This proposal addresses the Applied Sciences Program goal of integrating Earth science data and information for disaster forecasting, mitigation and response; specifically by delivering EO-derived built environment data and information for use in catastrophe (CAT) models and loss estimation tools. CAT models and loss estimation tools typically use GIS exposure databases to characterize the real-world environment. These datasets are often a source of great uncertainty in the loss estimates, particularly in international events, because the data is incomplete, and sometimes inaccurate and disparate in quality from one region to another. Preliminary research by project team members as part of the Global Earthquake Model (GEM) consortium suggests that a strong relationship exists between the height and volume of built-up areas and EO-derived data products such as Global Rural-Urban Mapping Project-Population (GRUMP), Gridded Population of the World (GPW) and Global Impervious Surface Areas (IMPSA). Applying this knowledge within the framework of a Global Exposure Database (GED) will significantly enhance our ability to quantify building exposure, particularly in developing countries and emerging insurance markets. The project team brings together leaders from the insurance industry, as well as from the Global Earthquake Model (GEM) initiative to assess the commercial viability of these products for assessing risk, particularly in developing countries, and to help develop insurance products that more accurately characterize property and casualty exposure. Global insurance products that have a more comprehensive basis for assessing risk and exposure - as from EO-derived data and information assimilated into CAT models and loss estimation tools - will a) help to transform the way in which we measure, monitor and assess the vulnerability of our communities globally, and in turn, b) help encourage the investments needed especially in the developing world stimulating economic growth and actions that would lead to a more disaster-resilient world.