Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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Author: search.filters.author.Tan MLSubject: search.filters.subject.citizen science

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    Using citizen data to understand earthquake impacts: Aotearoa New Zealand’s earthquake Felt Reports
    (Massey University, 2021-12) Goded T; Tan ML; Becker JS; Horspool N; Canessa S; Huso R; Jonathan H; Johnston D
    Aotearoa New Zealand's national seismic network, GeoNet, administers Felt Reports, including the Felt RAPID and Felt Detailed databases, which are being collected at present. NZ has a long tradition of using earthquake Felt Reports provided by the public to analyse the damage caused by moderate to large earthquakes. From traditional paper-based Felt Reports to current online reports (using the GeoNet website or a mobile app), researchers have been using such data to obtain a geographical distribution of the damage caused by an earthquake and to assess what actions people take during shaking. Felt Reports include questions on people's reactions, indoor and outdoor effects of earthquake shaking, building damage, and tsunami evacuation. The database of long online Felt Reports (Felt Classic between 2004 and 2016 and Felt Detailed from 2016 to the present) comprises over 930,000 reports from more than 30,000 earthquakes. Current research being carried out using this data includes: 1) updating of the NZ Ground Motion to Intensity Conversion Equation and Intensity Prediction Equation, 2) understanding human behaviour for earthquakes and related hazards such as tsunami, 3) developing a predictive model of human behaviour in earthquakes to estimate injuries and fatalities, and 4) improving public education. This paper summarises the history of NZ earthquake Felt Reports as well as the research currently being carried out using this data. Finally, we discuss how citizen science helps in the understanding of earthquake impacts and contributes to the aim of improving Aotearoa New Zealand's resilience to future events.
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    “Saving Precious Seconds”—A Novel Approach to Implementing a Low-Cost Earthquake Early Warning System with Node-Level Detection and Alert Generation
    (MDPI (Basel, Switzerland), 8/03/2022) Prasanna R; Chandrakumar C; Nandana R; Holden C; Punchihewa A; Becker JS; Jeong S; Liyanage N; Ravishan D; Sampath R; Tan ML
    This paper presents findings from ongoing research that explores the ability to use Micro-Electromechanical Systems (MEMS)-based technologies and various digital communication protocols for earthquake early warning (EEW). The paper proposes a step-by-step guide to developing a unique EEW network architecture driven by a Software-Defined Wide Area Network (SD-WAN)-based hole-punching technology consisting of MEMS-based, low-cost accelerometers hosted by the general public. In contrast with most centralised cloud-based approaches, a node-level decentralised data-processing is used to generate warnings with the support of a modified Propagation of Local Undamped Motion (PLUM)-based EEW algorithm. With several hypothetical earthquake scenarios, experiments were conducted to evaluate the system latencies of the proposed decentralised EEW architecture and its performance was compared with traditional centralised EEW architecture. The results from sixty simulations show that the SD-WAN-based hole-punching architecture supported by the Transmission Control Protocol (TCP) creates the optimum alerting conditions. Furthermore, the results provide clear evidence to show that the decentralised EEW system architecture can outperform the centralised EEW architecture and can save valuable seconds when generating EEW, leading to a longer warning time for the end-user. This paper contributes to the EEW literature by proposing a novel EEW network architecture.
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    Citizen science initiatives in high-impact weather and disaster risk reduction
    (Massey University, 20/12/2021) Vinnell LJ; Becker JS; Scolobig A; Johnston DM; Tan ML; McLaren L
    High-impact weather events cause considerable social and economic harm, with these effects likely to increase as climate change drives extremes and population growth leads to commensurate growth in exposure. As part of the World Meteorological Organization’s World Weather Research Programme, the 10-year High-Impact Weather (HIWeather) Project facilitates global cooperation and collaboration to improve weather prediction, forecasting, and warning. As part of this, the HIWeather Citizen Science Project identifies and promotes activities which involve citizens in the warning value chain, from “sensors” where they passively provide data, through to “collaborators” where they are involved in designing, running, interpreting, and applying the research. As well as benefitting global efforts to reduce societal impacts of weather and other natural hazards, citizen science also encourages hazard awareness and scientific literacy and interest. This editorial introduces the HIWeather Citizen Science Project special issue, summarizing the three papers in this issue in the broader context of high-impact weather and citizen science.