Coupling Remote Sensing Insights With Vegetation Dynamics and to Analyze NO₂ Concentrations: A Google Earth Engine-Driven Investigation

Abstract

Rapid urbanization and industrialization in Lahore and Faisalabad have intensified air pollution issues, influencing nitrogen dioxide (NO2) concentrations, land surface temperature (LST), and vegetation. The study aims to comprehensively assess changes in NO2, LST, and vegetation induced by industrialization, focusing on seasonal variations from 2019-2022. The study evaluates NO2 concentrations vegetation health using indices Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Atmospherically Resistant Vegetation Index (ARVI), and LST variations. The analysis reveals a notable increase in NO2 during both summer and winter, with approximately 0.021 (×10 3 mol/m 2 ) and 0.03 (×10 3 mol/m 2 ) rises observed in Lahore. In comparison, Faisalabad experienced more modest increases of around 0.0034 (×10 3 mol/m 2 ) and 0.007 (×10 3 mol/m 2 ) in the respective seasons. Simultaneously, vegetation indices decline in both cities, indicating substantial vegetation health deterioration. Moreover, a notable upward trend in LST occurred, with Lahore experiencing an increase of approximately 1.59 ℃ in summer and 0.92 °C in winter. Faisalabad also showed rises of around 1.64 and 0.54 ℃ in the corresponding seasons. Pearson correlation analysis highlights a robust negative correlation between NO2 and vegetation indices, underlining the impact of declining vegetation on air quality. A positive correlation between NO2 and LST indicates the interconnected nature of rising temperatures and air pollution. The findings emphasize the need for environmental regulations in Lahore and Faisalabad. Addressing rising NO2 levels and temperatures is critical for policymakers and urban planners. These insights contribute to the Sustainable Development Goal (SDG-11), fostering strategies for sustainable cities and communities to combat pressing environmental challenges in these urban areas.