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Flood detection and monitoring is increasingly important, especially on remote areas such as African tropical river basins, where ground investigations are difficult. We present an experiment aimed at integrating multi-temporal and multi-source data from the Sentinel-1 and ALOS 2 synthetic aperture radar (SAR) sensors, operating in C band, VV polarization, and L band, HH and HV polarizations, respectively. Information from the globally available CORINE land cover dataset, derived over Africa from the Proba V satellite, and available publicly at the resolution of 100 m, is also exploited. Integrated multi-frequency, multi-temporal, and multi-polarizations analysis allows highlighting different drying dynamics for floodwater over various land cover classes, such as herbaceous vegetation, wetlands, and forests. They also enable detection of different scattering mechanisms, such as double bounce interaction of vegetation stems and trunks with underlying floodwater, giving precious information about the distribution of flooded areas among the different ground cover types present on the site. The approach is validated through visual analysis from Google EarthTM imagery. This kind of integrated analysis, exploiting multi-source remote sensing to partially make up for the unavailability of reliable ground truth, is expected to assume increasing importance as constellations of satellites, observing the Earth in different electromagnetic radiation bands, will be available.

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Sediment connectivity is considered a powerful geomorphic indicator for defining the most sensitive areas to geomorphological modifications in a fluvial catchment (hotspots). This encourages the development of methods and models for its assessment, to investigate the interrelation of the various phenomena that occur in a river basin (landslides, floods, etc.). This work explores the potential connection of the processes in flood dynamics, by focusing on induced flood hazard, in order to evaluate the applicability of sediment connectivity to flood monitoring. By applying the recently developed sediment flow connectivity index (SCI) computation method to the Severn River basin, in UK, recurrently affected by floods, we investigate the agreement between the hotspot areas (described by the index) and the areas recurrently flooded (as mapped by aerial photography, satellite imagery and hydrodynamic modelling). Qualitative and quantitative approaches are used for the analysis of past (March 2007 and January 2010) as well as predicted (with return periods of 200 and 500 years) flood events. The results show a good correspondence of areas of high sediment connectivity with flood occurrence. Moreover, the detection performance of the SCI is slightly better than that of a simple flow accumulation map, confirming the importance of the initial mapping of sediment availability and mobility. This experiment extends the direct applicability of the SCI from fluvial analysis to flood monitoring, thus opening interesting future scenarios.

Digital elevation models (DEMs) represent a fundamental resource in geomorphological analysis. The increasing availability of open-access DEMs over wide areas is advantageous, but requires an evaluation of DEM quality and errors. This work applies a hierarchical assessment of global, continental and national DEMs in Italy in order to explore