Ylenia Casali, Nazli Yonca Aydin, & Tina Comes. (2021). Zooming into Socio-economic Inequalities: Using Urban Analytics to Track Vulnerabilities – A Case Study of Helsinki. 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. 1028–1041). Blacksburg, VA (USA): Virginia Tech.
Abstract: The Covid19 crisis has highlighted once more that socio-economic inequalities are a main driver of vulnerability. Especially in densely populated urban areas, however, these inequalities can drastically change even within neighbourhoods. To better prepare for urban crises, more granular techniques are needed to assess these vulnerabilities, and identify the main drivers that exacerbate inequality. Machine learning techniques enable us to extract this information from spatially geo-located datasets. In this paper, we present a prototypical study on how Principal Component Analysis (PCA) to analyse the distribution of labour and residential characteristics in the urban area of Helsinki, Finland. The main goals are twofold: 1) identify patterns of socio-economic activities, and 2) study spatial inequalities. Our analyses use a grid of 250x250 meters that covers the whole city of Helsinki, thereby providing a higher granularity than the neighbourhood-scale. The study yields four main findings. First, the descriptive statistical analysis detects inequalities in the labour and residential distributions. Second, relationships between the socio-economic variables exist in the geographic space. Third, the first two Principal Components (PCs) can extract most of the information about the socio-economic dataset. Fourth, the spatial analyses of the PCs identify differences between the Eastern and Western areas of Helsinki, which persist since the 1990s. Future studies will include further datasets related to the distribution of urban services and socio-technical indicators.
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Jingxian Wang, Lida Huang, Guofeng Su, Tao Chen, Chunhui Liu, & Xiaomeng Wang. (2021). UAV and GIS Based Real-time Display System for Forest Fire. 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. 527–535). Blacksburg, VA (USA): Virginia Tech.
Abstract: When a forest fire occurs, the commander cannot obtain information in time, and the rescue command is like groping in the dark. In order to solve the problem, this research establishes a real-time forest fire display system based on UAV and GIS. The UAV is equipped with visible light and thermal imaging cameras to transmit back forest fire scenes in real time. Based on GIS, the system can extract the boundary of the fire field through image processing and 3D modeling technology, and display various forest fire information on the screen. Through image processing and 3D modeling technology, the boundary of the fire field can be extracted and displayed on the screen. We conducted several experiments to test the accuracy and the reliability of the system. The result shows that the accuracy, reliability and real-time capability can be guaranteed in small-scale forest fires.
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Tinghao Zhang, Lida Huang, Tao Chen, & Shuo Bai. (2021). GIS Based Emergency Management Framework for Large-scale Events: A Case Study of the Torch Relay Activity. 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. 503–514). Blacksburg, VA (USA): Virginia Tech.
Abstract: Due to the high popular concentration of large-scale events, once an emergency (like a stampede) occurs, it will often cause severe casualties. Moreover, since the widespread of the COVID-19, the prevention of the novel coronavirus should also be considered during mass gatherings. How to reduce the probability and potential consequence of emergencies is of great significance. This research designs an emergency management framework using ArcGIS-based geographic information technology for large-scale events. To verify the effectiveness of our framework, we take the Winter Olympic torch relay in university as an example. The paper is mainly divided into two parts, emergency resource allocation and the emergency prevention model. The former part focuses on the site selection of emergency sentries and emergency hospitals during the torch relay. In the latter part, an emergency prevention model is designed for two significant emergencies: stampede and epidemic.
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Zeno Franco, Chris Davis, Adina Kalet, Michelle Horng, Johnathan Horng, Christian Hernandez, et al. (2021). Augmenting Google Sheets to Improvise Community COVID-19 Mask Distribution. 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. 359–375). Blacksburg, VA (USA): Virginia Tech.
Abstract: Face mask scarcity in the United States hindered early infection control efforts during the COVID-19 pandemic. Areas with a history of racial segregation and poverty experienced differential COVID-19 death and morbidity rates. Supplying masks equitably and rapidly became an urgent public health priority. A partnership between a local manufacturer with available polypropylene fabric and the Medical College of Wisconsin, which had the capability to assemble and distribute masks, was formed in April, 2020. An improvised logistics framework allowed for rapid distribution more than 250,000 masks, and later facilitated hand-off to other organizations to distribute over 3 million masks. Using an action research framework three phases of the effort are considered, 1) initial deliveries to community clinics, 2) equitable distribution to community agencies while under “safer at home” orders, and 3) depot deliveries and transfer of logistics management as larger agencies recovered. A multi-actor view was used to interrogate the information needs of faculty and staff remotely directing distribution, medical student volunteers delivering masks, and the manufacturer monitorng overall inventory. Logistics information was managed using Google Sheets augmented with a small SQLite component. A phenomenological view, toggling back and forth from the “socio” to the “technical” provides detailed insight into the strengths and limitations of digital solutions for humanitarian logistics, highlighting where paper-based processes remain more efficient. This case study suggests that rather than building bespoke logistics software, supporting relief efforts with non-traditional responders may benefit from extensible components that augment widely used digital tools.
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Boris Petrenj, Mariachiara Piraina, Giada Feletti, Paolo Trucco, Valentina Urbano, & Stefano Gelmi. (2021). Cross-border Information Sharing for Critical Infrastructure Resilience: Requirements and Platform Architecture. 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. 247–259). Blacksburg, VA (USA): Virginia Tech.
Abstract: Resilience of Critical Infrastructures is high on the agenda of countries' efforts. Modern CI highly interdependent and span countries, so disruptions occurring on one side of the border can significantly affect economic and social functions on the other. To build CI resilience, stakeholder organizations must collaborate and exchange information throughout the Emergency Management cycle. In this paper, we present the Critical Infrastructure Platform (PIC in Italian) which is being developed within the SICt project (Resilience of Cross-Border Critical Infrastructure). PIC is a technological piece of a broader cross-border regional resilience strategy between Lombardy Region (Italy) and Canton Ticino (Switzerland) aiming to improve the capacity to manage accidental events involving transportation CI between the two countries. The main goal of the PIC platform is to support secure and effective information-sharing, inter-organizational risk assessment, monitoring and operational coordination under critical situations. The paper presents the key requirements of such ICT system, its high-level architecture including the description of its main modules, main takeaways and future steps.
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