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.
This paper takes Harbin city as an example, on remote sensing data of 2004, 2006, 2007, and 2010, reflect city land surface temperature. Through the distance calculation, the heat island intensity distribution map in Harbin city was different in different seasons, and then analyzes Harbin urban heat island effect characteristics to explore the distribution and variation.
Data and techniques for studying the urban heat island effect in Johannesburg