Fine-Scale Population Estimation by 3D Reconstruction of Urban Residential Buildings

Fine-scale population estimation is essential in emergency response and epidemiological applications as well as urban planning and management. However, representing populations in heterogeneous urban regions with a finer resolution is a challenge. This study aims to obtain fine-scale population distribution based on 3D reconstruction of urban residential buildings with morphological operations using optical high-resolution (HR) images from the Chinese No. 3 Resources Satellite (ZY-3). Specifically, the research area was first divided into three categories when dasymetric mapping was taken into consideration. The results demonstrate that the morphological building index (MBI) yielded better results than built-up presence index (PanTex) in building detection, and the morphological shadow index (MSI) outperformed color invariant indices (CIIT) in shadow extraction and height retrieval. Building extraction and height retrieval were then combined to reconstruct 3D models and to estimate population. Final results show that this approach is effective in fine-scale population estimation, with a mean relative error of 16.46% and an overall Relative Total Absolute Error (RATE) of 0.158. This study gives significant insights into fine-scale population estimation in complicated urban landscapes, when detailed 3D information of buildings is unavailable.