International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-4/W16
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 359–363, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-359-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 359–363, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-359-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  01 Oct 2019

01 Oct 2019

BIG DATA PROCESSING AND ANALYSIS USING MULTI-TEMPORAL SENTINEL 1 DATA TO MANAGE FLOODS IN NORTH OF MOROCCO

M. Lahsaini, H. Tabyaoui, and F. El Hammichi M. Lahsaini et al.
  • Natural Resources and Environment Laboratory, Sidi Mohamed Ben Abdellah University, Polydisciplinary Faculty of Taza, Morocco

Keywords: Sentinel 1, SAR Radar images, Earth Observation, Flood mapping, Morocco

Abstract. Floods are the natural hazards that produce the highest number of casualties and material damage in the Western Mediterranean, especially in Morocco. An improvement in flood risk assessment and study of a possible increase in flooding occurrence are therefore needed. Earth Observation big data such as the ones acquired by the Copernicus programme are providing unprecedented opportunities to detect changes and assess economic impacts in case of disasters. This article present the different results obtained by the multi-temporal methods using the Synthetic Aperture Radar images. The spaceborne Synthetic Aperture Radar (SAR) systems are suitable tools for flood mapping thanks to their daytime and nighttime and almost all-weather imaging capability, in addition to their sensitivity to surface roughness and to Flood monitoring. The method has been developed to exploit Sentinel-1 data. It has been tested for the 2018 flood of Tetouan (Morocco).