Abstract
Although many attempts have been made, it has remained a challenge to retrieve the aerosol optical depth (AOD) at 550 nm from moderate to high spatial-resolution (MHSR) optical remotely sensed imagery in arid areas with bright surfaces, such as deserts and bare ground. Atmospheric correction for remote-sensing images in these areas has not been good. In this paper, we proposed a new algorithm that can effectively estimate the spatial distribution of atmospheric aerosols and retrieve surface reflectance from moderate to high spatial-resolution imagery in arid areas with bright surfaces. Land surface in arid areas is usually bright and stable and the variation of atmosphere in these areas is also very small; consequently, the land-surface characteristics, specifically the bidirectional reflectance distribution factor (BRDF), can be retrieved easily and accurately using time series of satellite images with relatively lower spatial resolution like the Moderate-resolution Imaging Spectroradiometer (MODIS) with 500 m resolution and the retrieved BRDF is then used to retrieve the AOD from MHSR images. This algorithm has three advantages: (i) it is well suited to arid areas with bright surfaces; (ii) it is very efficient because of employed lower resolution BRDF; and (iii) it is completely automatic. The derived AODs from the Multispectral Instrument (MSI) on board Sentinel-2, Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Gao Fen 1 Wide Field Viewer (GF-1/WFV), Gao Fen 6 Wide Field Viewer (GF-6/WFV), and Huan Jing 1 CCD (HJ-1/CCD) data are validated using ground measurements from 4 stations of the AErosol Robotic NETwork (AERONET) around the world.
Highlights
A large number of continental- and global-scale applications at 30 m resolution have been created and have pushed the discoveries using remote sensing at higher spatial resolution forward, since the Landsat series of satellite data have been made freely downloadable
The satellite constellations with higher spatial resolution optical sensors will dramatically increase the observations with higher resolution, such as the Sentinle2 Multispectral Instrument (MSI) of European Space Agency (ESA), the Chinese GaoFen 1 (GF1) and GaoFen 6 (GF6) Wide Field Viewers (WFVs), and so on
The introduction of Moderate-resolution Imaging Spectroradiometer (MODIS) imagery greatly lowers the spatial resolution of the retrieved aerosol optical depth (AOD) and the applicability of the new method is subsequently restricted to those regions with relatively stable atmospheres; it cannot be applied to areas with highly varied atmospheres, such as urban areas and their surroundings
Summary
A large number of continental- and global-scale applications at 30 m resolution have been created and have pushed the discoveries using remote sensing at higher spatial resolution forward, since the Landsat series of satellite data have been made freely downloadable. A better surface reflectance dataset with spatial and temporal consistency at global scale has been required by the global-scale applications at higher spatial resolution and some methods have been developed for this purpose, such as the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) algorithm [5] and the Moderate-resolution Imaging Spectroradiometer (MODIS)-based algorithms [6,7] Both of the methods used the MODIS aerosol optical depth (AOD) product [8,9,10] with a lower spatial resolution of 7–10 km, which is only 1/20–1/30 of the required resolution, and a large portion of void areas, especially arid areas, were interpolated; subsequently, the spatial distribution of aerosols at high resolution (30 m and higher) cannot be captured well, which causes spatial inconsistency. The situations in arid areas were not taken into consideration, which largely degraded the applications in these areas
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