Building strong, resilient communities: what we learned from the Canterbur…
Research papers, University of Canterbury Library
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This report forms part of a research project examining rural community resilience to natural hazard events, with a particular focus on transient population groups. A preliminary desktop and scoping exercise was undertaken to examine nine communities affected by the Kaikoura earthquake and to identify the variety of transient population groups that are commonly (and increasingly) found in rural New Zealand (see Wilson & Simmons, 2017). From this, four case study communities – Blenheim, Kaikoura, Waiau and St Arnaud – were selected to represent a range of settlement types. These communities varied in respect of social, economic and geographic features, including the presence of particular transient population groups, and earthquake impact. While the 2016 Kaikoura earthquake provided a natural hazard event on which to focus the research, the research interest was in long-term (and broad) community resilience, rather than short-term (and specific) response and recovery actions which occurred post-earthquake.
Creativity that is driven by a need for physical or economic survival, which disasters are likely to inspire, raises the question of whether such creativity fits with conventional theories and perspectives of creativity. In this paper we use the opportunity afforded by the 2010-2013 Christchurch, New Zealand earthquakes to follow and assess the creative practices and responses of a number of groups and individuals. We use in-depth interviews to tease out motivations and read these against a range of theoretical propositions about creativity. In particular, we focus on the construct of “elite panic” and the degree to which this appeared to be evident in the Christchurch earthquakes context. Bureaucratic attempts to control or limit creativity were present but they did not produce a completely blanket dampening effect. Certain individuals and groups seemed to be pre-equipped to navigate or ignore potential blocks to creativity. We argue, using Geir Kaufmann’s novelty-creativity matrix and aspects of Teresa Amabile’s and Michael G. Pratt’s revised componential theory of creativity that a special form of disaster creativity does exist.
Farming and urban regions are impacted by earthquake disasters in different ways, and feature a range of often different recovery requirements. In New Zealand, and elsewhere, most earthquake impact and recovery research is urban focused. This creates a research deficit that can lead to the application of well-researched urban recovery strategies in rural areas to suboptimal effect. To begin to reduce this deficit, in-depth case studies of the earthquake impacts and recovery of three New Zealand farms severely impacted by the 14th November 2016, M7.8 Hurunui-Kaikōura earthquake were conducted. The initial earthquake, its aftershocks and coseismic hazards (e.g., landslides, liquefaction, surface rupture) affected much of North Canterbury, Marlborough and the Wellington area. The three case study farms were chosen to broadly represent the main types of farming and topography in the Hurunui District in North Canterbury. The farms were directly and indirectly impacted by earthquakes and related hazards. On-farm infrastructure (e.g., woolsheds, homesteads) and essential services (e.g., water, power), frequently sourced from distributed networks, were severely impacted. The earthquake occurred after two years of regional drought had already stressed farm systems and farmers to restructuring or breaking point. Cascading interlinked hazards stemming from the earthquakes and coseismic hazards continued to disrupt earthquake recovery over a year after the initial earthquake. Semi-structured interviews with the farmers were conducted nine and fourteen months after the initial earthquake to capture the timeline of on-going impacts and recovery. Analysis of both geological hazard data and interview data resulted in the identification of key factors influencing farm level earthquake impact and recovery. These include pre-existing conditions (e.g., drought); farm-specific variations in recovery timelines; and resilience strategies for farm recovery resources. The earthquake recovery process presented all three farms with opportunities to change their business plans and adapt to mitigate on-going and future risk.
Natural hazard reviews reveal increases in disaster impacts nowhere more pronounced than in coastal settlements. Despite efforts to enhance hazard resilience, the common trend remains to keep producing disaster prone places. This paper explicitly explores hazard versus multi-hazard concepts to illustrate how different conceptualizations can enhance or reduce settlement resilience. Understandings gained were combined with onthe-ground lessons from earthquake and flooding experiences to develop of a novel ‘first cut’ approach for analyzing key multi-hazard interconnections, and to evaluate resilience enhancing opportunities. Traditional disaster resilience efforts often consider different hazard types discretely. However, recent events in Christchurch, a New Zealand city that is part of the 100 Resilient Cities network, highlight the need to analyze the interrelated nature of different hazards, especially for enhancing lifelines system resilience. Our overview of the Christchurch case study demonstrates that seismic, hydrological, shallow-earth, and coastal hazards can be fundamentally interconnected, with catastrophic results where such interconnections go unrecognized. In response, we have begun to develop a simple approach for use by different stakeholders to support resilience planning, pre and post disaster, by: drawing attention to natural and built environment multi-hazard links in general; illustrating a ‘first cut’ tool for uncovering earthquake-flooding multi-hazard links in particular; and providing a basis for reviewing resilience strategy effectiveness in multi-hazard prone environments. This framework has particular application to tectonically active areas exposed to climate-change issues.
The quality of public space is vital to livable cities. Yet livable cities also require empowered communities. This thesis asks: how is the landscape architect’s design expertise expressed as part of the public participation process, what are the key features of design expertise that lead to an effective design-based participation process and how does quality in the participation process relate to the quality of design outcomes? A theoretical framework is developed from which to clarify the relationship between decision-making processes in design and public participation. Insights from design theory are combined with the findings of key informant interviews with New Zealand and Northern Europe design experts, and with landscape architects, community and Council staff working in post-earthquake Ōtautahi/Christchurch, Aotearoa/New Zealand. Results of a case study of Albion Square in Ōhinehou/Lyttelton reveal that the designer’s interactions with the public play a critical role in shaping elegant design outcomes in public space design. Four key insights reveal that participatory design processes in New Zealand need to be reconsidered in order to enable landscape architects to work more closely with communities in mutual learning, rather than the currently limiting technical problem solving process. Institutional, professional and theoretical implications are drawn from the findings.
Land cover change information in urban areas supports decision makers in dealing with public policy planning and resource management. Remote sensing has been demonstrated as an efficient and accurate way to monitor land cover change over large extents. The Canterbury Earthquake Sequence (CES) caused massive damage in Christchurch, New Zealand and resulted in significant land cover change over a short time period. This study combined two types of remote sensing data, aerial imagery (RGB) and LiDAR, as the basis for quantifying land cover change in Christchurch between 2011 – 2015, a period corresponding to the five years immediately following the 22 February 2011 earthquake, which was part of the CES. An object based image analysis (OBIA) approach was adopted to classify the aerial imagery and LiDAR data into seven land cover types (bare land, building, grass, shadow, tree and water). The OBIA approach consisted of two steps, image segmentation and object classification. For the first step, this study used multi-level segmentation to better segment objects. For the second step, the random forest (RF) classifier was used to assign a land cover type to each object defined by the segmentation. Overall classification accuracies for 2011 and 2015 were 94.0% and 94.32%, respectively. Based on the classification result, land cover changes between 2011 and 2015 were then analysed. Significant increases were found in road and tree cover, while the land cover types that decreased were bare land, grass, roof, water. To better understand the reasons for those changes, land cover transitions were calculated. Canopy growth, seasonal differences and forest plantation establishment were the main reasons for tree cover increase. Redevelopment after the earthquake was the main reason for road area growth. By comparing the spatial distribution of these transitions, this study also identified Halswell and Wigram as the fastest developing suburbs in Christchurch. These results provided quantitative information for the effects of CES, with respect to land cover change. They allow for a better understanding for the current land cover status of Christchurch. Among those land cover changes, the significant increase in tree cover aroused particularly interest as urban forests benefit citizens via ecosystem services, including health, social, economic, and environmental benefits. Therefore, this study firstly calculated the percentages of tree cover in Christchurch’s fifteen wards in order to provide a general idea of tree cover change in the city extent. Following this, an automatic individual tree detection and crown delineation (ITCD) was undertaken to determine the feasibility of automated tree counting. The accuracies of the proposed approach ranged between 56.47% and 92.11% in thirty different sample plots, with an overall accuracy of 75.60%. Such varied accuracies were later found to be caused by the fixed tree detection window size and misclassifications from the land cover classification that affected the boundary of the CHM. Due to the large variability in accuracy, tree counting was not undertaken city-wide for both time periods. However, directions for further study for ITCD in Christchurch could be exploring ITCD approaches with variable window size or optimizing the classification approach to focus more on producing highly accurate CHMs.