Accurate flood mapping is important for both planning activity during emergencies and as a support for the successive assessment of damaged areas. A valuable information source for such a procedure can be remote sensing synthetic aperture radar (SAR) imagery. However, flood scenarios are typical examples of complex situations in which different factors have to be considered to provide accurate and robust interpretation of the situation on the ground. For this reason, a data fusion approach of remote sensing data with ancillary information can be particularly useful. In this work, a Bayesian Network (BN) is proposed to integrate remotely sensed data, such as multi-temporal SAR intensity images and InSAR coherence data, with geomorphic and other ground information. The methodology is tested on a case study regarding a flood occurred in the Basilicata region (Italy) on December 2013, monitored using a time series of COSMO-SkyMed data. It is shown that the synergetic use of different information layers can help to detect more precisely the areas affected by the flood, reducing false alarms and missed identifications which may affect algorithms based on data from a single source. The produced flood maps are compared to data obtained independently from the analysis of optical images; the comparison indicates that the proposed methodology is able to reliably follow the temporal evolution of the phenomenon, assigning high probability to areas most likely to be flooded, in spite of their heterogeneous temporal SAR/InSAR signatures, reaching accuracies of up to 89%

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The continuous feedbacks among tectonics, surface processes, and climate are reflected in the distribution of catchments on active mountain ranges. Previous studies have shown a regularity of valley spacing across mountain ranges worldwide, but the origin of this geomorphological feature is currently not well known. In this work, we use a landscape evolution model to investigate the process of fluvial network organization and the evolution of regular ridge-and-valley patterns on simulated mountain ranges. In particular, we investigate the behavior of such patterns when subjected to a perturbation in landscape processes from a previous steady state, resulting from a sudden variation in the pattern of bedrock erodibility, from homogeneous to a gradient. We analyze the time evolution of the mean ratio λ' between the linear spacing of adjacent valleys and the half width of the mountain range. We show how a valley spacing ratio of~0.5 is first achieved at steady state under uniform bedrock erodibility. After applying the gradient of bedrock erodibility across the landscape, we observe that λ' first increases and then decreases to a new steady-state value that is smaller than the original value. A detailed analysis of the simulations, through observations of surface 'snapshots' at repeated time intervals, allows to gain some insight into the mechanisms governing this fluvial network reorganization process, driven by the migration of the main divide toward the side characterized by lower bedrock erodibility. On both sides of the range the new steady-state valley spacing is obtained through mechanisms of catchment reorganization and competition between adjacent fluvial networks. In particular, catchment reorganization is characterized by the growth of smaller catchments between shrinking larger catchments on the side with lower erodibility, and the growth of larger catchments on the side with higher erodibility.