Modelling Day and Night-Time Population using a 3D Urban Model

Abstract

Dasymetric methods are commonly used to redistribute or disaggregate (census) population data, using either simple binary or multi-layer models. Most models show limitations in high density built-up areas as they commonly ignore the 3D dimension (meaning buildings height) of multi-story urban environments. For example, simple dasymetric models only allocate the population counts to built-up areas, without considering differences between areas of multi-story and single-story buildings. Furthermore, such models only allow the disaggregation of ‘night-time’ population data, while for many urban applications such as transport, health or hazard, the location of ‘day-time’ population is of interest. This research presents an initial approach to model day and night-time population using as case study an Indian city (Kalyan-Dombivli). For most Indian cities, census population data is only available for wards, while day-time population data is either not available or of very poor quality. Besides census data and ancillary spatial data, this research uses a 3D urban model, extracted from Cartosat stereo-images. First, the extracted height from the stereo-image is used in combination with building footprints to disaggregate census population data at wards to ‘night-time’ population per building. Second, a classification of economically active areas is constructed based on the 3D urban model in combination with other spatial layers (e.g. transport layers) to model the day-time population. The result shows different concentration of population during day and night-time across ward boundaries as well as it confirms the potential of 3D data to disaggregate population data