Spatial microsimulation is a set of techniques that allow the characteristics of individuals living in a particular area to be approximated, based on a set of 'constraint variables' that are known about the area.
It is thus often used in order to apply insights from 'non-spatial' survey data to small areas. For example, it has been used to predict the location of smokers across a city in order to evaluate the performance of established stop smoking services (Tomintz et al., 2008). In this talk I will give first give an overview of the technique, discussing pros and cons and possible applications in the Netherlands.
Next I will present the ongoing work within the H2020 project Clair City where spatial microsimulation techniques are used (i) to estimate residential energy use, and (ii) in combination with activity-chain models, to predict personal mobility choices. Here I will present some results from a case study of Amsterdam