The city of Johannesburg contains over 10 million trees and is often referred to as an urban forest. The intra-urban spatial variability
of the levels of vegetation across Johannesburg’s residential regions has an influence on the urban heat island effect within the city.
Residential areas with high levels of vegetation benefit from cooling due to evapo-transpirative processes and thus exhibit weaker heat
island effects; while their impoverished counterparts are not so fortunate. The urban heat island effect describes a phenomenon where
some urban areas exhibit temperatures that are warmer than that of surrounding areas. The factors influencing the urban heat island
effect include the high density of people and buildings and low levels of vegetative cover within populated urban areas. This paper
describes the remote sensing data sets and the processing techniques employed to study the heat island effect within Johannesburg. In
particular we consider the use of multi-sensorial multi-temporal remote sensing data towards a predictive model, based on the analysis
of influencing factors.