NH033
Progress, Ethics and Accuracy in Building Stock Attribution.
Session ID#: 252032
Session Description:
We continue our multi-year environment series under AGU theme, "Science Connects." Understanding urban dynamics (such as mobility, energy, security, and resilience) requires interdisciplinary collaboration. Buildings certainly serve as a "stage" for human connection and interaction, necessitating representations at various spatial scales. Advancements in earth observation, computing ecosystems, and AI are enabling urban analysis at finer scales, even down to the building level. For example, building footprints from Microsoft, Google, OpenStreetMap, and others have collectively achieved near-global 2D mapping, while progress in building height estimation are beginning to produce 2.5D mappings. Already, research attributing 2.5D buildings with estimates of floor count, purpose, structure, and materials is underway. This progress certainly supports fine-scale analysis and emerging digital twin capabilities. It also raises concerns about privacy and the risks of inaccurate attribution. We invite papers on technical advances, privacy, domain applications, as well as vision or way forward papers.
Co-Sponsor(s):
Index Terms:
4314 Mathematical and computer modeling [NATURAL HAZARDS]
4319 Spatial modeling [NATURAL HAZARDS]
4325 Megacities and urban environment [NATURAL HAZARDS]
4326 Exposure [NATURAL HAZARDS]
Primary Convener: Charles K Huyck, ImageCat, Inc., Hillsborough, United States
Conveners: Robert Stewart, Oak Ridge National Laboratory, Geographic Data Science, Oak Ridge, TN, United States, Douglas Bausch, Federal Emergency Management Agency, Washington, D.C., United States and Jibonananda Sanyal, Oak Ridge National Laboratory, Computational Urban Sciences Group, Oak Ridge, United States
Creating an IN-CORE Building Inventory by leveraging the NSI Dataset (1880659)
Yong Wook Wook Kim1, Dylan Sanderson2, Chris Navarro1, Rob Kooper3, Jong Lee1, Chen Wang1 and Rashmil Panchani4, (1)University of Illinois at Urbana Champaign, National Center for Supercomputing Applications, Urbana, United States, (2)Oregon State University, Corvallis, OR, United States, (3)National Center for Super Computing Applications, Urbana, United States, (4)University of Illinois, National Center for Supercomputing and Applications, Urana, United States
Toward a Statistically Representative Global Sample of Labeled Buildings: Challenges and Early Insights (1911167)
Jesse Piburn1, Jason Kaufman2, Brandyn Reynolds2, Pranav Sankhe2, Jessica Moehl3 and Daniel Adams4, (1)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (2)Oak Ridge National Laboratory, Oak Ridge, United States, (3)Oak Ridge National Laboratory, GSHS, Geoinformatics Engineering, Oak Ridge, United States, (4)Oak Ridge National Laboratory, GSHS, Human Geography, Oak Ridge, United States
Learning to Impute Missing Building Attributes with Expert-Guided Graph Autoencoders (1917633)
Pranav Sankhe1, Jesse Piburn1, Robert Stewart2 and Justin Jacobs3, (1)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (2)Oak Ridge National Laboratory, Geographic Data Science, Oak Ridge, TN, United States, (3)Oak Ridge National Laboratory, Oak Ridge, United States
A Data-Driven Probabilistic Approach to Regional Dynamics of Building Exposure and Physical Vulnerability Towards Global Disaster Risk Quantification Audit (1944928)
Joshua Dimasaka, MS, MA, MRes1, Fouad Bendimerad2, Renan Ma. Tanhueco3, Robert Muir-Wood4, Christian Geiẞ5 and Emily So1, (1)University of Cambridge, Cambridge University Centre for Risk in the Built Environment (CURBE), Department of Architecture, Cambridge, United Kingdom, (2)Earthquakes and Megacities Initiative, Quezon City, Philippines, (3)Earthquakes and Megacities Initiative, De La Salle University, Quezon City, Philippines, (4)Moody's Risk Management Solutions, London, United Kingdom, (5)German Aerospace Center, Georisks & Civil Security, German Remote Sensing Data Center, Earth Observation Center, Weßling, Germany
Improving accessibility to building stock inventories across the nation through the National Structure Inventory API v2.0 (1953232)
William Lehman, US Army Corps of Engineers, Jacksonville, FL, United States, Lutz, Nicholas J, USACE Hydrologic Engineering Center, Water Resources Systems Division, Davis, United States, Randal Goss, USACE-ERDC CRREL, Remote Sensing, Jacksonville, United States and Randal S Goss
Global Gridded Built Environment Characterization Using a Scalable Intelligent System Based on Morphological Profiles (1967408)
Daniel Adams1, Clinton Stipek2, Andrew Zimmer3, Jessica Moehl4, Robert Stewart5 and Marie Urban1, (1)Oak Ridge National Laboratory, GSHS, Human Geography, Oak Ridge, United States, (2)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (3)Oak Ridge National Laboratory, GSHS, Human Geography, Oak Ridge, TN, United States, (4)Oak Ridge National Laboratory, GSHS, Geoinformatics Engineering, Oak Ridge, United States, (5)Oak Ridge National Laboratory, Geographic Data Science, Oak Ridge, TN, United States
Advancing Access to Site-Specific Building Data for Multi-Hazard Risk Assessment (1977717)
Douglas Bausch, NiyamIT Inc., Makawao, United States, Ashley Hoke, Niyam IT Inc., Denver, United States and Troy Schmidt, FEMA/Niyam IT, Hazus, Fairfax, United States
