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Images for christchurch OR future OR heritage; more images...

Images, UC QuakeStudies

A photograph of part of a collaborative drawing on a table at the Pallet Pavilion. The drawing was made during Supernova City, a workshop led by Melbourne-based New Zealand artist and architect Byron Kinnaird. This event was part of FESTA 2013, and invited people to make new, imaginative drawings of Christchurch city.

Images, UC QuakeStudies

An aerial photograph of the Christchurch central city looking over the Tuam and Durham Streets intersection. The photograph has been captioned by BeckerFraserPhotos, "Tuam Street is the most prominent street in this photograph. Durham Street runs across the foreground, and St Michael of all Angels is in the bottom right corner".

Images, UC QuakeStudies

Damage to Englefield Lodge on Fitzgerald Avenue. A pile of bricks lies in front of the house, windows are boarded up, and wooden bracing is propping up the walls. A spray-painted message on a wall reads "We will try to save this house." The photographer comments, "A bike ride around the CBD. Englefield, Christchurch's oldest house, in Fitzgerald Ave".

Images, UC QuakeStudies

A photograph of Nick Sargent (middle) and Melanie Oliver (right) drawing at a table at the Pallet Pavilion during Supernova City, a drawing workshop led by Melbourne-based New Zealand artist and architect Byron Kinnaird. This event was part of FESTA 2013, and invited people to make new, imaginative drawings of Christchurch city.

Research papers, University of Canterbury Library

Overview of SeisFinder SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database. The basic SeisFinder architecture is shown in Figure 1.