Spatial-temporal contrast analysis of MODIS aerosol products in Heihe River basin

doi:10.13474/j.cnki.11-2246.2020.0216

Abstract

Abstract: Satellite remote sensing monitoring and aerosol foundation observation networks provide a data basis for aerosol research. Satellite remote sensing monitoring commonly used Terra and Aqua satellites are equipped with MODIS sensors to obtain satellite imagery data inversion of aerosol optical thickness AOD. MODIS data inversion of the aerosol optical thickness products currently experienced C002, C003, C004, C005, C006 and other versions. In order to compare and analyze the MODIS aerosol products in the Heihe River basin, this paper first validates the accuracy of the aerosol optical thickness product of the C006 version in the Heihe River basin, and then analyzes the spatial-temporal characteristics of aerosol optical thickness in the study area. The accuracy of the MODIS aerosol optical thickness product is verified by the observation data of the HIHATER aerosol optical thickness. The results show that MODIS aerosol products have higher accuracy and higher reliability than those with high applicability. The aerosol optical thickness of the aerosol in the study area is higher than that in the morning, and the optical thickness of the aerosol in the middle and lower reaches is higher than that in the upstream region. The aerosol thickness of summer is higher than that of aerosol in other seasons. The high value of aerosol optical field in spring is concentrated in the downstream area. The high value area of summer is distributed in the upstream area, and the distribution of high value area in autumn is relatively uniform. In winter, the high values are mainly distributed in the western region.

Key words: aerosol optical thickness, error test, comparative analysis, spatio-temporal change, AOD distribution

CLC Number:

P237

SONG Xiaochun, LIU Xingke, SUN Weijie. Spatial-temporal contrast analysis of MODIS aerosol products in Heihe River basin[J]. Bulletin of Surveying and Mapping, 2020, 0(7): 64-69.

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