Inversion of aerosol optical depth based on the measurement of HJ-1 satellite in Changsha city

doi:10.14088/j.cnki.issn0439-8114.2019.17.013

Abstract

Abstract: Based on the data of the CCD and IRS from HJ-1 satellite, the aerosol optical depth （AOD） in Changsha city was determined by the extended dark pixel algorithm with the processes of radiation calibration, pixels extracted, cloudy pixels deleted and 6S radiation transmission model used. The results show that the AOD in the east side of the Xiang River is higher than that in the west side. The values of AOD are more than 0.7 in the most of urban areas and surrounding with also typical low AODs existed, while they are between 0.3 and 0.5 in the outer suburbs. The typical high values of AOD distribute three places. One is located in Wangcheng district between the north of Xiang river road and Xiang river containing the Xianinggang School, Xintangchong, and Changtang, with the AOD between 1.4 and 1.6. One is located between Sifangping overpass and Yazipu road, with the AOD between 1.3 and 1.5. The last is located in Yuhua district in the north area of the south station of Changsha, with the AOD between 1.5 and 1.8. There are also three regions with low AOD in the cityThe first is located in the belt of Yuelu mountain-Meixi lake-Taohua hill, while the second is located in Gushan forest farm and the third is located in the belt of Hunan Province Forestry Bureau and Hunan Forestry Science and Technology Demonstration Park-Tianji mountain park-Hunan Botanical Garden. The comparative analysis results betwwen inversed AOD and the concentrations of PM10 and PM2.5 show that the distributions between AODs and the concentrations of PM10 have a good consistency.

Key words: HJ-1satellite, aerosol optical depth, fog and haze, space distribution, Changsha city

CLC Number:

P407.4

ZHOU Bi, LIAO Yu-fang, HAN Qin-zhe, GAO Xia-xia, DUAN Li-jie, DU Dong-sheng, DENG Jian-bo. Inversion of aerosol optical depth based on the measurement of HJ-1 satellite in Changsha city[J]. HUBEI AGRICULTURAL SCIENCES, 2019, 58(17): 51-55.

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