The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-7/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 243–246, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W3-243-2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 243–246, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W3-243-2015

  28 Apr 2015

28 Apr 2015

Preliminary Research on Radiance Fog Detection based on time series MTSAT data

X. Wen1, Z. Li1, S. Zhang1, S. Shen1, D. Hu2, and X. Xiao1 X. Wen et al.
  • 1Changjiang River Scientific Research Institute, Changjiang Water Resources Commission, Wuhan 430010, PR China
  • 2Department of Pharmacy, Tongji Hospital Affiliated with Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 430032, PR China

Keywords: Radiance fog, MTSAT, time series, Haar wavelet, frequency domain

Abstract. Fog is a kind of disastrous weather phenomenon. In this paper, the geostationary satellite MTSAT imagery is selected as the main data source to radiance fog detection. According to the unique feature of radiance fog from its generation to dissipation, especially considering the difference between clouds and fog during their lifecycle, the characteristics in frequency domain was constructed to discriminate fog from clouds, The time series MTSAT images were register with a modified Gauss Newton optimization method firstly, then, the Savitzky-Golay smoothing filter was applied to the time series remote sensing imageries to process the noises in the original signal, after that the non-orthogonal Haar wavelets was applied to convert the signal from time domain into frequency domain. The coefficient of high frequency component, including the properties: “max”, “min”, “the location of the min”, “the interval length between the max and min”, “the coefficient of linear fit for the high frequency”, these properties are selected as the characteristic parameters to distinguish fog from clouds. The experiment shows that using the algorithm proposed in this paper, the radiance fog could be monitored effectively, and it is found that although it is difficult to calculate the thickness of the fog directly, while the duration of fog could be obtained by using the frequency feature.