A new hierarchical analysis framework of building heights: Towards a more intuitive understanding of 3D urban structure

Abstract

Understanding the 3D spatial structure of a city is increasingly essential for addressing various environmental and management issues, surpassing the importance of traditional 2D analysis. However, existing studies neglect the diversity of building height and still lack a clear description of 3D urban structure. This article proposes a new framework to uncover the 3D urban structure. Firstly, kernel density is employed to reveal the hierarchical spatial structure of buildings and the contour tree method is improved to quantitatively measure the spatial diversity and complexity. Then, the 3D urban structure is abstracted by spatial interpolation after feature filtration. Finally, this framework is applied to the central area of Chengdu City, revealing that: (1) Spatial structures of buildings with different heights exhibit significant diversity, location preference, and complexity; and (2) A globally “depression” 3D urban structure with low center—high periphery is obviously identified. This framework provides an effective way to reveal the 3D urban structure in a more intuitive and clearer way from various disordered urban buildings, which can be transferable to other cities and further facilitate sustainable planning and development of cities.