Retrieval of High-Resolution Aerosol Optical Depth (AOD) using Landsat 8 imageries over different LULC classes over a City along Indo-Gangetic Plain, India

Abstract

Aerosol Optical Depth (AOD) serves as a crucial indicator for assessing regional air quality by quantifying aerosol levels in the atmosphere. While various satellite methods exist for estimating AOD, the spatial resolution of established AOD products is often limited. However, obtaining higher-resolution AOD data is essential for gaining a deeper understanding of regional and urban air pollution issues. To address this issue, we retrieved high-resolution AOD over Kanpur (26.4499° N, 80.3319° E), located in the Indo-Gangetic Plain (IGP) region using Landsat 8 imageries. We have used Landsat 8 imagery and the SEMARA algorithm, which combines SARA (Simplified Aerosol Retrieval Algorithm) and SREM (Simplified and Robust Surface Reflectance Estimation). Our approach leveraged the green band of the Landsat 8, resulting in an impressive spatial resolution of 30 meters. This methodology was applied over the period from 2014 to 2022 and rigorously validated with available AERONET observations. The retrieved AOD is in good agreement with high correlation coefficients (r) of 0.997, a low root mean squared error (RMSE) of 0.035, and root mean bias (RMB) of -4.91%. Furthermore, we conducted a comprehensive comparison with downscaled MODIS (MCD19A2) AOD products across various land classes for cropped and harvested period of agriculture cycle with different land use and land cover classes. The SEMARA approach proved to be more effective for AOD retrieval on brighter surfaces within the barren and built-up land categories for harvested period. This methodology holds great potential for monitoring aerosols over bright urban areas.