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Taylor Hauser

Geospatial Data Analyst

Contact

865.341.0524 | HAUSERTR@ORNL.GOV

All Publications

2023-2024 Technical Report: Updates to USA Structures
Inferring building height from footprint morphology data
Decoding Ethiopian Abodes: Towards Classifying Buildings by Occupancy Type Using Footprint Morphology
USA Structures Phase 2 Technical Report
A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation
SIGHT: Stacked Integration of Geospatial Hierarchical Typologies for Inferring Building Characteristics...
Multivariate Testing of Sampling Techniques to Address Class Imbalance in Building Use Type Classification...
HumoNet: A Framework for Realistic Modeling and Simulation of Human Mobility Network
A baseline structure inventory with critical attribution for the US and its territories
Empirically Categorizing the Built Environment in Relation to Height
An Environmental Justice Lens for Measuring Neighborhood Scale Vulnerability

Key Links

/news/global-building-height-prediction-made-easy-machine-learning
/news/datasets-assessing-lava-flow-impacts
/news/datasets-supporting-hurricane-damage-assessments

Organizations

National Security Sciences Directorate
Geospatial Science and Human Security Division
Human Dynamics Section
Geospatial Data Modeling

Related News

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Global building height prediction made easy with machine learning

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Deep learning underlies geographic dataset used in hurricane response

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Scientists develop environmental justice lens to identify neighborhoods vulnerable to climate change

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In disaster’s wake, novel computing techniques support emergency responders
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