Publications

Wang, Y; Yuan, QQ; Li, TW; Shen, HF; Zheng, L; Zhang, LP (2019). Large-scale MODIS AOD products recovery: Spatial-temporal hybrid fusion considering aerosol variation mitigation. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 157, 1-12.

Abstract
Aerosol optical depth (AOD) is a pivotal parameter to reflect aerosol properties, such as aerosol radiative forcing and atmospheric corrections of the aerosol effect. Unfortunately, the valid pixels of moderate resolution imaging spectroradiometer (MODIS) AOD products are scarce, which has attracted great attention from scholars. In recent years, numerous AOD recovering algorithms have been proposed and the algorithms merely employing a single temporal AOD image are regarded as the most convenient and flexible for large-scale practical applications. However, current algorithms face the challenge of insufficiently considering the impacts of aerosol variation resulted from the temporal difference. Meanwhile, the improvement of AOD valid pixels is also poor due to the scarce excavation of complementary information. In order to address these issues, a novel algorithm of spatial-temporal hybrid fusion considering aerosol variation mitigation (ST-AVM) is developed to fill the missing pixels in Aqua AOD products with a single Terra AOD image in large scale. The results show that the total recovered AOD products nearly maintain the original accuracy of MODIS. Meanwhile, the AOD coverage is significantly improved in the study areas and the degrees of improvements regionally vary. Overall, the AOD coverage over land is increased by 123.9% (from 20.5% to 45.9%) after the recovery. Besides, the spatial distribution of recovered monthly AOD products remains fairly consistent as the original Aqua. Also, the recovered annual AOD spatial distribution shows more coherent, which indicates the reliability of ST-AVM algorithm.

DOI:
10.1016/j.isprsjprs.2019.08.017

ISSN:
0924-2716