Modelling long-term residential growth using remote sensing data

Claus, working with Citycentric collaborator Rowan Davies, developed an R Shiny-based tool that uses remotely sensed building presence data from 2016 to 2023 to identify and count buildings over time based on footprint and height parameters. In addition to developing the tool and its analytical logic, Claus and Rowan applied it as an input into a long-term growth model for uMngeni Municipality being prepared for the UK FCDO under the Urban Resilience Programme. This work has created a replicable method for tracking spatial growth dynamics in data-constrained environments, with the longer-term objective of making the tool freely deployable across South Africa, particularly in non-metro and traditional authority contexts where spatially disaggregated development data is often limited.