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Images for Street Christchurch Earthquake Christchurch; more images...

Images, UC QuakeStudies

Damage to buildings along Norwich Quay in Lyttelton. To the left is the Lyttelton Hotel with a crumbled top. Bricks have fallen on the awning and all along the footpath. To the right is a cafe that was damaged severely in the earthquake. The front wall of the top storey has crumbled onto the street, crushing a car. Wire fencing and road cones have been used to create a cordon around the buildings.

Research papers, Lincoln University

The increase in urban population has required cities to rethink their strategies for minimising greenhouse gas impacts and adapting to climate change. While urban design and planning policy have been guided by principles such as walkability (to reduce the dependence on cars) and green infrastructure (to enhance the quality of open spaces to support conservation and human values), there have been conflicting views on what spatial strategies will best prepare cities for a challenging future. Researchers supporting compact cities based upon public Transit Oriented Development have claimed that walkability, higher density and mixed-uses make cities more sustainable (Owen, 2009) and that, while green spaces in cities are necessary, they are dull in comparison with shopfronts and street vendors (Speck, 2012, p 250). Other researchers claim that green infrastructure is fundamental to improving urban sustainability and attracting public space users with improved urban comfort, consequently encouraging walkability (Pitman and Ely, 2013). Landscape architects tend to assume that ‘the greener the better’; however, the efficiency of urban greenery in relation to urban comfort and urbanity depends on its density, distribution and the services provided. Green infrastructure can take many forms (from urban forests to street trees) and provide varied services (amended microclimate, aesthetics, ecology and so forth). In this paper, we evaluate the relevance of current policy in Christchurch regarding both best practice in green infrastructure and urban comfort (Tavares, 2015). We focus on the Christchurch Blueprint for rebuilding the central city, and critically examine the post-earthquake paths the city is following regarding its green and grey infrastructures and the resulting urban environment. We discuss the performance and appropriateness of the current Blueprint in post-earthquake Christchurch, particularly as it relates to the challenges that climate change is creating for cities worldwide.

Images, UC QuakeStudies

A photograph of a sign taped to a window. The sign includes a bullet pointed list of humorous observations about Christchurch following the February 2011 earthquake. The sign reads, "You know you're from Christchurch when: you use the term 'liquefaction' and 'seismic design' in casual conversation; digging a hole and shitting in your garden is no longer weird; your mayor describes the city as munted. If he means FUBARed, you agree; weaving through car size potholes on the street is no longer weird; a shower is heaven; you have a preference of which kind of silt you'd rather shovel, dry or wet; you see tanks...driving around town; you are always noting what you are under; due to frequent aftershocks during the night, you sleep like a baby - every 10 minutes you wake up and shit yourself".

Research papers, The University of Auckland Library

This thesis presents the application of data science techniques, especially machine learning, for the development of seismic damage and loss prediction models for residential buildings. Current post-earthquake building damage evaluation forms are developed for a particular country in mind. The lack of consistency hinders the comparison of building damage between different regions. A new paper form has been developed to address the need for a global universal methodology for post-earthquake building damage assessment. The form was successfully trialled in the street ‘La Morena’ in Mexico City following the 2017 Puebla earthquake. Aside from developing a framework for better input data for performance based earthquake engineering, this project also extended current techniques to derive insights from post-earthquake observations. Machine learning (ML) was applied to seismic damage data of residential buildings in Mexico City following the 2017 Puebla earthquake and in Christchurch following the 2010-2011 Canterbury earthquake sequence (CES). The experience showcased that it is readily possible to develop empirical data only driven models that can successfully identify key damage drivers and hidden underlying correlations without prior engineering knowledge. With adequate maintenance, such models have the potential to be rapidly and easily updated to allow improved damage and loss prediction accuracy and greater ability for models to be generalised. For ML models developed for the key events of the CES, the model trained using data from the 22 February 2011 event generalised the best for loss prediction. This is thought to be because of the large number of instances available for this event and the relatively limited class imbalance between the categories of the target attribute. For the CES, ML highlighted the importance of peak ground acceleration (PGA), building age, building size, liquefaction occurrence, and soil conditions as main factors which affected the losses in residential buildings in Christchurch. ML also highlighted the influence of liquefaction on the buildings losses related to the 22 February 2011 event. Further to the ML model development, the application of post-hoc methodologies was shown to be an effective way to derive insights for ML algorithms that are not intrinsically interpretable. Overall, these provide a basis for the development of ‘greybox’ ML models.

Images, UC QuakeStudies

A yellow sticker on the door of a house in Worcester Street reading, "Restricted use. No entry except on essential business. Warning: This building has been damaged and its structural safety is questionable. Earthquake aftershocks present danger. Enter only at own risk. Subsequent events may result in increased damage and danger, changing this assessment. Reinspection may be required. The damage is as described below: partial collapse of longitudinal walls". Following on from this are the specific conditions that must be complied with to enable entry into the property, the inspector's identification details, and the date and time the building was inspected. At the bottom the form reads, "Do not remove this placard. Placed by order of the territorial authority Christchurch City Council".

Research papers, University of Canterbury Library

Developing a holistic understanding of social, cultural, and economic impacts of disasters can help in building disaster risk knowledge for policy making and planning. Many methods can help in developing an understanding of the impacts of a disaster, including interviews and surveys with people who have experienced disaster, which may be invasive at times and create stress for the participants to relive their experiences. In the past decade, social media, blog posts, video blogs (i.e. “vlogs”), and crowdsourcing mechanisms such as Humanitarian OpenStreetMap and Ushahidi, have become prominent platforms for people to share their experiences and impacts of an event from the ground. These platforms allow for the discovery of a range of impact information, from physical impacts, to social, cultural, and psychological impacts. It can also reveal interesting behavioural information such as their decision to heed a warning or not, as people tend to share their experiences and their reactions online. This information can help researchers and authorities understand both the impacts as well as behavioural responses to hazards, which can then shape how early warning systems are designed and delivered. It can also help to identify gaps in desired behavioural responses. This poster presents a selection of cases identified from the literature and grey literature, such as the Haiti earthquake, the Christchurch earthquake, Hurricane Sandy, and Hurricane Harvey, where online platforms were widely used during and after a disaster to document impacts, experiences, and behavioural responses. A summary of key learnings and areas for future research is provided.