Abstract
As climate change continues, wildfire outbreaks are becoming more frequent and more difficult to control. In mid-July 2017, a forest fire spread from the forests to the city of Split in Croatia. This unpredictable spread nearly caused emergency systems to collapse. Fortunately, a major tragedy was avoided due to the composure of the responsible services and the help of citizens. Citizens helped to extinguish the fire and provided a large amount of disaster-related information on various social media platforms in a timely manner. In this paper, we addressed the problem of identifying useful Volunteered Geographic Information (VGI) and georeferenced social media crowdsourcing data to improve situational awareness during the forest fire in the city of Split. In addition, social media data were combined with other external data sources (e.g., Sentinel-2 satellite imagery) and authoritative data to establish geographic relationships between wildfire phenomena and social media messages. This article highlights the importance of using georeferenced social media data and provides a different perspective for disaster management by filling gaps in authoritative data. Analyses from the presented reconstruction of events from multiple sources impact a better understanding of these types of events, knowledge sharing, and insights into crowdsourcing processes that can be incorporated into disaster management.
Highlights
Natural disasters are often unpredictable and can cause significant human and material damage
The results presented could help develop new emergency response capabilities based on combining crowdsourcing, social media, and authoritative data to improve efficiency and analysis for disaster management
The results shown in this paper confirm the usefulness of the concept of combining different crowdsource data sources to support the disaster management system based on crowdsourcing data integration
Summary
Natural disasters are often unpredictable and can cause significant human and material damage. The development of society and technology contributes to a better response to the disaster (Tuladhar et al, 2015). It is necessary to understand that the modern systems of disaster relief and rescue are already very efficient to ensure the disaster’s successful resolution. Crowdsourcing engages communities around the world in emergency response and disaster management for natural hazards: Fires and wildfires (Becken and Hughey, 2013; Daly and Thom, 2016; De Longueville et al, 2009; Nayebi et al, 2017), earthquakes (Alexander, 2014; Han and Wang, 2019; Hewitt, 2014; Xu and Nyerges, 2017; Xu et al, 2013; Zook et al, 2010), and floods (Begg et al, 2015; Bird et al, 2012; Chan, 2015; Copernicus EMS, 2018; Eilander et al, 2016; Hossain, 2020; Merz et al, 2010; Schanze, 2006; Tingsanchali, (2021) 8:10. A variety of theories and practical implementations have been developed, which differ in the following areas: technical background and data collection from social networks (Ryabchenko et al, 2016; Xu et al, 2015), classification of social media messages (Mitigation, Prevention, Response and Recovery) (Xiao et al, 2015), analytical models from various sources such as videos (To et al, 2015), geographic approach to social media analysis to indicate the usefulness of messages (de Albuquerque et al, 2015), real-time data mining tools (Zhong et al, 2016; Zhu et al, 2019) or predictions based on Twitter events belonging to geographic analysis of spatiotemporal Big Data (Shi et al, 2016)
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