# Retrieval of High Spatial Resolution Aerosol Optical Depth from HJ-1 A/B CCD Data
## 1 Introduction  
Aerosol optical depth (AOD) is considered an important geophysical parameter for atmospheric pollution, aerosol radiation, and atmospheric correction studies [1]. Therefore, accurately measuring AOD is of great significance to the inversion of surface variables and air quality [2]. Satellite images can be used to monitor aerosol changes and explain the effects of aerosols on the earth and the atmosphere on a large spatial scale [3]. Satellite remote sensing images contain information on both the surface and the atmosphere [4; 5], although an interplay exists between the two. First, aerosol in the atmosphere leads to a loss of image detail and results in large errors in the quantitative inversion of surface variables. In addition, surface information also creates problems, making the accurate inversion of aerosols difficult.  
The currently available algorithms for AOD inversion based on remote sensing images mainly include the dark target method [6; 7; 8] and the deep blue algorithm [9; 10]. The dark target method is used to obtain AOD based on the linear relationship between surface reflectance of the visible/near infrared bands and the 2.1-\(\upmu\)m shortwave infrared (SWIR) band in areas densely covered with vegetation [6], which is used as an operational method for generating the MODerate resolution Imaging Spectroradiometer (MODIS) aerosol product [8]. The deep blue algorithm is usually applied toinversion of AOD in cities, deserts, and areas covered with bare soil with high surface reflectance [11; 12]. However, due to the spatial resolution of data sources, some aerosol products currently have the disadvantage of low spatial resolution, (e.g., for MODIS, the highest spatial resolution of aerosol products is 3 km [13]). Therefore, in areas with complex surface structure, AOD information with higher spatial resolution is required. With a spatial resolution of 30 m, the charge-coupled diode (CCD) sensors onboard the Chinese Huanjing-1 A/B (HJ-1 A/B) Satellites can serve as a data source for retrieving AOD with high spatial resolution. However, the CCD sensors onboard the HJ-1 A/B satellites contain only three visible bands and one near-infrared band (Table 1). Due to the absence of the 2.1-\(\upmu\)m shortwave infrared band, the dark target method cannot be used for HJ-1 A/B CCD data. In previous studies, [PERSON] et al. [14] improved the dark target method and derived the relationship between the visible red and blue bands for retrieving AOD from HJ-1 A/B CCD data. [PERSON] et al. [15] adjusted the coefficient of this relationship so that more ideal inversion results were obtained from HJ-1 A/B CCD data over evergreen broadleaf shrub woodlands-covered surfaces. In addition, [PERSON] et al. [16] simulated the HJ-1 A hyperspectral data based on HYPERION data from a hyperspectral imaging spectrometer on the U.S. National Aeronautics and Space Administration (NASA) Earth Observing-1 (EO-1) satellite, and then applied the dark target method to conduct AOD inversion. [PERSON] et al. [12; 17] and [PERSON] et al. [5; 18] used the deep blue algorithm on bright surfaces such as cities, applied the MODIS surface reflectance product to establish a surface reflectance database in the blue band, obtained AOD by inversion, and conducted atmospheric correction based on the obtained AOD.  
Nonetheless, these methods ignored the angular effects on the interband correlations. A single sensor of HJ-1A/B CCD has a width of 360 km (Table 1), with a maximum view zenith angle of 35\({}^{\circ}\). Therefore, the influence of solar/view geometry on AOD inversion cannot be ignored [19]. In this study, an improved dark target method is proposed to retrieve high-spatial resolution AODs based on interband regression coefficients that vary with the solar/view angle and land cover type.