Semantic enrichment of city information models with LiDAR-based rooftop albedo

Abstract

In the era of smart city, semantically rich city information models (CIMs) are demanded as a critical information hub. Roof albedo, a semantic property measures how much solar radiation is reflected, is vital to various urban sustainability topics, including heat island, local climate, green roof, and urban morphology. This paper presents an approach that enriches LiDAR-based albedo to rooftop models for CIM. First, we apply Chen et al. (2018)’s method to the reconstruction of the geometries of rooftop elements. Then, albedos of roofs and rooftop elements are estimated from the mean reflectance in LiDAR data. A pilot study was conducted in an urban area in Hong Kong. The results showed that the building models created by the presented approach were satisfactory in terms of rooftop elements and roof albedos. The results from the present approach can provide sustainability study the details of 3D geometries and albedos in an urban area.