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Extraction of Water Information Based on SAR Radar and Optical Image Processing: Case of Flood Disaster in Southern Morocco

  • Sofia HakdaouiEmail author
  • Anas Emran
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Part of the Advances in Science, Technology & Innovation book series (ASTI)

Abstract

This study investigates the problem of detecting the extent of inundation caused by flash floods following heavy rainfall and the transport of sediments that cause the overflow of waters of the wadi on the crest of the Sakia El Hamra dam, the opening of two breaches in the body of the dam. The study area is focusing on Laayoune city in Southern Morocco in the region of Laayoune-Sakia el Hamra. The geomorphology of the area and the formation of the drainage network caused the creation of flash floods which took place from October 27 to 28, 2016, following intense and heavy rain in the region. Seven satellite images (radar and optical) taken before and after this event were processed to extract the most useful information. To achieve our objectives, this study began by preprocessing the radar images (calibration, speckle filtering, Doppler ground correction) and optics images (atmospheric correction, calibration of the radiometric and correction of geometric and topographic distortions). In this study, four spectral indices were extracted, then the change of detection approach is used on multispectral diachronic images from three MSI Sentinel-2 images and two Landsat-8 OLI imageries of before and after the disaster event. Normalized Difference Water Index “NDWI,” Normalized Difference Moisture Index “NDMI,” Normalized Multi-band Drought Index “NMDI” and Albedo “Al” provide a two-dimensional spectral feature space resulted which gives a very good power of discrimination to monitor the spatiotemporal evolution of the different levels of soil moisture in the area after the floods. The application of the coregistration and segmentation methods on radar Sentinel-1 images before and after the event completes this work. The results obtained show the importance of the complementarity multisensor imagery for the dynamic mapping of floods.

Keywords

SAR imaging processing Flood mapping Automatic change detection Segmentation Flash flood 

Résumé

Cette étude traite la problématique de détection de l’étendu des inondations causées par des crues subites à la suite de fortes pluies pluviales et le transport des sédiments causant le débordement des eaux de l’oued sur la crête du barrage de Sakia El Hamra, entraînant l’ouverture de deux brèches dans le corps du barrage. La zone d’étude se trouve dans le sud du Maroc dans la région de Laayoune—Sakia el Hamra spécialement la ville de Laayoune. La géomorphologie de la zone et la formation du réseau de drainage provoquent la création d’inondations rapides qui ont eu lieu du 27 au 28 octobre 2016 suite à des précipitations intenses et fortes qui se sont déversées sur la région. Sept images satellitaires Radar et optiques d’avant et d’après cet événement ont été traité pour extraire les informations les plus utiles. Pour atteindre nos objectifs, cette étude a débuté par le prétraitement du radar (calibrage, filtrage du speckle, correction du terrain doppler) et de l’optique (correction atmosphérique, étalonnage de la dérive radiométrique du capteur et correction des distorsions géométriques et topographiques). Quatre indices spectraux ont été extraits, suivis d’une détection de changement sur des images diachroniques multispectrales à partir de trois images sentinel-2 MSI et deux images Landsat-8 OLI acquises avant et après l’évènement. Les indices spectraux Normalized Difference Water Index “NDWI”, Normalized Difference Moisture Index “NDMI”, Normalized Difference Drought Index “NMDI” et l’Albedo “Al” fournissent un espace spectrale bidimensionnel formé par (Albedo, NDMI) qui donne un très bon pouvoir de discrimination permettant de suivre l’évolution spatio-temporel des différents niveaux d’humidité du sol dans la zone après les inondations. L’application des méthodes de coregistration et de segmentation sur les images Radar Sentinel-1 avant et après l’évènement complète ce travail. Les résultats obtenus montrent l’importance de la complémentarité de l’imagerie multi capteurs pour la cartographie dynamique des inondations.

Mots-clés

Traitement des images SAR Cartographie des inondations Détection automatique des changements Segmentation Inondation 

Notes

Acknowledgements

The authors would like to thank the University Mohammed V of Rabat and CRASTE-LF for their logistic support. We would like to thank the NASA-GLOVIS-GATE for the OLI and the MSI data.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Geo-Biodiversity and Natural Patrimony Laboratory, GeophysicsNatural Patrimony and Green Chemistry Research Center, Scientific Institute, Mohamed V UniversityRabatMorocco

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