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Research papers, University of Canterbury Library

Smart cities utilise new and innovative technology to improve the function of the city for governments, citizens and businesses. This thesis offers an in-depth discussion on the concept of the smart city and sets the context of smart cities internationally. It also examines how to improve a smart city through public engagement, as well as, how to implement participatory research in a smart city project to improve the level of engagement of citizens in the planning and implementation of smart projects. This thesis shows how to incentivise behaviour change with smart city technology and projects, through increasing participation in the planning and implementation of smart technology in a city. Meaningful data is created through this process of participation for citizens in the city, by engaging the citizens in the creation of the data, therefore the information created through a smart city project is created by and for the citizens themselves. To improve engagement, a city must understand its specific context and its residents. Using Christchurch, New Zealand, and the Christchurch City Council (CCC) Smart City Project as a case study, this research engages CCC stakeholders in the Smart City Project through a series of interviews, and citizens in Christchurch through a survey and focus groups. A thorough literature review has been conducted, to illuminate the different definitions of the smart city in academia, business and governments respectively, and how these definitions vary from one another. It provides details of a carefully selected set of relevant smart cities internationally and will discuss how the Christchurch Earthquake Sequence of 2010 and 2011 has affected the CCC Smart City Project. The research process, alongside the literature review, shows diverse groups of citizens in the city should be acknowledged in this process. The concept of the smart city is redefined to incorporate the context of Christchurch, its citizens and communities. Community perceptions of smart cities in Christchurch consider the post-disaster environment and this event and subsequent rebuild process should be a focus of the smart city project. The research identified that the CCC needs to focus on participatory approaches in the planning and implementation of smart projects, and community organisations in Christchurch offer an opportunity to understand community perspectives on new smart technology and that projects internationally should consider how the context of the city will affect the participation of its residents. This project offers ideas to influence the behaviour change of citizens through a smart city project. Further research should consider other stakeholders, for instance, innovation and technology-focused business in the city, and to fully engage citizens, future research must continue the process of participatory engagement, and target diverse groups in the city, including but not limited to minority groups, older and younger generations, and those with physical and mental disabilities.

Research papers, University of Canterbury Library

This thesis examines the opportunities for young citizens in Christchurch to be engaged in city planning post-disaster. This qualitative study was conducted eight years after the 2010-2011 earthquakes and employed interviews with 18 young people aged between 12-24 years old, 14 of whom were already actively engaged in volunteering or participating in a youth council. It finds that despite having sought out opportunities for youth leadership and advocacy roles post-disaster, young people report frustration that they are excluded from decision-making and public life. These feelings of exclusion were described by young people as political, physical and social. Young people felt politically excluded from decision-making in the city, with some youth reporting that they did not feel listened to by decision-makers or able to make a difference. Physical exclusion was also experienced by the young people I interviewed, who reported that they felt excluded from their city and neighbourhood. This ranged from feeling unwelcome in certain parts of the city due to perceived social stratification, to actual exclusion from newly privatised areas in a post-quake recovery city. Social exclusion was reported by young people in the study in regard to their sense of marginalisation from the wider community, due to structural and social barriers. Among these, they observed a sense of prejudice towards them and other youth due to their age, class and/or ethnicity. The barriers to their participation and inclusion, and their aspirations for Christchurch post-disaster are discussed, as well as the implications of exclusion for young people’s wellbeing and sense of belonging. Results of this study contribute to the literature that challenges the sole focus on children and young peoples’ vulnerability post-disaster, reinforcing their capacity and desire to contribute to the recovery of their city and community (Peek, 2008). This research also challenges the narrative that young people are politically apathetic (Norris, 2004; Nissen, 2017), and adds to our understandings of the way that disasters can concentrate power amongst certain groups, in this case excluding young people generally from decision-making and public life. I conclude with some recommendations for a more robust post-disaster recovery in Christchurch, in ways that are more inclusive of young people and supportive of their wellbeing.

Research papers, University of Canterbury Library

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.

Research papers, University of Canterbury Library

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.