Lucas Dorigueto, Carlos Brumatti, Erick Figueiredo, & Jugurta Lisboa-Filho. (2021). A Framework for Landslide Information Management Systems Development. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 515–526). Blacksburg, VA (USA): Virginia Tech.
Abstract: Volunteered Geographic Information (VGI) integrated with Disaster Information Management Systems (DIMS) has great potential to assist managers and the community in times of emergency. However, there is little research focusing on integrating VGI with DIMS, in addition, there are a lack of use of standards of interoperability and emergency, which can impair interoperability and the quality of the information contained in these systems. This work presents a fully interoperable framework aimed at the construction of DIMS, which integrates official data and VGI through ISO and OGC standards, allowing managers and the community to work with official data and VGI in order to assist managers in decision making. To show the viability of the framework, a case study using data from the risk situation of dams located in the municipality of Barão de Cocais in Brazil was carried out.
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Rob Grace. (2020). Hyperlocal Toponym Usage in Storm-Related Social Media. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 849–859). Blacksburg, VA (USA): Virginia Tech.
Abstract: Crisis responders need to locate events reported in social media messages that typically lack geographic metadata such as geotags. Toponyms, places names referenced in messages, provide another source of geographic information, however, the availability and granularity of toponyms in crisis social media remain poorly understood. This study examines toponym usage and granularity across six categories of crisis-related information posted on Twitter during a severe storm. Findings show users often include geographic information in messages describing local and remote storm events but do so rarely when discussing other topics, more often use toponyms than geotags when describing local events, and tend to include fine-grained toponyms in reports of infrastructure damage and service disruption and course-grained toponyms in other kinds of storm-related messages. These findings present requirements for hyperlocal geoparsing techniques and suggest that social media monitoring presents more immediate affordances for course-grained damage assessment than fine-grained situational awareness during a crisis.
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Samuel Lee Toepke. (2018). Leveraging Elasticsearch and Botometer to Explore Volunteered Geographic Information. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 663–676). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In the past year, numerous weather-related disasters have continued to display the critical importance of crisis management and response. Volunteered geographic information (VGI) has been previously shown to provide illumination during all parts of the disaster timeline. Alas, for a geospatial area, the amount of data provided can cause information overload, and be difficult to process/visualize. This work presents a set of open-source tools that can be easily configured, deployed and maintained, to leverage data from Twitter's streaming service. The user interface presents data in near real-time, and allows for dynamic queries, visualizations, maps and dashboards. Another VGI challenge is quantifying trustworthiness of the data. The presented work shows integration of a Twitter-bot assessment service, which uses several heuristics to determine the bot-ness of a Twitter account. Architecture is described, Twitter data from a major metropolitan area is explored using the tools, and conclusions/follow-on work are discussed.
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Lívia Castro Degrossi, João Porto de Albuquerque, Roberto dos Santos Rocha, & Alexander Zipf. (2017). A Framework of Quality Assessment Methods for Crowdsourced Geographic Information: a Systematic Literature Review. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 532–545). Albi, France: Iscram.
Abstract: Crowdsourced Geographic Information (CGI) has emerged as a potential source of geographic information in different application domains. Despite the advantages associated with it, this information lacks quality assurance, since it is provided by different people. Therefore, several authors have started investigating different methods to assess the quality of CGI. Some of the existing methods have been summarized in different classification scheme. However, there is not an overview of the methods employed to assess the quality of CGI in the absence of authoritative data. On the basis of a systematic literature review, we found 13 methods that can be employed to this end.
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Stathis G. Arapostathis. (2019). Instagrammers report about the deadly wildfires of East Attica, 2018, Greece: An introductory analytic assessment for disaster management purposes. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: This article contributes to identifying the capabilities of Instagram when utilized as a source of Volunteered
Geographic Information (VGI) for disaster management (DM) purposes. The geographic focus of this research is
in the Mediterranean area. As case study, the fire event of East Attica 2018, Greece, was chosen. This major fire
occurred on the 23rd of July 2018 and caused the death of 100 people, the injury of additional 164 while the total
burnt area was about 1275,9ha. It is the deadliest in modern Greece?s history and the second deadliest at a global
level, within the 21st century. About 15000 related photos along with the corresponding captions and timestamps
were crawled from Instagram. An initial sample of about 1100, was analyzed, by using a certain methodology
divided in certain steps, the most important of which include the classification of the information to certain
categories, geo-referencing and the creation of graphs and maps that visualize the processed data.
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