SAHARA: A Simplified AtmospHeric Correction AlgoRithm for Chinese gAofen Data: 1. Aerosol Algorithm

Abstract

Abstract:The recently launched Chinese GaoFen-4 (GF4) satellite provides valuable information to obtain geophysical parameters describing conditions in the atmosphere and at the Earth's surface. The surface reflectance is an important parameter for the estimation of other remote sensing parameters linked to the eco-environment, atmosphere environment and energy balance. One of the key issues to achieve atmospheric corrected surface reflectance is to precisely retrieve the aerosol optical properties, especially Aerosol Optical Depth (AOD). The retrieval of AOD and corresponding atmospheric correction procedure normally use the full radiative transfer calculation or Look-Up- Table (LUT) methods, which is very time-consuming. In this paper, a Simplified AtmospHeric correction AlgoRithm for gAofen data (SAHARA) is presented for the retrieval of AOD and corresponding atmospheric correction procedure. This paper is the first part of the algorithm, which describes the aerosol retrieval algorithm. In order to achieve high-accuracy analytical form for both LUT and surface parameterization, the MODIS Dark-Target (DT) aerosol types and Deep Blue (DB) similar surface parameterization have been proposed for GF4 data. Limited Gaofen observations (i.e., all that were available) have been tested and validated. The retrieval results agree quite well with MODIS Collection 6.0 aerosol product, with a correlation coefficient of R 2 = 0.72. The comparison between GF4 derived AOD and Aerosol Robotic Network (AERONET) observations has a correlation coefficient of R 2 = 0.86. The algorithm, after comprehensive validation, can be used as an operational running algorithm for creating aerosol product from the Chinese GF4 satellite.

Evaluation and comparison of multiangle implementation of the atmospheric correction algorithm, Dark Target, and Deep Blue aerosol products over China

“…Some studies were also conducted to examine the properties of these high-quality measurements in China (Liu et al, 2011;Xia et al, 2007;Li et al, 2007;Che et al, 2008Che et al, , 2014Bi et al, 2014). These high-accuracy datasets support various satellite AOD product evaluation studies in the China region (Tao et al, 2015;Tian et al, 2018;He et al, 2017;Sogacheva et al, 2018). AERONET provides three quality levels of data, e.g., level 1.0, level 1.5, and level 2.0, in version 3.…”

Simplified and Fast Atmospheric Radiative Transfer model for satellite-based aerosol optical depth retrieval

“…For example, Riffler et al (2010) have developed a modified Advanced Very High Resolution Radiometer (AVHRR) aerosol optical depth retrieval algorithm, which employs only the single scattering approximation for Rayleigh and aerosol reflectance calculation. This single scattering approximation is also used in the Simplified High-resolution Aerosol Retrieval Algorithm (SARA; Bilal et al, 2013) and the Simplified Atmospheric Correction Algorithm for Chinese Gaofen (SAHARA; She et al, 2017). Although use of the single scattering approximation allows extremely fast RTM computation, Antoine and Morel (1998) have noted significant differences between single and multiple scattering approximations for aerosol reflectance calculation.…”

Atmospheric correction of multispectral satellite imagery

“…Åñëè ÷èñëî êàíàëîâ ñåíñîðà ðàâíî, íàïðèìåð, 3 èëè 4 (êàê ó ðîññèéñêîãî ñïóòíèêà "Êàíîïóñ-Â" èëè ÁÊÀ (Áåëîðóññêèé êîñìè÷åñêèé àïïàðàò)), òî äàëüíåéøåå óìåíüøåíèå ÷èñëà íåèçâåñòíûõ ïàðàìåòðîâ ìîaeåò îñóùåñòâëÿòüñÿ íà îñíîâå èñïîëüçîâàíèÿ ðåãðåññèîííûõ ñîîòíîøåíèé ìåaeäó ïàðàìåòðàìè àòìîñôåðû.  ÷àñòíîñòè, â ðàáîòå (She et al, 2017) óñòàíîâëåíû ñëåäóþùèå ðåãðåññèîííûå ñîîòíîøåíèÿ àëüáåäî îäíîêðàòíîãî ðàññåÿíèÿ íà îïîðíîé äëèíå âîëíû ω λ0 è ïîêàçàòåëÿ Àíãñòðåìà β ñ àýðîçîëüíîé îïòè÷åñêîé òîëùèíîé àòìîñôåðû íà îïîðíîé äëèíå âîëíû τ a0 :…”