City-wide building height determination using light detection and ranging data

• Published in: Environment and planning. B, Urban analytics and city science Urban analytics and city science, 2019-11, Vol.46 (9), p.1741-1755
• Main Authors: Wu, Yue, Blunden, Luke S, Bahaj, AbuBakr S
• Format: Article
• Language: English
• ISSN: 2399-8083; 2399-8091
• DOI: 10.1177/2399808318774336

The research presented in this paper addresses a current gap in the availability of building geometry data and provides estimates of individual building characteristics at city scale. Such data are crucial for a wide range of subjects such as modelling building energy consumption as well as regional housing market studies. However, such data are currently not available in the UK. In this work, a new approach was developed to automatically estimate the geometric characteristics of buildings, including height and floor count. A wide range of datasets have been brought together including high-resolution light detection and ranging data to accurately estimate building elevation and to obtain the external dimension of buildings. In the UK, most of the datasets required for this model are available for urban areas, allowing the model to be widely applied both in cities and beyond. The paper presents the results of building height and floor count determined from this model and compares these with the actual data obtained from a survey of 108 representative buildings in the city of Southampton. The results show good accuracy of the model with 97% of the estimates having an error under ±1 floor and an absolute mean error of 0.3 floors. These results provide confidence in utilising this model for future building studies at a city scale.