Assessing the intraurban differences in vegetation coverage and surface climate in a heterogeneous area

Abstract

Urban trees play a critical role in alleviating land surface temperatures in cities. In remote sensing studies, vegetation indices are widely used to examine the relationship between Land Surface Temperature (LST) and vegetation cover. The vegetation cover can be measured using the Normalised Difference Vegetation Index (NDVI). In this study, the LST-NDVI relationship was assessed in each of the seven city-regions (A-G) in Johannesburg using Moderate-Resolution Imaging Spectroradiometer (MODIS) datasets to provide a basis for urban ecological planning and environmental protection. This study's specific objective was to determine the intraurban differences in vegetation coverage and LST in the seven city-regions over 19 years. The relationship between LST and NDVI was also examined over the years of study. The results showed a significant intraurban difference in LST and NDVI values in the city-regions with a negative correlation between them, ranging from −0.03 to −0.76. The LST values increased in all the city-regions with the highest value of 20.1°C in city-region G, followed by 19.6°C in city-region E. The vegetation cover decreased over the years, with the lowest NDVI value in city-region G (0.39), followed by city-regions F (0.43) and D (0.48). The city-regions with high LST and low vegetation cover include the city-centre and highly populated suburbs. This indicates that areas with greater vegetation cover have low LSTs and vice versa. These findings provide useful information for municipal authorities and other stakeholders to undertake appropriate decisions to tackle Urban Heat Island (UHI) effects by adopting effective urban planning and management interventions.

Keywords:

• land surface temperature (LST)
• normalised difference vegetation index (NDVI)
• moderate resolution imaging spectroradiometer (MODIS)
• city-region

ACKNOWLEDGMENTS

We acknowledge the South African Weather Service (SAWS) for providing us with the meteorological data used in this study. We graciously thank the anonymous reviewer for constructive comments that improved this manuscript.