Data Screening and Synthesis to Develop High-Resolution Building Inventories for Regional Risk Assessment

High-fidelity regional simulations of the impact of natural hazards on the built environment can be used to support disaster risk management and guide mitigation priorities. These assessments are underpinned by building inventories. Historically, building inventory development has primarily been driven by insurance companies and government agencies, typically targeting aggregate risk and impact measures. The growing feasibility of modeling impacts beyond aggregate loss and the growing interest in regional risk studies from a broad range of stakeholders are creating a need for detailed footprint-level building inventories. Current research studies often use varied data sources to describe the building inventory or use variable single-use methods to synthesize multiple datasets; however, few have assessed the impact of these inventory development decisions or the variability of the results. This study presents 1) a systematic framework for creating footprint-level building inventories through the synthesis of multiple data sources, 2) specific implementation methods for various data types, and 3) a quantitative evaluation of how inventory development decisions impact the resulting inventory makeup and quality for a case study city. Results show that the choice of input data sources and synthesis methods can lead to substantial differences in the resulting inventory. Furthermore, these differences are geospatially clustered and concentrate in certain types of buildings, which can lead to significant biases in the results. These findings underscore the need for more systematic and standardized approaches to building inventory development for regional natural hazard risk assessments.