Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1765-1772, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1765-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1765-1772, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1765-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

SNOW COVER MAPPING AND ICE AVALANCHE MONITORING FROM THE SATELLITE DATA OF THE SENTINELS

S. Wang1, B. Yang1,2, Y. Zhou1, F. Wang1, R. Zhang1,2, and Q. Zhao1 S. Wang et al.
  • 1Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing 100101, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China

Keywords: Snow Cover, Ice Avalanche, Sentinels

Abstract. In order to monitor ice avalanches efficiently under disaster emergency conditions, a snow cover mapping method based on the satellite data of the Sentinels is proposed, in which the coherence and backscattering coefficient image of Synthetic Aperture Radar (SAR) data (Sentinel-1) is combined with the atmospheric correction result of multispectral data (Sentinel-2). The coherence image of the Sentinel-1 data could be segmented by a certain threshold to map snow cover, with the water bodies extracted from the backscattering coefficient image and removed from the coherence segment result. A snow confidence map from Sentinel-2 was used to map the snow cover, in which the confidence values of the snow cover were relatively high. The method can make full use of the acquired SAR image and multispectral image under emergency conditions, and the application potential of Sentinel data in the field of snow cover mapping is exploited. The monitoring frequency can be ensured because the areas obscured by thick clouds are remedied in the monitoring results. The Kappa coefficient of the monitoring results is 0.946, and the data processing time is less than 2 h, which meet the requirements of disaster emergency monitoring.