Unreinforced masonry construction is considered to be the most vulnerable forms of construction as demonstrated through recent earthquakes. In Canada, many densely populated cities such as (Vancouver, Montreal and Ottawa) have large inventories of seismically vulnerable masonry structures. Although measures have been taken to rehabilitate and increase the seismic resistance of important and historic structures, many existing unreinforced masonry structures have not been retrofitted and remain at risk in the event of a large magnitude earthquake. There is therefore a need to identify buildings at risk and develop tools for assessing the seismic vulnerability of existing unreinforced masonry structures in Canada. This thesis presents results from an ongoing research program which forms part of a multi-disciplinary effort between the University of Ottawa’s Hazard Mitigation and Disaster Management Research Centre and the Geological Survey of Canada (NRCAN) to assess the seismic vulnerability of buildings in dense urban areas such as Ottawa, Ontario. A risk-based seismic assessment tool (CanRisk) has been developed to assess the seismic vulnerability of existing unreinforced masonry and reinforced concrete structures. The seismic risk assessment tool exploits the use of fuzzy logic, a soft computing technique, to capture the vagueness and uncertainty within the evaluation of the performance of a given building. In order to conduct seismic risk assessments, a general building inventory and its spatial distribution and variability is required for earthquake loss estimations. The Urban Rapid Assessment Tool (Urban RAT) is designed for the rapid collection of building data in urban centres. This Geographic Information System (GIS) based assessment tool allows for intense data collection and revolutionizes the traditional sidewalk survey approach for collecting building data. The application of CanRisk and the Urban RAT tool to the City of Ottawa is discussed in the following thesis. Data collection of over 13,000 buildings has been obtained including the seismic risk assessment of 1,465 unreinforced masonry buildings. A case study of selected URM buildings located in the City of Ottawa was conducted using CanRisk. Data obtained from the 2011 Christchurch Earthquake in New Zealand was utilized for verification of the tool.

Unreinforced masonry construction is considered to be the most vulnerable forms of construction as demonstrated through recent earthquakes. In Canada, many densely populated cities such as (Vancouver, Montreal and Ottawa) have large inventories of seismically vulnerable masonry structures. Although measures have been taken to rehabilitate and increase the seismic resistance of important and historic structures, many existing unreinforced masonry structures have not been retrofitted and remain at risk in the event of a large magnitude earthquake. There is therefore a need to identify buildings at risk and develop tools for assessing the seismic vulnerability of existing unreinforced masonry structures in Canada. This thesis presents results from an ongoing research program which forms part of a multi-disciplinary effort between the University of Ottawa’s Hazard Mitigation and Disaster Management Research Centre and the Geological Survey of Canada (NRCAN) to assess the seismic vulnerability of buildings in dense urban areas such as Ottawa, Ontario. A risk-based seismic assessment tool (CanRisk) has been developed to assess the seismic vulnerability of existing unreinforced masonry and reinforced concrete structures. The seismic risk assessment tool exploits the use of fuzzy logic, a soft computing technique, to capture the vagueness and uncertainty within the evaluation of the performance of a given building. In order to conduct seismic risk assessments, a general building inventory and its spatial distribution and variability is required for earthquake loss estimations. The Urban Rapid Assessment Tool (Urban RAT) is designed for the rapid collection of building data in urban centres. This Geographic Information System (GIS) based assessment tool allows for intense data collection and revolutionizes the traditional sidewalk survey approach for collecting building data. The application of CanRisk and the Urban RAT tool to the City of Ottawa is discussed in the following thesis. Data collection of over 13,000 buildings has been obtained including the seismic risk assessment of 1,465 unreinforced masonry buildings. A case study of selected URM buildings located in the City of Ottawa was conducted using CanRisk. Data obtained from the 2011 Christchurch Earthquake in New Zealand was utilized for verification of the tool.

Wood-framed buildings have generally performed well during earthquake events, resulting in low fatality levels. However, various degrees of damage is still observed in these buildings during previous earthquakes. Lessons learned from the performance of wood frame construction in these earthquakes is led to an improvement in the design codes and construction practices over the past decades. But, the existing buildings are still vulnerable, since they were designed based on the older codes or constructed using old construction practices. Wood frame construction is the most common construction type in Canada, especially for single family dwellings. Most of these buildings are old, built prior to any modern seismic requirement, and have not been retrofitted against the damaging effects of earthquakes. Therefore, with a number of Canadians living in areas of high or moderate earthquake risk, there is a need to develop tools to assess the seismic vulnerability of the exiting wood-framed buildings in Canada. In the following thesis, a risk-based visual seismic assessment model and a screening tool (CanRisk) is developed, to assess the seismic vulnerability of existing wood frame construction in Canada. The model is dependent on the seismic hazard, building vulnerability, and building importance/exposure, which are integrated using hierarchical fuzzy rule based modeling. In the proposed seismic assessment model, fuzzy logic is used as a computing technique to capture the vagueness and uncertainty of a seismic vulnerability assessment, caused by subjectivity involved in the evaluation process. The hierarchical fuzzy rule based modeling used in this seismic assessment method is implemented in a prototype Matlab based program (CanRisk), which incorporates the Canadian seismic design practice based on the National Building Code of Canada (NBCC) and the Canadian site seismic hazard. A sensitivity analysis is conducted to test and verify the seismic assessment model and investigate the effects of various parameters on the outcome of the assessment. Also, in a case study, selected wood-framed buildings located in the city of Ottawa are evaluated using CanRisk, to demonstrate the applicability of the program.

The process of modeling earthquake hazard risk and vulnerability is a prime component of mitigation planning, but is rife with epistemic, aleatory and factual uncertainty. Reducing uncertainty in such models yields significant benefits, both in terms of extending knowledge and increasing the efficiency and effectiveness of mitigation planning. An accurate description of the built environment as an input into loss estimation would reduce factual uncertainty in the modeling process. Building attributes for earthquake loss estimation and risk assessment modeling were identified. Three modules for developing the building attributes were proposed, including structure classification, building footprint recognition and building valuation. Data from primary sources and field surveys were collected from Shelby County, Tennessee, for calibration and validation of the structure type models and for estimation of various components of building value. Building footprint libraries were generated for implementation of algorithms to programmatically recognize two-dimensional building configurations. The modules were implemented to produce a building inventory for Shelby County, Tennessee that may be used effectively in loss estimation modeling. Validation of the building inventory demonstrates effectively that advanced technologies and methods may be effectively and innovatively applied on combinations of primary and derived data and replicated in order to produce a bottom-up, reliable, accurate and cost-effective building inventory.