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.
This study analyses the Earthquake Commission’s (EQC) insurance claims database to investigate the influence of seismic intensity and property damage resulting from the Canterbury Earthquake Sequence (CES) on the repair costs and claim settlement duration for residential buildings. Firstly, the ratio of building repair cost to its replacement cost was expressed as a Building Loss Ratio (BLR), which was further extended to Regional Loss Ratio (RLR) for greater Christchurch by multiplying the average of all building loss ratios with the proportion of building stock that lodged an insurance claim. Secondly, the total time required to settle the claim and the time taken to complete each phase of the claim settlement process were obtained. Based on the database, the regional loss ratio for greater Christchurch for three events producing shakings of intensities 6, 7, and 8 on the modified Mercalli intensity scale were 0.013, 0.066, and 0.171, respectively. Furthermore, small (less than NZD15,000), medium (between NZD15,000 and NZD100,000), and large (more than NZD100,000) claims took 0.35-0.55, 1.95-2.45, and 3.35-3.85 years to settle regardless of the building’s construction period and earthquake intensities. The number of claims was also disaggregated by various building characteristics to evaluate their relative contribution to the damage and repair costs.
<b>Ōtautahi-Christchurch faces the future in an enviable position. Compared to other New Zealand cities Christchurch has lower housing costs, less congestion, and a brand-new central city emerging from the rubble of the 2011 earthquakes. ‘Room to Breathe: designing a framework for medium density housing (MDH) in Ōtautahi-Christchurch’ seeks to answer the timely question how can medium density housing assist Ōtautahi-Christchurch to respond to growth in a way that supports a well-functioning urban environment? Using research by design, the argument is made that MDH can be used to support a safe, accessible, and connected urban environment that fosters community, while retaining a level of privacy. This is achieved through designing a neighbourhood concept addressing 3 morphological scales- macro- the city; meso- the neighbourhood; and micro- the home and street. The scales are used to inform a design framework for MDH specific to Ōtautahi-Christchurch, presenting a typological concept that takes full advantage of the benefits higher density living has to offer.</b>
Room to Breathe proposes repurposing underutilised areas surrounding existing mass transit infrastructure to provide a concentrated populous who do not solely rely on private vehicles for transport. By considering all morphological scales Room to Breathe provides one suggestion on how MDH could become accepted as part of a well-functioning urban environment.
In this thesis, focus is given to develop methodologies for rapidly estimating specific components of loss and downtime functions. The thesis proposes methodologies for deriving loss functions by (i) considering individual component performance; (ii) grouping them as per their performance characteristics; and (iii) applying them to similar building usage categories. The degree of variation in building stock and understanding their characteristics are important factors to be considered in the loss estimation methodology and the field surveys carried out to collect data add value to the study. To facilitate developing ‘downtime’ functions, this study investigates two key components of downtime: (i) time delay from post-event damage assessment of properties; and (ii) time delay in settling the insurance claims lodged. In these two areas, this research enables understanding of critical factors that influence certain aspects of downtime and suggests approaches to quantify those factors. By scrutinising the residential damage insurance claims data provided by the Earthquake Commission (EQC) for the 2010- 2011 Canterbury Earthquake Sequence (CES), this work provides insights into various processes of claims settlement, the time taken to complete them and the EQC loss contributions to building stock in Christchurch city and Canterbury region. The study has shown diligence in investigating the EQC insurance claim data obtained from the CES to get new insights and build confidence in the models developed and the results generated. The first stage of this research develops contribution functions (probabilistic relationships between the expected losses for a wide range of building components and the building’s maximum response) for common types of claddings used in New Zealand buildings combining the probabilistic density functions (developed using the quantity of claddings measured from Christchurch buildings), fragility functions (obtained from the published literature) and cost functions (developed based on inputs from builders) through Monte Carlo simulations. From the developed contribution functions, glazing, masonry veneer, monolithic and precast concrete cladding systems are found to incur 50% loss at inter-storey drift levels equal to 0.027, 0.003, 0.005 and 0.011, respectively. Further, the maximum expected cladding loss for glazing, masonry veneer, monolithic, precast concrete cladding systems are found to be 368.2, 331.9, 365.0, and 136.2 NZD per square meter of floor area, respectively. In the second stage of this research, a detailed cost breakdown of typical buildings designed and built for different purposes is conducted. The contributions of structural and non- structural components to the total building cost are compared for buildings of different usages, and based on the similar ratios of non-structural performance group costs to the structural performance group cost, four-building groups are identified; (i) Structural components dominant group: outdoor sports, stadiums, parkings and long-span warehouses, (ii) non- structural drift-sensitive components dominant group: houses, single-storey suburban buildings (all usages), theatres/halls, workshops and clubhouses, (iii) non-structural acceleration- sensitive components dominant group: hospitals, research labs, museums and retail/cold stores, and (iv) apartments, hotels, offices, industrials, indoor sports, classrooms, devotionals and aquariums. By statistically analysing the cost breakdowns, performance group weighting factors are proposed for structural, and acceleration-sensitive and drift-sensitive non-structural components for all four building groups. Thus proposed building usage groupings and corresponding weighting factors facilitate rapid seismic loss estimation of any type of building given the EDPs at storey levels are known. A model for the quantification of post-earthquake inspection duration is developed in the third stage of this research. Herein, phase durations for the three assessment phases (one rapid impact and two rapid building) are computed using the number of buildings needing inspections, the number of engineers involved in inspections and a phase duration coefficient (which considers the median building inspection time, efficiency of engineer and the number of engineers involved in each assessment teams). The proposed model can be used: (i) by national/regional authorities to decide the length of the emergency period following a major earthquake, and estimate the number of engineers required to conduct a post-earthquake inspection within the desired emergency period, and (ii) to quantify the delay due to inspection for the downtime modelling framework. The final stage of this research investigates the repair costs and insurance claim settlement time for damaged residential buildings in the 2010-2011 Canterbury earthquake sequence. Based on the EQC claim settlement process, claims are categorized into three groups; (i) Small Claims: claims less than NZD15,000 which were settled through cash payment, (ii) Medium Claims: claims less than NZD100,000 which were managed through Canterbury Home Repair Programme (CHRP), and (iii) Large Claims: claims above NZD100,000 which were managed by an insurance provider. The regional loss ratio (RLR) for greater Christchurch for three events inducing shakings of approximate seismic intensities 6, 7, and 8 are found to be 0.013, 0.066, and 0.171, respectively. Furthermore, the claim duration (time between an event and the claim lodgement date), assessment duration (time between the claim lodgement day and the most recent assessment day), and repair duration (time between the most recent assessment day and the repair completion day) for the insured residential buildings in the region affected by the Canterbury earthquake sequence is found to be in the range of 0.5-4 weeks, 1.5- 5 months, and 1-3 years, respectively. The results of this phase will provide useful information to earthquake engineering researchers working on seismic risk/loss and insurance modelling.
Hon JUDITH COLLINS to the Prime Minister: Does she stand by all her Government’s statements and actions?
HELEN WHITE to the Minister of Finance: What recent reports has he seen on the New Zealand economy?
Hon PAUL GOLDSMITH to the Minister of Education: Does he stand by all his statements and policies on education?
GINNY ANDERSEN to the Minister of Housing: What recent announcements has she made about the Government’s transitional housing programme?
NICOLA WILLIS to the Minister of Housing: Has the Government kept the commitment made in the 2017 Speech from the Throne to develop a ‘Rent to Own’ scheme; if so, how many families has the scheme helped into houses since then?
ANAHILA KANONGATA'A-SUISUIKI to the Minister for Social Development and Employment: What support has the Ministry of Social Development provided to people and families affected by recent COVID-19 restrictions?
NICOLE McKEE to the Minister of Police: Will Government actions reduce gang crime and gang numbers this year?
IBRAHIM OMER to the Lead Coordination Minister for the Government's Response to the Royal Commission's Report into the Terrorist Attack on the Christchurch Mosques: What recent engagement has there been with the Muslim and other ethnic communities on the Royal Commission of Inquiry into the terrorist attack on Christchurch masjidain?
SIMEON BROWN to the Minister of Police: Does she stand by her commitment to achieve the Striving Towards 1800 New Police initiative; if so, when will she achieve this initiative?
TEANAU TUIONO to the Minister for Economic and Regional Development: What advice, if any, has he received about the upcoming launch in New Zealand of a satellite that includes the “Gunsmoke-J” payload from the United States Army’s Space and Missile Defense Command?
MARJA LUBECK to the Minister for Workplace Relations and Safety: What recent announcements has he made about improving the Holidays Act 2003?
TIM VAN DE MOLEN to the Minister for Building and Construction: How many applications has the Residential Earthquake-Prone Building Financial Assistance Scheme had since its inception in September last year, and how much has been appropriated for the scheme?
A city’s planted trees, the great majority of which are in private gardens, play a fundamental role in shaping a city’s wild ecology, ecosystem functioning, and ecosystem services. However, studying tree diversity across a city’s many thousands of separate private gardens is logistically challenging. After the disastrous 2010–2011 earthquakes in Christchurch, New Zealand, over 7,000 homes were abandoned and a botanical survey of these gardens was contracted by the Government’s Canterbury Earthquake Recovery Authority (CERA) prior to buildings being demolished. This unprecedented access to private gardens across the 443.9 hectares ‘Residential Red Zone’ area of eastern Christchurch is a unique opportunity to explore the composition of trees in private gardens across a large area of a New Zealand city. We analysed these survey data to describe the effects of housing age, socio-economics, human population density, and general soil quality, on tree abundance, species richness, and the proportion of indigenous and exotic species. We found that while most of the tree species were exotic, about half of the individual trees were local native species. There is an increasing realisation of the native tree species values among Christchurch citizens and gardens in more recent areas of housing had a higher proportion of smaller/younger native trees. However, the same sites had proportionately more exotic trees, by species and individuals, amongst their larger planted trees than older areas of housing. The majority of the species, and individuals, of the larger (≥10 cm DBH) trees planted in gardens still tend to be exotic species. In newer suburbs, gardens in wealthy areas had more native trees than gardens from poorer areas, while in older suburbs, poorer areas had more native big trees than wealthy areas. In combination, these describe, in detail unparalleled for at least in New Zealand, how the tree infrastructure of the city varies in space and time. This lays the groundwork for better understanding of how wildlife distribution and abundance, wild plant regeneration, and ecosystem services, are affected by the city’s trees.
