"Global Building Heights for Urban Studies (Ut-Globus) for City- and St" by Harsh G. Kamath, Manmeet Singh et al.
 

Abstract

We introduce University of Texas - GLObal Building heights for Urban Studies (UT-GLOBUS), a dataset providing building heights and urban canopy parameters (UCPs) for more than 1200 city or locales worldwide. UT-GLOBUS combines open-source spaceborne altimetry (ICESat-2 and GEDI) and coarse-resolution urban canopy elevation data with a machine-learning model to estimate building-level information. Validation using LiDAR data from six U.S. cities showed UT-GLOBUS-derived building heights had a root mean squared error (RMSE) of 9.1 meters. Validation of mean building heights within 1-km2 grid cells, including data from Hamburg and Sydney, resulted in an RMSE of 7.8 meters. Testing the UCPs in the urban Weather Research and Forecasting (WRF-Urban) model resulted in a significant improvement (55% in RMSE) in intra-urban air temperature representation compared to the existing table-Based local climate zone approach in Houston, TX. Additionally, we demonstrated the dataset's utility for simulating heat mitigation strategies and building energy consumption using WRF-Urban, with test cases in Chicago, IL, and Austin, TX. Street-scale mean radiant temperature simulations using the SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model, incorporating UT-GLOBUS and LiDAR-derived building heights, confirmed the dataset's effectiveness in modeling human thermal comfort in Baltimore, MD (daytime RMSE = 2.85°C). Thus, UT-GLOBUS can be used for modeling urban hazards with significant socioeconomic and biometeorological risks, enabling finer scale urban climate simulations and overcoming previous limitations due to the lack of building information.

Department(s)

Biological Sciences

Publication Status

Open Access

Comments

University of Texas at Austin, Grant NA21OAR4310146

International Standard Serial Number (ISSN)

2052-4463

Document Type

Article - Journal

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2025 The Authors, All rights reserved.

Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Publication Date

01 Dec 2024

PubMed ID

39147835

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