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

Abstract

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.

Geographic Information Systems for Facilitating Audits of the Urban Built Environment

“…Nevertheless, the number of floors were accurately estimated for the majority of the buildings in the case study (57%), and for the rest with accuracy of ±1 floors, which is considered acceptable for a large-scale analysis [52]. The building height and the number of floors can also be determined using other methods, including light detection and ranging data with high resolution [59].…”

Advancing Urban Building Energy Modeling: Building Energy Simulations for Three Commercial Building Stocks through Archetype Development

“…Another important geometric parameter for building energy simulation is the elevation, or building height, which is not embedded in GIS data in many cities, including Pittsburgh. Though the average floor height was used in several UBEM studies (e.g., [30]), it may affect the accuracy of the models [61]. We used a similar process to determine the building height as in [45], but we provide more specific information herein.…”

Space Ratio: A Measure of Density Potentials in the Built Environment

“…Ordnance Survey deploy Light Detection and Ranging (LiDAR) to calculate the height of buildings. To obtain the measurements, a Digital Terrain Model was derived from a Digital Surface Model by way of interpolation (Wu et al, 2018) and a dataset detailing property extents. As Wu et al (2018Wu et al ( , p.1742) state, LiDAR surveys that utilise interpolation can contain errors derived from the inclusion of non-manmade objects.…”

“…To obtain the measurements, a Digital Terrain Model was derived from a Digital Surface Model by way of interpolation (Wu et al, 2018) and a dataset detailing property extents. As Wu et al (2018Wu et al ( , p.1742) state, LiDAR surveys that utilise interpolation can contain errors derived from the inclusion of non-manmade objects. There is a severe lack of good-quality data on density in the UK (Orford, 2010), which somewhat hinders the spatial analysis of upward densification at area-level.…”