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Title: At Scale Attribution and Mapping of the Built Environment for Population Dynamics, Climate Security, and Emergency Response
Abstract: Prospects for mapping and attributing the built environment in increasingly greater detail has seen an astonishing rise. In only a handful of years, we have moved from roughly detecting the absence/presence of built-up spaces to easily imagining the routine production of 3D building maps at scale. This is only the beginning with significant investments and new capabilities growth in artificial intelligence, high performance computing, remote sensing, and open data curation frameworks continuing to grow exponentially. Stakeholders across industry, government, and academia are already anticipating how deeper building level attribution will support critical problem solving in energy security, urban mobility, climate resiliency, and emergency response. At this moment, there is an opportunity to develop and position a global building community model in front of what we anticipate will be a decade of exponential growth in demand and capabilities in this space. This presentation will focus on how Oak Ridge National Laboratory, the U.S. Department of Energy's largest open science laboratory is engaging this interdisciplinary opportunity with world class computing facilities, big data, computational intelligence, and partnerships across industry, academia, and government. I begin with a brief overview of the national laboratory mission followed by details of the Global Building Intelligence project, an exemplar case study in interdisciplinary GeoAI modeling at scale.