Fostering a regional vision on river systems by remote sensing

Abstract:

River classification and the derived knowledge about river systems have been relying until recently on discontinuous field campaigns and visual interpretation of aerial images. For this reason, building a regional vision on river systems based on a systematic and coherent set of hydromorphological indicators was, and still is, a research challenge. Remote sensing data, since some years, offer notable opportunities to shift this paradigm offering an unprecedented amount of spatially distributed data over large scales, such as regional. Here, we have implemented a river characterization framework based on color infrared orthophotos at 40 cm and a LIDAR derived DTM at 5 m acquired simultaneously in 2009-2010 for all Piedmont Region Italy (25400 kmq). 1500 km of river systems have been characterized in terms typology, geometry and topography of hydromorphological features. The framework delineates the valley bottom of each river course, and maps by a semi-automated procedure water channels, unvegetated and vegetated sediment bars, islands, and riparian corridors. Using a range of statistical techniques the river systems have been segmented and classified with an objective, quantitative, and then repeatable approach. Such regional database enhances our ability to address a number of research and management challenges, such as: i) quantify shape and topography of channel forms for different river functional types, and investigate their relationships with potential drivers like hydrology, geology, land use and historical contingency; ii) localize most degraded and better functioning river stretches so to prioritize finer scale monitoring and set quantifiable restoration targets; iii) provide indication for future RS acquisition campaigns so to start monitoring river processes at the regional scale. The Piedmont Region in Italy is here used as a laboratory of concrete examples and analyses to discuss our current ability to answer to these challenges in river science.