Projections of future spatiotemporal urban 3D expansion in China under shared socioeconomic pathways

Abstract

The 21st century is marked by urbanization, with global focus on horizontal city expansion. Yet, vertical growth lacks research due to data scarcity. This study investigates the fusion of urban building height predictions with conventional sprawl projections to offer a holistic 3D urban expansion foresight. We constructed a model for projecting urban building volume using socio-economic factors includes GDP, population, and urbanization indicators, enabling the anticipation of China's 2010–2100 building volume demand across five Shared Socioeconomic Pathways (SSPs). Furthermore, deep learning-based neural networks were harnessed for estimating land conversion probabilities and building heights. By aggregating the projected demand, we estimated spatial expansion and building heights for each scenario at ten-year intervals from 2010 to 2100. Compared to other products, our proposed method excels in spatial granularity and temporal continuity, which includes height properties in the 3D structure. According to the projections of this study, considering various SSPs, China's building volume is expected to reach approximately 4500 km3 to 6500 km3 by 2050, representing 1.3–1.9 times increase compared to 2010. Furthermore, forecasts for 2050–2100 anticipate a notable decline to 60 % of the 2050 demand. At a more local level, potential spatial imbalances may arise, as the projections indicate significant urban expansion in the eastern areas and a heightened density of urban land within existing city clusters. This approach surpasses the constraints of 2D analysis, pioneering the prediction of fine-resolution, long-term spatiotemporal urban expansion in China (2010–2100), contributing a model and data support for future sustainable urban development pursuits.