Publications
Showing 25 results for Author: Taylor R. Hauser
Mar, 2026
Conference Paper
SIGHT: Stacked Integration of Geospatial Hierarchical Typologies for Inferring Building Characteristics
Building characteristics are often absent in building stock datasets, particularly in regions most vulnerable to climate change and requiring effective disaster management strategies. Traditional machine learning approaches, while widely used to predict building attributes, typically neglect the spatial context of the data, leading to less accurate and reliable outcomes. T…
Mar, 2026
Conference Paper
Multivariate Testing of Sampling Techniques to Address Class Imbalance in Building Use Type Classification
This study addresses the challenges inherent in building use type classification, particularly focusing on the issue of class imbalance in the training datasets for machine learning classifiers. We comprehensively analyze the efficacy of various class-balancing sampling techniques. Employing Monte Carlo simulations and Bayesian optimization, we evaluated the performance of…
Mar, 2026
Conference Paper
HumoNet: A Framework for Realistic Modeling and Simulation of Human Mobility Network
Understanding, analyzing, and predicting human mobility and dynamics are valuable to solving pressing problems, developing effective plans, and prescribing timely remedies. As a computational approach, realistic human mobility simulations allow us to understand, analyze, and predict complex systems, including human societies. Accurate simulations rely on (1) the model that…
Mar, 2026
Conference Paper
Empirically Categorizing the Built Environment in Relation to Height
Buildings are a core component of the urban environment and affect human populations, energy usage, city development, city planning, and urban heat islands. Buildings span an enormous range of sizes, from a 2m tall shelter to the Burj Khalifa; and at the same time there are widely recognized categories of similar buildings, with homes, office buildings, or skyscrapers as s…
Mar, 2026
Conference Paper
Leveraging Open-Source Satellite-Derived Building Footprints for Height Inference
At a global scale, cities are growing and characterizing the built environment is essential for deeper understanding of human population patterns, urban development, energy usage, climate change impacts, among others. Buildings are a key component of the built environment and significant progress has been made in recent years to scale building footprint extractions from sa…
Nov, 2025
Journal
Building Morphologies of the USA Structures Database; a Gauntlet Feature Set
In recent years there has been a proliferation of methods and data to extract building footprints from satellite imagery. However there has been very little effort to provide additional insight about these buildings beyond their spatial location and shape. Features derived from their geometries can be used to better characterize these buildings which are critical for furth…