Combining Social Media and Authoritative Data for Crisis Mapping: A Case Study of a Wildfire Reaching Croatian City of Split

Abstract

<p><strong>Abstract.</strong> Due to climate changes, wildfire breakouts get more frequent and difficult to control. In the mid-July 2017, the wildfire spread from wildland to the city of Split, the second-largest city in Croatia. This unpredictable spread almost caused the collapse of emergency response systems. Fortunately, a greater tragedy was avoided with the composure of the responsible services and the help of the citizens. The citizens helped in extinguishing the fire and timely provided the significant amount of disaster-related information on different platforms and through social media. In this paper, we address the problem of identifying useful Volunteered Geographic Information (VGI) and georeferenced social media, for improving situation awareness while the wildfire was reaching the Croatian city of Split. Additionally, we combine social media with other external data sources (e. g. Sentinel-2 satellite images) and authoritative data (e.g. Croatian National Protection and Rescue Directorate official data and Public Fire Department of Split data) to establish the geographical relations between the wildfire phenomena and social media messages. In this manner, we seek to leverage the existing knowledge and data about the spatiotemporal characteristics of the Split wildfire in order to improve the identification of useful information from georeferenced social media with other integrated data sources that can be valuable for improving situation awareness in wildfire events.</p>

Decision Support System Development of Wildland Fire: A Systematic Mapping

“…It can also be seen that the distribution was relatively equitable between the two remaining: case study (37.5%) and experiment (26.3%). [29,45,145,181,[190][191][192][193][194][195] It was observed that the most widely used type of DSS continued to be the traditional PDSS (including GIS). Despite technological advances, with the application of AI and Big Data, there is low use of these in the field of forest fires.…”

“…BA[77,86,90,149,172,[180][181][182][183][184][185][186][187][188][189] Big Data[29,45,145,181,[190][191][192][193][194][195] Figure6. Number of studies found versus the problem to be solved.…”

Social Media Data Processing and Analysis by Means of Machine Learning for Rapid Detection, Assessment and Mapping the Impact of Disasters

“…Proposed approach allows to achieve: -very high accuracy of damage assessment and mapping; -scalability of approach for various emergencies and territories; -ability to work with various combinations of data sources; -low dependency on data quality and quantity; -high automatization and assessment speed ( (Leichter A., et al, 2018, Migliaccio F., et al, 2019, Tavra M., et al, 2019).…”