Spatiotemporal retrieval of the aerosol optical thickness using Landsat 8 OLI imagery for Indian urban area.

Autor: Chauhan, Akshay, Jariwala, Namrata, Christian, Robin
Zdroj: Air Quality, Atmosphere & Health; Jul2024, Vol. 17 Issue 7, p1467-1478, 12p
Abstrakt: The surge in urbanization and industrialization is majorly contributing to ambient air pollution, predominantly in terms of particulate emissions. Human health is highly susceptible to the particles suspended in the air due to their lightweight and small size (≤ 2.5 μm), called atmospheric aerosols. In India, insufficient ground-based instruments hinder continuous aerosol monitoring. However, remote sensing offers earth imagery for in-depth analysis of air quality and weather parameters. In the present study, an attempt is made to retrieve the high-resolution (30 m) AOT using Landsat 8 Operational Land Imager (L8-OLI) imagery for Pune, Maharashtra, from the years 2014 to 2021. For the atmospheric corrections and better spatiotemporal resolution, the dark target spectrum-based Image Corrections for Atmospheric Effects (iCOR) algorithm was executed. The year 2021 showed the highest mean AOT value at the Pashan location (18.537° N, 73.805° E) in Pune, India. Also, seasonal analysis (winter and summer) indicates that the mean AOT in the winter gradually increases every year. The AOT retrieved using L8-OLI with iCOR and AOT retrieved from Aerosol Robotic Network (AERONET) in situ monitoring station (± 30 min) at 440 nm showed R2 = 0.76, r = 0.83, and RMSE = 0.1012. From this, it is summarized that for L8-OLI images, the iCOR algorithm performs well for the atmospheric correction by retrieving AOT at high spatial resolution with minimum cloud cover. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index