Retrieval of high-resolution aerosol optical depth (AOD) using Landsat 8 imageries over different LULC classes over a city along Indo-Gangetic Plain, India

Aerosol optical depth (AOD) serves as a crucial indicator for assessing regional air quality. To address regional and urban pollution issues, there is a requirement for high-resolution AOD products, as the existing data is of very coarse resolution. 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 and implemented the algorithm SEMARA, 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 m of AOD 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 of 0.035, and root mean bias of - 4.91%. We evaluated the retrieved AOD with downscaled MODIS (MCD19A2) AOD products across various land classes for cropped and harvested period of agriculture cycle over the study region. It is noticed that over the built-up region of Kanpur, the SEMARA algorithm exhibits a stronger correlation with the MODIS AOD product compared to vegetation, barren areas and water bodies. The SEMARA approach proved to be more effective for AOD retrieval over the barren and built-up land categories for harvested period compared with the cropping period. This study offers a first comparative examination of SEMARA-retrieved high-resolution AOD and MODIS AOD product over a station of IGP.

Retrieval of total and fine mode aerosol optical depth by an improved MODIS Dark Target algorithm

Total and fine mode aerosol optical depth (AODT and AODF), as well as the fine mode fraction (FMF = AODF/AODT), are critical variables for climate change and atmospheric environment studies. The retrievals with high accuracy from satellite observations, particularly FMF and AODF over land, remain challenging. This study aims to improve the Moderate-resolution Imaging Spectro-radiometer (MODIS) land dark target (DT) algorithm for retrieving AODT, AODF, and FMF on a global scale. Based on the fact that the underestimated surface reflectance (SR) could overestimate the AODT and underestimate the aerosol size parameter in the DT algorithm, two robust schemes were developed to improve SR determination: the first (NEW1 DT) used the top of the atmosphere reflectance instead of SR at 2.12 µm; the second (NEW2 DT) used eleven-year MODIS data to establish a monthly spectral SR relationship model (2.12-0.47 and 2.12-0.65 µm) database at pixel-by-pixel scale. Then a novel lookup table approach based on the physical process was proposed to retrieve the AODF and FMF. The new MODIS AODT, FMF, and AODF were compared to AERosol RObotic NETwork (AERONET) retrievals. Results showed that the root mean square error (RMSE) was 0.096-0.103, 0.098-0.099, and 0.167-0.180 for the new AODTs, AODFs, and FMFs, respectively, which were better than that of the Collection 6.1 (C6.1) DT (0.117, 0.235, and 0.426) in the validation by global AERONET sites. From the validation results, NEW2 DT provided better AODT and coarse mode AOD retrievals, while NEW1 DT had better AODF and FMF performances. The spatial patterns of AODF, FMF, and AODC of the new DT algorithms were comparable to those of the Polarization and Directionality of the Earth's Reflectances aerosol product. Hence, the new algorithms have the potential to provide global AODT, FMF, and AODF products over land to the scientific community with high accuracy using long-term MODIS data.

Advances in sunphotometer-measured aerosol optical properties and related topics in China: Impetus and perspectives

Aerosol is a critical trace component of the atmosphere. Many processes in the Earth's climate system are intimately related to aerosols via their direct and indirect radiative effects. Aerosol effects are not limited to these climatic aspects, however. They are also closely related to human health, photosynthesis, new energy, etc., which makes aerosol a central focus in many research fields. A fundamental requirement for improving our understanding of the diverse aerosol effects is to accumulate high-quality aerosol data by various measurement techniques. Sunphotometer remote sensing is one of the techniques that has been playing an increasingly important role in characterizing aerosols across the world. Much progress has been made on this aspect in China during the past decade, which is the work reviewed in this paper. Three sunphotometer networks have been established to provide high-quality observations of long-term aerosol optical properties across the country. Using this valuable dataset, our understanding of spatiotemporal variability and long-term trends of aerosol optical properties has been much improved. The radiative effects of aerosols both at the bottom and at the top of the atmosphere are comprehensively assessed. Substantial warming of the atmosphere by aerosol absorption is revealed. The long-range transport of dust from the Taklimakan Desert in Northwest China and anthropogenic aerosols from South Asia to the Tibetan Plateau is characterized based on ground-based and satellite remote sensing as well as model simulations. Effective methods to estimate chemical compositions from sunphotometer aerosol products are developed. Dozens of satellite and model aerosol products are validated, shedding new light on how to improve these products. These advances improve our understanding of the critical role played by aerosols in both the climate and environment. Finally, a perspective on future research is presented.

Simultaneous determination of aerosol optical depth and exponent of the Junge power law from MODIS shortwave infrared bands over Qinghai Lake

The water-leaving radiances for shortwave infrared (SWIR) channels can be negligible, and these channels also contain information on aerosol particle size. Therefore, the satellite-based data of SWIR channels can be used to estimate aerosol particle size over inland waters [Appl. Opt.39, 887 (2000)APOPAI0003-693510.1364/AO.39.000887]. Supposing the actual atmospheric aerosol size distribution is based on the Junge power law, in this paper an iterative algorithm is used to simultaneously determine the aerosol optical depth (AOD) and the exponent of the Junge power law from Aqua MODIS L1B reflectance data of channels 1.64 μm and 2.13 μm over Qinghai Lake. Whether using the constant or variable aerosol complex refractive index (ACRI), the retrieved exponent of the Junge power law is always larger than the product value. Supposing the product values are accurate, for the constant ACRI, there are 68.91% and 25.48% pixels of acceptable retrieval AOD and the exponent of the Junge power-law value, respectively. Likewise, there are 71.63% and 43.75% pixels for variable ACRI. Compared with the retrieval error under constant ACRI, there are 58.65% and 98.72% pixels, with a smaller AOD and Junge power-law index retrieval error under variable ACRIs, respectively. In addition, the precision of the AOD retrieved with variable ACRI is improved when the AOD product is less than 0.17. However, under the current environment with frequent aerosol particle pollution, the same ACRI for the ten wavelengths can achieve results with equivalent accuracy compared with variable ACRI.

High resolution remote sensing of densely urbanised regions: a case study of Hong Kong

Data on the urban environment such as climate or air quality is usually collected at a few point monitoring stations distributed over a city. However, the synoptic viewpoint of satellites where a whole city is visible on a single image permits the collection of spatially comprehensive data at city-wide scale. In spite of rapid developments in remote sensing systems, deficiencies in image resolution and algorithm development still exist for applications such as air quality monitoring and urban heat island analysis. This paper describes state-of-the-art techniques for enhancing and maximising the spatial detail available from satellite images, and demonstrates their applications to the densely urbanised environment of Hong Kong. An Emissivity Modulation technique for spatial enhancement of thermal satellite images permits modelling of urban microclimate in combination with other urban structural parameters at local scale. For air quality monitoring, a Minimum Reflectance Technique (MRT) has been developed for MODIS 500 m images. The techniques described can promote the routine utilization of remotely sensed images for environmental monitoring in cities of the 21(st) century.