James Hilton, & Nikhil Garg. (2023). Rapid Geospatial Processing for Hazard and Risk Management using the Geostack Framework. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 2–7). Palmerston North, New Zealand: Massey Unversity.
Abstract: Operational predictive and risk modelling of landscape-scale hazards such as floods and fires requires rapid processing of geospatial data, fast model execution and efficient data delivery. However, geospatial data sets required for hazard prediction are usually large, in a variety of different formats and usually require a complex pre-processing toolchain. In this paper we present an overview of the Geostack framework, which has been specifically designed for this task using a newly developed software library. The platform aims to provide a unified interface for spatial and temporal data sets, deliver rapid processing through OpenCL and integrate with web APIs or external graphical user interface systems to display and deliver results. We provide examples of hazard and risk use cases, particularly Spark, a Geostack based system for predicting the spread of wildfires. The framework is open-source and freely available to end users and practitioners in the hazard and geospatial space.
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Ana María Cintora, Eva Teresa Robledo, Cristina Gomez, Raquel Lafuente, Ricardo García, & Cristina Horrillo. (2022). Analysis of the Chemical Incidents from Seveso Directive according to Direct Fatalities and Injuries. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 1058–1067). Tarbes, France.
Abstract: This paper provides a descriptive analysis of the eMARS database, which contains compulsory information on major chemical incidents under the SEVESO Directive. This analysis serves to assess the installations with the highest number of direct fatalities and injuries. At present, the data collected to assess the status of chemical accident risk globally are rather limited. There are some sources of data on chemical accidents in government and industry that might be used to estimate the frequency and severity of some types of events, but they are far from providing a complete perspective that covers all chemical accidents, thus limiting the possibilities of obtaining a more homogeneous picture of the risk of chemical accidents worldwide. Waste storage, treatment and disposal is one of the industrial areas with the highest number of fatalities and injuries, so we must emphasize the importance of this type of industry within the risk maps.
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Yajie Li, Amanda Lee Hughes, & Peter D. Howe. (2018). Communicating Crisis with Persuasion: Examining Official Twitter Messages on Heat Hazards. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 469–479). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Official crisis messages need to be persuasive to promote appropriate public responses. However, little research has examined the content of crisis messages from a persuasion perspective, especially for natural hazards. This study deductively identifies five persuasive message factors (PMFs) applicable to natural hazards, including two under-examined health-related PMFs: health risk susceptibility and health impact. Using 2016 heat hazards as a case study, this paper content-analyzes heat-related Twitter messages (N=904) posted by eighteen U.S. National Weather Service Weather Forecast Offices according to the five PMFs. We find that the use of descriptions of hazard intensity is disproportionately high, with a lack of use of other PMFs. We also describe different types of statements used to signal the two health-related PMFs. We conclude with implications and recommendations relevant to practitioners and researchers in social media crisis communication.
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Zachary Sutherby, & Brian Tomaszewski. (2018). Conceptualizing the Role Geographic Information Capacity has on Quantifying Ecosystem Services under the Framework of Ecological Disaster Risk Reduction (EcoDRR). In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 326–333). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: The use of ecosystems for EcoDRR is a beneficial and a viable option for community stakeholders. For example, ecosystems can mitigate the effects of hazards experienced in anthropogenic communities. Ecosystem services are the underlying reason for this benefit. EcoDRR is the idea of sustainable management, conservation, and restoration of ecosystems to maximize ecosystem services and reduce disaster risks and impacts. The use of geospatial technologies to monitor large-scale ecosystems are often subject to Geographic Information Capacity (GIC), or the ability of ecosystem stakeholders to utilize all existing geographic information, resources, and capacities to monitor ecosystem services. Though these tools are useful, currently there is not a tool that specifically quantifies ecosystem services in the context of DRR. The main contribution of this paper is a conceptual framework intended to quantify ecosystem services in the context of EcoDRR.
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Miles Crawford, Wendy Saunders, Emma Hudson-Doyle, & David Johnston. (2018). End-user perceptions of natural hazard risk modeling across policy-making, land-use planning, and emergency management within New Zealand local government. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 550–560). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: While the development of risk modelling has focussed on improving model accuracy and modeller expertise, less consideration has been given to understanding how risk models are perceived and used by the end-user. In this think-piece, we explore how risk modelling is perceived and used by three different end-user functions for natural hazard risk management in New Zealand local government: policy-making, land-use planning, and emergency management. We find that risk modelling is: valued and used by policy-makers; less valued within land-use planning and not as widely used; and valued within emergency planning but not as widely used. We offer our thoughts as to why this is the case with reference to focus groups and qualitative interviews held with local government natural hazard risk end-users across the Wellington, Hawke's Bay and Gisborne regions of New Zealand. We conclude with recommendations for how risk modelling can be further developed to increase community resilience.
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