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Research on Atmospheric Visibility Grading based on Remote Sensing Data

Author

Listed:
  • Siyu Wang
  • Xiuguo Zou
  • Xinfa Qiu

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.

Suggested Citation

  • Siyu Wang & Xiuguo Zou & Xinfa Qiu, 2020. "Research on Atmospheric Visibility Grading based on Remote Sensing Data," International Journal of Sciences, Office ijSciences, vol. 9(03), pages 44-48, March.
    • Handle: RePEc:adm:journl:v:9:y:2020:i:3:p:44-48
    DOI: 10.18483/ijSci.2286
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