GLObal Building heights for Urban Studies (UT-GLOBUS) for city- and street- scale urban simulations: Development and first applications

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.