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Images, eqnz.chch.2010

Clock Tower at old ChCh central Train station (Now movie theatre and science alive activity centre) Cracked.. Badly

Articles, UC QuakeStudies

A post on the NZ Raw blog written by Mark Lincoln on 24 February 2011. Mark says, "I think this is the first post I wrote after the Feb 2011 earthquake. That first photo was my first view after coming out of the office. There's a popular wide panoramic photo that someone took from the Port Hills of all of the dust rising up from the city - the photo in the blog post shows what it looked like from within the dust cloud! There are people gathering further down the street where a building has collapsed".

Research papers, University of Canterbury Library

A significant portion of economic loss from the Canterbury Earthquake sequence in 2010-2011 was attributed to losses to residential buildings. These accounted for approximately $12B of a total $40B economic losses (Horspool, 2016). While a significant amount of research effort has since been aimed at research in the commercial sector, little has been done to reduce the vulnerability of the residential building stock.

Research papers, University of Canterbury Library

The Canterbury Earthquake Sequence (CES), induced extensive damage in residential buildings and led to over NZ$40 billion in total economic losses. Due to the unique insurance setting in New Zealand, up to 80% of the financial losses were insured. Over the CES, the Earthquake Commission (EQC) received more than 412,000 insurance claims for residential buildings. The 4 September 2010 earthquake is the event for which most of the claims have been lodged with more than 138,000 residential claims for this event only. This research project uses EQC claim database to develop a seismic loss prediction model for residential buildings in Christchurch. It uses machine learning to create a procedure capable of highlighting critical features that affected the most buildings loss. A future study of those features enables the generation of insights that can be used by various stakeholders, for example, to better understand the influence of a structural system on the building loss or to select appropriate risk mitigation measures. Previous to the training of the machine learning model, the claim dataset was supplemented with additional data sourced from private and open access databases giving complementary information related to the building characteristics, seismic demand, liquefaction occurrence and soil conditions. This poster presents results of a machine learning model trained on a merged dataset using residential claims from the 4 September 2010.

Images, Alexander Turnbull Library

The cartoon shows three 'Redzone Girls'. The first wears a green tshirt and wears a green 'no restriction' label, the second wears a yellow tshirt and has a yellow 'Limited access' label and the third wears a red tshirt and has a red label that reads 'munted'; she also has a red and white barrier around her. The second and third of the 'girls' are in an increasing state of decrepitude. Behind them is a crumbling brick wall. Context - Christchurch prostitutes aren't letting natural disaster prevent them from plying their trade on the streets despite the dangers of aftershocks in the city. NZPC's Christchurch regional co-ordinator, Anna Reed, said it was a concern sex workers were standing in the shadow of potentially unsafe buildings as the city was shaken by aftershocks, but said the shattered CBD had "left them with no outlet". Christchurch residents are up in arms about the number of prostitutes working in their local neighbourhoods because their usual work areas are out of bounds in the 'red zone'. (Stuff 25 February 2011) Quantity: 1 digital cartoon(s).