Global Mapping of Three-Dimensional (3D) Urban Structures Reveals Escalating Utilization in the Vertical Dimension and Pronounced Building Space Inequality

Xiaoping Liu,Xinxin Wu,Xuecao Li,Xiaocong Xu,Weilin Liao,Limin Jiao,Zhenzhong Zeng,Guangzhao Chen,Xia Li

Engineering（2024）

Guangdong Key Laboratory for Urbanization and Geo-simulation | College of Land Science and Technology | School of Resource and Environment Science | School of Environmental Science and Engineering | Division of Landscape Architecture | Key Lab of Geographic Information Science (Ministry of Education)

Cited 3|Views49

Abstract

Three-dimensional (3D) urban structures play a critical role in informing climate mitigation strategies aimed at the built environment and facilitating sustainable urban development. Regrettably, there exists a significant gap in detailed and consistent data on 3D building space structures with global coverage due to the challenges inherent in the data collection and model calibration processes. In this study, we constructed a global urban structure dataset (GUS-3D), including building volume, height, and footprint information, at a 500 m spatial resolution using extensive satellite observation products and numerous reference building samples. Our analysis indicated that the total volume of buildings worldwide in 2015 exceeded 1 × 1012 m3. Over the 1985 to 2015 period, we observed a slight increase in the magnitude of 3D building volume growth (i.e., it increased from 166.02 km3 during the 1985–2000 period to 175.08 km3 during the 2000–2015 period), while the expansion magnitudes of the two-dimensional (2D) building footprint (22.51 × 103 km2 vs. 13.29 × 103 km2) and urban extent (157 × 103 km2 vs. 133.8 × 103 km2) notably decreased. This trend highlights the significant increase in intensive vertical utilization of urban land. Furthermore, we identified significant heterogeneity in building space provision and inequality across cities worldwide. This inequality is particularly pronounced in many populous Asian cities, which has been overlooked in previous studies on economic inequality. The GUS-3D dataset shows great potential to deepen our understanding of the urban environment and creates new horizons for numerous 3D urban studies.

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Key words

Three-dimensional (3D),Global mapping,Building volume,Building height,Building space inequality

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