Research on Atmospheric Visibility Grading based on Remote Sensing Data

Research on Atmospheric Visibility Grading based on Remote Sensing Data

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Author(s): Siyu Wang, Xiuguo Zou, Xinfa Qiu

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DOI: 10.18483/ijSci.2286 34 129 44-48 Volume 9 - Mar 2020


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.


Atmospheric Visibility Grading, Remote Sensing Data, MODIS


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International Journal of Sciences is Open Access Journal.
This article is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License.
Author(s) retain the copyrights of this article, though, publication rights are with Alkhaer Publications.

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