Research on Atmospheric Visibility Grading based on Remote Sensing Data

Siyu Wang, Xiuguo Zou and Xinfa Qiu

International Journal of Sciences, 2020, vol. 9, issue 03, 44-48

Abstract: Theoretical research on atmospheric radiative transfer shows that aerosol optical depth (AOD) is positively correlated with atmospheric particulate matter (PM) concentration. Using satellite remote sensing data to retrieve the AOD, and monitor and analyze the atmospheric visibility and atmospheric pollution are gradually being widely applied. In this research, the data of moderate resolution imaging spectroradiometer (MODIS) is used for analysis. Firstly, geometric correction, data quality improvement, image stitching, vector cropping, and masking are performed to process the data. Then, the cloud detection tree algorithm is used to detect cloud, thereby eliminating the cloud interference. Finally, the classic dense dark vegetation (DDV) algorithm is used for the retrieval of AOD, and the distribution characteristics of the obtained AOD values are graded according to the retrieval results. This paper uses remote sensing data to grade the visibility of the atmosphere, which provides a reference for the prediction and assessment of the overall atmospheric environment.

Keywords: Atmospheric Visibility Grading; Remote Sensing Data; MODIS (search for similar items in EconPapers)
Date: 2020
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DOI: 10.18483/ijSci.2286

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