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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/amt-2017-306
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2017-306
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  23 Oct 2017

23 Oct 2017

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This preprint was under review for the journal AMT but the revision was not accepted.

A method for the spectral analysis and identification of Fog, Haze and Dust storm using MODIS data

Qinghua Su1,2, Lin Sun1, Mei Di1, Xinyan Liu1, and Yikun Yang1 Qinghua Su et al.
  • 1Geomatics College, Shandong University of Science and Technology, Shandong Qingdao 266590, China
  • 2School of Geography and Tourism, Qufu Normal University, Qufu 273165, China

Abstract. The three typical extreme weather of fog, haze and dust storm have occurred frequently in recent years in China. These events influence the transportation, the ecological environment, and the daily lives of people. Remote sensing is very important technology that can be used to monitor them due to its high temporal resolution and wide area of coverage. But because the spectral features of the three extreme weather conditions are very complex, the high accuracy identification of them is facing severe challenges. In this article, the spectra of these three weather conditions, as well as those of clouds and the background surface, are analyzed. A monitoring model is constructed to achieve the separation of fog, haze, dust storm, clouds and the underlying surface using satellite data. The monitoring results are tested based on their corresponding measurements obtained from ground stations, and indicate that the extraction of fog, haze and dust storm can reach a high accuracy.

Qinghua Su et al.

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Qinghua Su et al.

Qinghua Su et al.

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Short summary
The three typical extreme weather of fog, haze and dust storm have occurred frequently in recent years in China. The spectra characteristics of fog, haze, dust storm, as well as clouds and the background surface, are analyzed. A monitoring model is constructed to achieve the separation of fog, haze, dust storm, clouds and the underlying surface using MODIS data. The monitoring results are tested, and indicate that the extraction of fog, haze and dust storm can reach a high accuracy.
The three typical extreme weather of fog, haze and dust storm have occurred frequently in recent...
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