Remote sensing and geographic information system (GIS) methods were used for karst research in the coastal area of Northwest Morocco near the city of Safi in order to identify karst landscapes, to describe karst features and to detect geological structures relevant to karst development. The aim of this study was to investigate the use of different satellite data, such as Landsat, RapidEye and IKONOS imagery, as well as ASTER-and SRTM-derived digital elevation models (DEMs) for the analysis of karst features. Dolines were identified by visual interpretations based on high resolution satellite imagery and aerial photographs. Digital image processing of the satellite data, such as deriving vegetation and water index images, helped to identify regions with relatively higher surface water input, where karstification processes might be more intense than in surrounding areas. ArcGIS-integrated weighted overlay tools were used for this purpose as well by aggregating of morphometric, causal factors (lowest and flattest areas) influencing the susceptibility to higher surface water input. Lineament analysis based on the different satellite data contributed to the detection of near-surface fault and fracture zones with potential influence on dissolution processes in sub-terrain waterways.

The quality , data amount and information content of GeoInformation Systems (GIS) dealing with natural hazards and vulnerability assessment has increased considerably during the last decades. Meanwhile many countries have implemented such a GIS for the public use, whereby satellite imageries before and after disasters form important layers within these GIS. In the scope of this research adaptation strategies are developed by presenting an approach in which Geographic Information Systems, used together with remote sensing data, contribute to the analysis and presentation of information, especially required for the increasing geo-hazards in Morocco, such as earthquakes, mass movements and flooding using mainly free available, existing data for contributing to a GIS integrated data base.

The violent storms of 22-30 November 2014, resulted in flash floods and wadi floods (rivers) in large parts of Southern Morocco, at the foot of the Atlas Mountains. The Guelmim area was the most affected part with at least 32 fatalities and damages due to inundations. The flooding hazard in the Guelmim region initiated this study in order to investigate the use of remote sensing and geographic information system (GIS) for the detection and identification of areas most likely to be flooded in the future again due to their morphologic properties during similar weather conditions. By combining morphometric analysis and visual interpretation based on Landsat 8 satellite data and derived images such as water index (NDWI) images, areas with relatively higher soil moisture and recently deposited sediments were identified. The resulting maps of weighted overlay procedures, aggregating causal, morphometric factors influencing the susceptibility to flooding (lowest height levels, flattest areas), allowed for the distinguishing of areas with higher, medium and lower susceptibility to flooding. Thus, GIS and remote sensing tools contribut to the recognition and mapping of areas and infrastructure prone to flooding in the Guelmim area.

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