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    Systematic Mapping of Global Research on Disaster Damage Estimation for Buildings: A Machine Learning-Aided Study
    (MDPI (Basel, Switzerland), 2024-06-20) Rajapaksha D; Siriwardana C; Ruparathna R; Maqsood T; Setunge S; Rajapakse L; De Silva S; Witt E; Bilau AA; Sun B
    Research on disaster damage estimation for buildings has gained extensive attention due to the increased number of disastrous events, facilitating risk assessment, the effective integration of disaster resilience measures, and policy development. A systematic mapping study has been conducted, focusing on disaster damage estimation studies to identify trends, relationships, and gaps in this large and exponentially growing subject area. A novel approach using machine learning algorithms to screen, categorise, and map the articles was adopted to mitigate the constraints of manual handling. Out of 8608 articles from major scientific databases, the most relevant 2186 were used in the analysis. These articles were classified based on the hazard, geographical location, damage function properties, and building properties. Key observations reveal an emerging trend in publications, with most studies concentrated in developed and severely disaster-affected countries in America, Europe, and Asia. A significant portion (68%) of the relevant articles focus on earthquakes. However, as the key research opportunities, a notable research gap exists in studies focusing on the African and South American continents despite the significant damage caused by disasters there. Additionally, studies on floods, hurricanes, and tsunamis are minimal compared to those on earthquakes. Further trends and relationships in current studies were analysed to convey insights from the literature, identifying research gaps in terms of hazards, geographical locations, and other relevant parameters. These insights aim to effectively guide future research in disaster damage estimation for buildings.
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    Transition to a low-carbon economy for New Zealand
    (Royal Society of New Zealand, 2016-04) Sims REH; Barton B; Bennet P; Isaacs N; Kerr S; Leaver J; Reisinger A; Stephenson J
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    Cost estimation model for earthquake damage repair in New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Construction at Massey University, Albany, New Zealand
    (Massey University, 2021) Kahandawa Appuhamillage, Ravindu Visal Dharmasena Kahandawa
    Earthquakes are natural hazards that can devastate nations, their people and the surrounding built environments. Designing a suitable strategy for rapid recovery requires an accurate damage assessment process for the built environment. Loss estimation models were developed to predict the cost of repair, but these models were not used to estimate the costs of post-earthquake repair. This could be due to the fact that these probability-based models tend to provide less accurate outputs. In fact, there is no existing literature on post-earthquake repair cost estimation models that can rapidly produce repair cost estimates. This research developed a post-earthquake cost estimation model for earthquake damage repair work (referred to as a cost of damage repair, earthquake estimation model or C-DREEM). The research used an exploratory sequential research design that used semi-structured interviews (N=19) with engineers, quantity surveyors and builders with experience in earthquake damage repair work as the primary data collection. Then a web-based survey questionnaire (N=310 distributed, N=92 received) of professionals with experience in cost estimation for earthquake damage repair work was the second data collection. The collected data was analysed using thematic analysis, descriptive statistics and non-parametric tests. Based on the findings in the literature, document review and research data analysis, a cost of damage repair earthquake estimation model (C-DREEM) was developed. The C-DREEM model was then validated through a focus group interview session with participants who had experience in the cost estimation for earthquake damage repair work in New Zealand (N=9). Key findings identified from the research were: (i) 11 factors have a critical impact on the accuracy of cost estimation of earthquake damage repair work (CEEDRW) which includes consequential damage, initially unforeseen damage, and changes to the final repair state; (ii) Use of a unit rate and lump sum amount methods were some of the most suitable ways incorporate these factors to CEEDRW; (iii) detailed damage evaluation reports are the most likely information sources post-earthquake for CEEDRW; and (iv) the standardised and automated cost estimation model, C-DREEM, developed by this research can improve both pre and post-earthquake CEEDRW process with include the benefits of sharing consequence functions and probable damage information with probability-based methods. The key contribution to knowledge from this research is identifying the factors affecting CEEDRW, evaluating the significance, selecting methods to incorporate the factors into the costing process, and creating the C-DREEM costing process that combines the pre-and post-earthquake loss estimation processes. The research also supports the professional practice by providing: a standardised and automated cost estimation process; specifying the areas that should be improved, such as the damage reporting process; and a better cost control and monitoring process through standardised rates. Through the findings of the research, government and insurance companies: can standardise and improve the accuracy and speed CEEDRW process, and makes informed decisions to manage the impact of the eleven factors affecting CEEDRW identified by this research.