Comiti F., Bertoldi W., Cavalli M., Theule J., Trevisani S., 2014, Channel morphology through airborne LIDAR data_ recent advances from mountain streams to large rivers., 34th EARSeL Symposium_ European remote sensing - new opportunities for science and practice, Warsaw (Poland), 16-20 June 2014,
URL: http://www.cnr.it/prodotto/i/283127

Airborne Laser Scanner (ALS) surveys are widely used to obtain high-resolution DTMs to be used in natural hazards preventive analysis, e.g. flood and debris-flow modelling, as well as to reconstruct sediment budget through DoD (DEM of Difference) analysis, in particular in mountain basins after large events . In contrast, the use of ALS to capture the morphometric features of stream channels is less favorable as the infrared signal, characteristic of the most common LiDAR instruments, do not penetrate deep water bodies and thus do no permit to analyze the wet portion of channels. Yet, surveys carried out by these instruments can provide sufficient data to characterize and analyze morphometrically stream channels featuring either very shallow flows relative to bed roughness(e.g. steep mountain channels) or relatively limited wet areas (e.g. braided rivers). So far, very few investigations have deployed bathymetric LiDAR surveys, also known as green LiDAR, to map river systems. Bathymetric LiDAR has the potential to offer high-resolution DTMs for morphometric analysis in river systems complementary to those mentioned above (i.e. channels with perennial and substantial wet areas) and where bathymetric surveys using boats are not easily carried out due to fast and turbulent flows. These conditions are typical of mild-sloping, single-thread or wandering mountain rivers, widely distributed worldwide, in which detailed morphometric analysis are thus very challenging when carried out through traditional approaches. We will present a state of the art of morphometric analyses used to characterize channel morphology, including published and unpublished examples from step-pool channels as well as from sinuous-meandering and braided rivers, based on both infrared and green LiDAR data.

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