The retrieval of aerosol properties over land from satellite sensors has always been a challenge. At present, several different algorithms for retrieving aerosol optical depth (AOD) have been developed from different satellite sensors.... more
The retrieval of aerosol properties over land from satellite sensors has always been a challenge. At present, several different algorithms for retrieving aerosol optical depth (AOD) have been developed from different satellite sensors. While each algorithm has its own advantages, the accuracy of AOD retrieval still needs to be further improved. To improve the retrieval accuracy of aerosol algorithms, it is necessary to provide a better method to describe the surface properties. In the current study, a new aerosol retrieval algorithm for Moderate Resolution Imaging Spectroradiometer (MODIS) images at a high spatial resolution of 500 m is proposed based on $a$ priori bidirectional reflectance distribution function (BRDF) shape parameters database, which is reconstructed via the 3-D discrete cosine transform (DCT-PLS) method. Then, the surface reflectances are calculated from BRDF model (i.e., RossThick-LiSparse), and a non-Lambertian forward model used to describe the surface anisotropy. The new algorithm is used for processing the MODIS over the Beijing–Tianjin–Hebei of China, and Southeastern United States of America regions, and results are validated against AERONET AOD measurements as well as compared with the MODIS AOD products. The comparison showed that the estimation scheme of surface reflectance in this new algorithm significantly improved the AOD retrievals accuracy, with average correlation coefficient ~0.965 and root-mean-square error ~0.125; the number of AOD retrievals falling within expected error has increased to ~80.1%, and the overestimation uncertainty has been reduced compared with MODIS products. Due to the high spatial resolution and continuous spatial distributions of the AOD retrievals by the new algorithm, therefore, it can well-captured aerosol details over mixed surfaces and better useful for air pollution studies than the MODIS products at local and urban scales.
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HJ-1B (Huan Jing = Environment) IRS (Infrared Scanner) is one of the key instruments onboard HJ-1B satellite, launched by China in 2008. The 150m and 300m resolutions in four spectral bands wavelength ranging from near-infrared to thermal... more
HJ-1B (Huan Jing = Environment) IRS (Infrared Scanner) is one of the key instruments onboard HJ-1B satellite, launched by China in 2008. The 150m and 300m resolutions in four spectral bands wavelength ranging from near-infrared to thermal infrared, and the four days revisit period, make it attractive for researching the global change by providing the parameter of LST (Land Surface Temperature). LST retrieval requires a background value of Land Surface Emissivity (LSE). But for lack of a red band on HJ-1B IRS, LSE calculation faces a great challenge with the traditional methods. A method using the high quality data outputs of 16 days combined MODIS (MODerate Resolution Imaging Spectroradiometer ) NDVI (Normalized Difference Vegetation Index) was presented to calculate the LSE. To decrease the effect of pixels mismatch from two kinds of data, a method of Pixel Number Percentage Matching (PNPM) was proposed, this method matches the pixels of MODIS and HJ-1 IRS by counting the percentage of different level of NDVI. It can effectively decrease the LSE errors caused by the mismatch of two kinds of data. Two prevalent methods for LST deriving were chosen to calculate LST from HJ-1B IRS, one is developed by Qin and Karnieli, hereafter referred to as “QK&B”, the other is developed by Jiménez-Muñoz and Sobrin hereafter referred to as “JM&S”. LST retrieved from HJ-1 IRS was compared with MODIS LST products, which have been validated to have a high precision, result showed, that LST retrieved from HJ-1B IRS LST by the two algorithms are highly in conformity with the MODIS LST products.
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The operational Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Products (APs) have provided long-term and wide-spatial-coverage aerosol optical properties across the globe, such as aerosol optical depth (AOD). However, the... more
The operational Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Products (APs) have provided long-term and wide-spatial-coverage aerosol optical properties across the globe, such as aerosol optical depth (AOD). However, the performance of the latest Collection 6.1 (C6.1) of MODIS APs is still unclear over urban areas that feature complex surface characteristics and aerosol models. The aim of this study was to validate and compare the performance of the MODIS C6.1 and C6 APs (MxD04, x = O for Terra, x = Y for Aqua) over Beijing, China. The results of the Dark Target (DT) and Deep Blue (DB) algorithms were validated against Aerosol Robotic Network (AERONET) ground-based observations at local sites. The retrieval uncertainties and accuracies were evaluated using the expected error (EE: ±0.05 + 15%) and the root-mean-square error (RMSE). It was found that the MODIS C6.1 DT products performed better than the C6 DT products, with a greater percentage (by about 13%–14%) of th...