Urban Air Pollution–Heat Correlation Across Vegetation Density Classes: A Remote Sensing Study Using Google Earth Engine
摘要
Urbanization exacerbates environmental issues such as air pollution and urban heat stress, particularly in fast-growing cities. While prior studies have emphasized the importance of green areas in moderating these impacts, they frequently overlook how spatial changes in vegetation influence pollutant-thermal interactions. In order to examine the relationship between key air pollutants (NO2, SO2, CO, and O3) and UTFVI, this study proposes a spatial analytical framework that explicitly takes intra-urban variations in vegetation cover into account. Focusing on Tehran, which has high variety in both environmental quality and green space distribution, the study divides the city’s 22 districts into three categories based on NDVI-derived vegetation density. The study found that as green coverage decreases, the negative correlation between NO2 and UTFVI increases, from 0.08 in high-vegetation areas to − 0.48 in low-vegetation zones. A comparable trend is found when examining the relationship between LST and NO₂, with correlation values shifting from 0.01 to – 0.51 across the same vegetation gradient. To examine how changes in vegetation over time relate to shifts in thermal conditions and air quality, a five-year spatial–temporal analysis (2020–2024) was conducted. The findings indicate that areas with greater vegetation cover consistently experience reduced thermal field variance (r = – 0.45) and NO2 concentrations (r = – 0.52), while correlations with SO2, O3, and CO remain relatively weak. By categorizing urban areas according to vegetation levels, this study offers novel insights into the localized dynamics of climate-pollution interactions, emphasizing the importance of a context-sensitive approach for effective urban heat mitigation and sustainable land-use planning.