Regional hydromorphological characterization with continuous and automated remote sensing analysis based on VHR imagery and low‐resolution LiDAR data. Issue 3 (29th January 2017)

• Record Type: Journal Article
• Authors: Demarchi, Luca; Bizzi, Simone; Piégay, Hervé
• Is Part Of: Earth surface processes and landforms. Volume 42:Issue 3(2017)
• Page Start: 531
• Page End: 551
• Publication Date: 2017-01-29
• Subjects: VHR and LiDAR data -- object‐based classification -- regional scale -- hydromorphological characterization; Geomorphology -- Periodicals; 551.4
• DOI: 10.1002/esp.4092
• Languages: English
• ISSNs: 0197-9337

Abstract

Abstract: Recent developments in remote sensing (RS) technologies lead the way in characterizing river morphology at regional scales and inferring potential channel responses to human pressures. In this paper, a unique regional database of continuous hydromorphological variables (HyMo DB) based on areal and topographic data has been generated from RS analysis. Key riverscape units with specific geomorphic meaning have been automatically mapped for 1700 km 2 of river floodplains from simultaneous very‐high‐resolution (VHR) near‐infrared aerial imagery and low‐resolution LiDAR‐derived products. A multi‐level, geographical object‐based architecture (GEOBIA) was employed to integrate both spectral and topographic information and generate a regional classifier able to automatically map heterogeneous fluvial patterns in different geographical and topographical contexts of the Piedmont Region (Italy). This HyMo‐generated DB offers a unique set of tools for hydromorphologists and can be exploited for different purposes. For the first time, topographic information can be exploited regionally per riverscape unit class, allowing for quantitative analysis of their regional spatial and statistical variability. In this manner, river types can be automatically characterized and classified using objective and repeatable hydromorphological variables. We discuss the potential of quantifying functional links between riverscape units and their driving processes, a valuable source of information to start assessing and highlighting the entity of potential channel adjustments at the regional scale to human pressures. The HyMo DB can also be integrated with historical, field‐based information to better comprehend current fluvial changes at a local scale. In view of future RS acquisitions, the present approach will result in a suitable procedure for quantitative, objective and continuous monitoring of river evolutions over large scales. This type of hydromorphological characterization will allow regional trends and patterns to be highlighted through time and river management strategies to thus be implemented at both regional and local scales. Copyright © 2016 John Wiley & Sons, Ltd.