Journal Articles

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

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    Destination transitions and resilience following trigger events and transformative moments
    (Taylor and Francis Group, 2024-04-28) Hall CM; Prayag G; Fang SE
    Disasters and crises are increasingly seen as opportunities for transformation of the tourism system at various scales. From a resilience perspective, crises and disasters may act as trigger events for system change, sometimes described as the “disaster-reform hypothesis”. An integrative framework informed by different fields is used to analyse the destination development pathways following the Kaikōura earthquake in New Zealand. In addition to policy documents and media, the study draws on semi-structured interviews with 21 business owners and managers in the Kaikōura region, an internationally recognised ecotourism destination. The findings show pathway competition, experimentation, scale effects and lock-in influencing transitions. The research identifies interactions between different actors at different levels of governance in shaping destination pathways post-disaster, with external political and economic actors having the most influence. Multiple levels of resilience chart a potentially more resilient destination. The study concludes that the range of potential destination pathways is constrained by decision-making at other scales, e.g. national policy settings and insurance coverage, that affect tourism businesses and destination decision-making. As a result, the notion of transformation should be understood as an essentially contested concept both within a destination and between destination stakeholders and those that operate at a national scale.
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    Rapid and Resilient LoRa Leap: A Novel Multi-Hop Architecture for Decentralised Earthquake Early Warning Systems
    (MDPI (Basel, Switzerland), 2024-09-13) Ranasinghe V; Udara N; Mathotaarachchi M; Thenuwara T; Dias D; Prasanna R; Edirisinghe S; Gayan S; Holden C; Punchihewa A; Stephens M; Drummond P; Galmés S; Atakan B
    We introduce a novel LoRa-based multi-hop communication architecture as an alternative to the public internet for earthquake early warning (EEW). We examine its effectiveness in generating a meaningful warning window for the New Zealand-based decentralised EEW sensor network implemented by the CRISiSLab operating with the adapted Propagation of Local Undamped Motion (PLUM)-based earthquake detection and node-level data processing. LoRa, popular for low-power, long-range applications, has the disadvantage of long transmission time for time-critical tasks like EEW. Our network overcomes this limitation by broadcasting EEWs via multiple short hops with a low spreading factor (SF). The network includes end nodes that generate warnings and relay nodes that broadcast them. Benchmarking with simulations against CRISiSLab's EEW system performance with internet connectivity shows that an SF of 8 can disseminate warnings across all the sensors in a 30 km urban area within 2.4 s. This approach is also resilient, with the availability of multiple routes for a message to travel. Our LoRa-based system achieves a 1-6 s warning window, slightly behind the 1.5-6.75 s of the internet-based performance of CRISiSLab's system. Nevertheless, our novel network is effective for timely mental preparation, simple protective actions, and automation. Experiments with Lilygo LoRa32 prototype devices are presented as a practical demonstration.
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    Tsunami or storm deposit? A late Holocene sedimentary record from Swamp Bay, Rangitoto ki te Tonga/D’Urville Island, Aotearoa–New Zealand
    (Taylor and Francis Group, 2023) King DN; Clark K; Chagué C; Li X; Lane E; McFadgen BG; Hippolite J; Meihana P; Wilson B; Dobson J; Geiger P; Robb H; Hikuroa D; Williams S; Morgenstern R; Scheele F
    Informed by Māori oral histories that refer to past catastrophic marine inundations, multi-proxy analysis of stratigraphic records from Swamp Bay, Rangitoto ki te Tonga (D’Urville Island) shows evidence of an anomalous deposit extending some 160 m inland. The deposit includes two distinct lithofacies. The lower sand unit is inferred to have been transported from the marine environment, with corresponding increases in the percentages of benthic marine and brackish–marine diatoms, and geochemical properties indicative of sudden changes in environmental conditions. Radiocarbon dating indicates the deposit formation is less than 402 yrs BP, and pollen indicates it is unlikely to be younger than 1870 CE. Core stratigraphy age models and co-seismic chronologies point to the marine unit most likely being emplaced by tsunami transport associated with rupture of the Wairarapa Fault in 1855 CE. The overlying unit of gravel and silt is inferred to be fluvial deposit and slope-wash from the surrounding hills, loosened by ground-shaking following the earthquake. These findings indicate the 1855 CE earthquake may have been more complex than previously thought and, or, available tsunami modelling does not fully capture the local complexities in bathymetry and topography that can cause hazardous and localized tsunami amplification in embayments like Swamp Bay.
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    A Statistical Model for Earthquake And/Or Rainfall Triggered Landslides
    (Frontiers Media S.A., 2021-02-04) Frigerio Porta G; Bebbington M; Xiao X; Jones G; Xu C
    Natural hazards can be initiated by different types of triggering events. For landslides, the triggering events are predominantly earthquakes and rainfall. However, risk analysis commonly focuses on a single mechanism, without considering possible interactions between the primary triggering events. Spatial modeling of landslide susceptibility (suppressing temporal dependence), or tailoring models to specific areas and events are not sufficient to understand the risk produced by interacting causes. More elaborate models with interactions, capable of capturing direct or indirect triggering of secondary hazards, are required. By discretising space, we create a daily-spatio-temporal hazard model to evaluate the relative and combined effects on landslide triggering due to earthquakes and rainfall. A case study on the Italian region of Emilia-Romagna is presented, which suggests these triggering effects are best modeled as additive. This paper demonstrates how point processes can be used to model the triggering influence of multiple factors in a large real dataset collected from various sources.