Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry

Abstract

Quantifying the topography of rivers and their associated bedforms has been a fundamental concern of fluvial geomorphology for decades. Such data, acquired at high temporal and spatial resolutions, are increasingly in demand for process‐oriented investigations of flow hydraulics, sediment dynamics and in‐stream habitat. In these riverine environments, the most challenging region for topographic measurement is the wetted, submerged channel. Generally, dry bed topography and submerged bathymetry are measured using different methods and technology. This adds to the costs, logistical challenges and data processing requirements of comprehensive river surveys. However, some technologies are capable of measuring the submerged topography. Through‐water photogrammetry and bathymetric LiDAR are capable of reasonably accurate measurements of channel beds in clear water. While the cost of bathymetric LiDAR remains high and its resolution relatively coarse, the recent developments in photogrammetry using Structure from Motion (SfM) algorithms promise a fundamental shift in the accessibility of topographic data for a wide range of settings. Here we present results demonstrating the potential of so called SfM‐photogrammetry for quantifying both exposed and submerged fluvial topography at the mesohabitat scale. We show that imagery acquired from a rotary‐winged Unmanned Aerial System (UAS) can be processed in order to produce digital elevation models (DEMs) with hyperspatial resolutions (c. 0.02 m) for two different river systems over channel lengths of 50–100 m. Errors in submerged areas range from 0.016 m to 0.089 m, which can be reduced to between 0.008 m and 0.053 m with the application of a simple refraction correction. This work therefore demonstrates the potential of UAS platforms and SfM‐photogrammetry as a single technique for surveying fluvial topography at the mesoscale (defined as lengths of channel from c.10 m to a few hundred metres). Copyright © 2014 John Wiley & Sons, Ltd.

Application of Low-Cost Fixed-Wing UAV for Inland Lakes Shoreline Investigation

“…Using UAVs is now widespread across a range of disciplines (Anderson and Gaston 2013;Liu et al 2014;Smith et al 2016). The most popular environmental applications are: landslide monitoring (Lucieer et al 2014a), measuring changes in coastal morphology (Casella et al 2014;Gonçalves and Henriques 2015;Papakonstantinou et al 2016), monitoring glacier movement (Immerzeel et al 2014;Ryan et al 2015), studying Antarctic moss beds (Lucieer et al 2014b), soil erosion monitoring (d'Oleire-Oltmanns et al 2012), fluvial geomorphology (Mori et al 2002;Tamminga et al 2015;Woodget et al 2015) and forest research (Tang and Shao 2015;Wallace et al 2012). These studies are conducted using different UAV platforms delivered by various manufacturers (i.e., hybrid, flapping-wing, fixed-wing, coaxial, duct-fan, single rotor, and multi-rotor).…”

Technical note: Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an unmanned aerial vehicle

“…However, TLS suffers from similar limitations as lidar. Furthermore, the highly oblique scan angles of TLS make refraction effects more problematic (Woodget et al, 2015) and decrease returns from the bottom while increasing returns from the water surface (Bangen et al, 2014). Therefore, field surveys are normally performed using single-beam or multi-beam swath sonars transported on manned boats or more recently on unmanned vessels (e.g., Brown et al, 2010;Ferreira et al, 2009;Giordano et al, 2015) .…”

“…Bathymetry studies using UAVs are so far restricted to (i) spectral signature-depth correlation based on passive optical imagery (Flener et al, 2013;Lejot et al, 2007) or (ii) DEM (digital elevation model) generation through stereoscopic techniques from through-water pictures, correcting for the refractive index of water (Bagheri et al, 2015;Dietrich, 2016;Tamminga et al, 2014;Woodget et al, 2015).…”

“…UAV measurements of water depth (i.e., elevation of the water surface above the bed) can enrich the set of available hydrological observations along with measurements of water surface elevation (WSE), i.e., elevation of the water surface above sea level (Bandini et al, 2017;Ridolfi and Manciola, 2018;Woodget et al, 2015), and surface water flow (Detert and Weitbrecht, 2015;Tauro et al, 2015aTauro et al, , 2016Virili et al, 2015).…”

Rainfall simulation and Structure-from-Motion photogrammetry for the analysis of soil water erosion in Mediterranean vineyards

“…Remote-sensing technologies have proven to facilitate significantly the creation of high-resolution DEMs (Aucelli et al, 2016;Tarolli, 2014;Tarolli et al, 2015), and the availability of DEMs at multiple scales in terms of resolution but also temporal coverage is becoming essential to the understanding of global issues, such sediment production and anthropogenic changes to the Earth system, among others . The recent development of the photogrammetric technique 'Structure-from-Motion' (SfM) has confirmed to represent a valid and cheaper alternative to the established airborne and terrestrial lidar (Light Detection and Ranging) technology for measuring soil surface changes in different environments (Dandois and Ellis, 2013;Eltner et al, 2015;James and Robson, 2012;Masiero et al, 2015;Piermattei et al, 2016;Westoby et al, 2012;Whitehead et al, 2013;Woodget et al, 2015). All this information can shed light into the connectivity within the soil and water losses (López-Vicente et al, 2016;Marchamalo et al, 2016;Masselink et al, 2016).…”