Retrieval of Urban Aerosol Optical Depth from Landsat 8 OLI in Nanjing, China

Abstract

Aerosol is an essential parameter for assessing the atmospheric environmental quality, and accurate monitoring of the aerosol optical depth (AOD) is of great significance in climate research and environmental protection. Based on Landsat 8 Operational Land Imager (OLI) images and MODIS09A1 surface reflectance products under clear skies with limited cloud cover, we retrieved the AODs in Nanjing City from 2017 to 2018 using the combined Dark Target (DT) and Deep Blue (DB) methods. The retrieval accuracy was validated by in-situ CE-318 measurements and MOD04_3K aerosol products. Furthermore, we analyzed the spatiotemporal distribution of the AODs and discussed a case of high AOD distribution. The results showed that: (1) Validated by CE-318 and MOD04_3K data, the correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) of the retrieved AODs were 0.874 and 0.802, 0.134 and 0.188, and 0.099 and 0.138, respectively. Hence, the combined DT and DB algorithms used in this study exhibited a higher performance than the MOD04_3K-obtained aerosol products. (2) Under static and stable meteorological conditions, the average annual AOD in Nanjing was 0.47. At the spatial scale, the AODs showed relatively high values in the north and west, low in the south, and the lowest in the center. At the seasonal scale, the AODs were highest in the summer, followed by spring, winter, and autumn. Moreover, changes were significantly higher in the summer than in the other three seasons, with little differences among spring, autumn, and winter. (3) Based on the spatial and seasonal characteristics of the AOD distribution in Nanjing, a case of high AOD distribution caused by a large area of external pollution and local meteorological conditions was discussed, indicating that it could provide extra details of the AOD distribution to analyze air pollution sources using fine spatial resolution like in the Landsat 8 OLI.

Development and Testing a Method for Retrieving Atmospheric Aerosol Optical Thickness based on the Solar Intensity from the Sun-photometer Data

“…Comparing the method in processing the sun-photometer data (Xun et al, 2021;Bărbulescu, 2022), the Langley plot and Lambert-Beer Law are useful to support several methods in retrieving the solar intensity from the extraterrestrial atmosphere. In several atmospheric corrections of optical remote sensing using satellite sensors, the AOT's values play an essential role in arranging a Look Up Table (LUT) for scattering parameters (Aminuddin et al, 2018a;Jin et al, 2021;Kuze, 2012b).…”

Retrieval of Aerosol Optical Thickness with Custom Aerosol Model Using SKYNET Data over the Chiba Area

“…The sky-radiometer data observed at CEReS is used to constraint the aerosol model through the wavelength dependence of AOTs, and we assumed custom aerosol model can be applied to the whole Kanto area based on surface albedo under clearsky conditions. Additionally, the reference of surface albedo generated from clearsky conditions can be employed to retrieve the spatial distribution of AOTs not only Although the availability of clear-sky images from Landsat-8 is limited because of its long revisit time (16 days) [54,55], the fine resolution of its imagery (30 m per pixel) will be useful for dealing with the mixel (mixed pixel) problem inevitable for Himawari-8 imagery. The AOTs from Landsat-8 band 2 (482 nm) varies in the range 0.1~0.2, which reasonably agrees with the result found for Himawari-8 band 1 (470 nm).…”

“…The retrieved AOTs using custom aerosol model had good consistencies, Figure 13 shows a tentative result of AOT distributions for the visible images from Landsat-8 OLI visible bands observed on 6 January 2020. Although the availability of clear-sky images from Landsat-8 is limited because of its long revisit time (16 days) [54,55], the fine resolution of its imagery (30 m per pixel) will be useful for dealing with the mixel (mixed pixel) problem inevitable for Himawari-8 imagery. The AOTs from Landsat-8 band 2 (482 nm) varies in the range 0.1~0.2, which reasonably agrees with the result found for Himawari-8 band 1 (470 nm).…”

Retrieving High-Resolution Aerosol Optical Depth from GF-4 PMS Imagery in Eastern China

“…For the other satellites, limited by the aerosol retrieval algorithms, their spatial resolution and overall accuracy are overall lower than those of MODIS products. Of course, many scholars have developed their own algorithms to retrieve AODs from different high-resolution satellites [47][48][49][50][51][52], but these generated data are not public, making it impossible to perform a comparison. Considering these, MODIS DT and DB AOD products at different resolutions are selected for comparison in the current study.…”