We also provide content based analysis along with temporal and geo-location based filtering to provide more accurate information to the users. To show the capabilities of the system, we demonstrate that a large number of disaster events can be detected by the system. In addition, we use crowdsourcing to demonstrate the quality of the provided information about the disasters, and usefulness of JORD from potential users point of view.

URLhttp://dl.acm.org/citation.cfm?doid=3095713
DOI10.1145/3095713.3095726
Citation Key25812