This paper exhibits methodologies for optimising municipal revenues within the confines of existing
tax systems and revenue instruments, and for the testing of urban planning proposals aimed at uplifting
the plight of the urban poor in South Africa. These methodologies employ quantitative and spatial
modelling techniques and a wealth of datasets readily available to cities, without the need for costly,
primary research.
Results indicate that cities in South Africa have significant scope for optimising their revenues without
changing the tax system, introducing new revenue instruments or raising rates and taxes. This is possible
through spatial overlays to locate properties not registered on the billing system, to identify incorrect
billing relative to land use and to locate high value outstanding debtors.

The paper also demonstrates that planning for alleviation of urban poverty and the optimal functioning
of cities based on accepted theory or winning recipes in different contexts are likely to entrench or even
aggravate the very negative effects that planning wishes to eradicate, and in almost all cases will drain
city coffers.
It then proceeds to offer a number of techniques and case studies demonstrating how urban planning
problems and proposed solutions can be identified, assessed and refined. These include the
identification and ranking of urban nodes, the identification of high-value investment areas and
employment opportunities in city spaces, the testing of spatial development proposals and the
development of spatially-based capital investment frameworks.