Assessing air quality variations in relation to vegetation patterns and meteorological conditions using remote sensing

Rapid industrialization, urban expansion, and the growth of transportation networks have significantly increased air pollutant emissions, especially in urban and peri-urban areas of developing nations. This study investigates the interplay among air quality, vegetation condition, and meteorological variables across two contrasting environments: the highly urbanized area of Sandton and the semi-urban setting of Tembisa. By comparing these locations, the research assesses how varying degrees of urbanization shape the relationships between atmospheric pollutants, ecological health, and local climate dynamics. During summer (DJF), Sandton recorded relatively low NO 2 concentrations (5–7 μg/m 3 ) alongside high Modified Soil Adjusted Vegetation Index (MSAVI) values (0.4–0.67), reflecting extensive, healthy vegetation maintained through urban greenery such as trees, irrigated gardens, and landscaped areas. Vegetation remained comparatively stable year-round, with high summer greenness and only moderate winter decline, indicating a more persistent vegetative cover than in Tembisa. Tembisa, by contrast, showed fragmented and strongly seasonal vegetation, with reduced greenness outside summer and a pronounced decline in winter. In the winter months (JJA), environmental variables in Tembisa exhibited strong interrelationships: NO 2 and land surface temperature (LST) were highly positively correlated (r = 0.98), while Modified Soil Adjusted Vegetation Index and precipitation showed a strong negative correlation (r = −0.89), suggesting that winter rainfall may negatively affect vegetation through processes such as waterlogging, erosion, or runoff. In Sandton, however, only weak winter correlations were detected among these variables, indicating that precipitation has minimal influence on vegetation, temperature, and SO 2 levels within this urban environment.