Mapping riverbed sediment size from Sentinel‐2 satellite data

Abstract

A comprehensive understanding of river dynamics requires the grain size distribution of bed sediments and its variation across different temporal and spatial scales. Several techniques are already available for grain size assessment based on field and remotely sensed data. However, the existing methods are only applicable on small spatial scales and on short time scales. Thus, the operational measurement of grain size distribution of riverbed sediments at the catchment scale remains an open problem. A solution could be the use of satellite images as the main imaging platform. However, this would entail retrieving information at sub‐pixel scales. In this study, we propose a new approach to retrieve sub‐pixel scale grain size class information from Copernicus Sentinel‐2 imagery building upon a new image‐based grain size mapping procedure. Three Italian gravel‐bed rivers featuring different morphologies were selected for unmanned aerial vehicle (UAV) acquisitions, field surveys and laboratory analysis meant to serve as ground truth grain size data, ranging from medium sand to coarse gravel. Grain size maps on the river bars were generated in each study site by exploiting image texture measurements, upscaled and co‐registered with Sentinel‐2 data resolution. Relationships between the grain sizes measured and the reflectance values in Sentinel‐2 imagery were analysed using a machine learning framework. Results show statistically significant predictive models (MAE of ±8.34 mm and R2 = 0.92). The trained model was applied on 300 km of the Po River in Italy and allowed us to identify the gravel–sand transition occurring along this river length. Therefore, the approach presented here—based on freely available satellite data calibrated by low‐cost drone‐derived imagery—represents a promising step towards an automated surface mean grain size mapping over long river length, easily repeated through time for monitoring purposes.

Comparison of three grain size measuring methods applied to coarse-grained gravel deposits

“…Nowadays the flourishing use of uncrewed aerial vehicles (i.e., drones) allows simple and rapid surveys of large areas. This has proven an efficient method for the quantification of grain sizes (e.g., Carbonneau et al, 2018;Woodget et al, 2018;Marchetti et al, 2022). In the past years, applications of semi-automatic grain size measuring methods, where algorithms model ellipsoids around single grains, have gained an increasing popularity (Detert and Weitbrecht, 2012;Purinton and Bookhagen, 2019).…”

Introduction to the Women in Geomorphology special issue

“…• comparison of grain-size distributions from field measurements and remotely acquired images (Marchetti et al, 2022);…”

“…Remote sensing ( 26) Agostini et al, 2022;Atwood & West, 2022;Davies et al, 2022;Davis et al, 2021;Fadul et al, 2022;Gervasi et al, 2021;Hendrickx et al, 2022;Hodge & Buechel, 2022;Hooke, 2022;Hovenga et al, 2021;Konlechner & Hilton, 2022;Lefebvre et al, 2022;Marchetti et al, 2022;McKenzie et al, 2022;Mol & Grenfell, 2022;Opalka et al, 2022;Rabanaque et al, 2022;Regalla et al, 2022;Reitman et al, 2022;Sampietro-Vattuone et al, 2021;Schoch-Baumann et al, 2022;Thompson et al, 2022;Vah et al, 2022;Valentine et al, 2022;Zhang et al, 2022 Physical experiments (8) Bako et al, 2022;Bywater-Reyes et al, 2022;Demiral et al, 2022;Friedrich et al, 2022;Negreiros et al, 2022;Rachelly et al, 2022;Roelofs et al, 2022;Vah et al, 2022 Numerical models ( 11) Agostini et al, 2022;Bywater-Reyes et al, 2022;Cullen et al, 2022;Glover et al, 2022;Hodge & Buechel, 2022;Kooijma...…”

“…Field (26) Atkins et al, 2023;Bernatek-Jakiel & Nadal-Romero, 2023;Biausque et al, 2022;Brooks et al, 2022;Bywater-Reyes et al, 2022;Chin, 2022;Gervasi et al, 2021;Glover et al, 2022; Goodman et al, in press;Guiney & Lininger, 2022; Gurnell et al, 2022;Harvey et al, 2022;Hinshaw et al, 2022;Hooke, 2022;Konlechner & Hilton, 2022;Kooijman et al, 2022;Lane et al, 2022;Lefebvre et al, 2022;Marchetti et al, 2022;McKeon et al, 2022;Mol & Grenfell, 2022;Mossa & Chen, 2022;Opalka et al, 2022;Patton et al, 2022;Quock et al, 2022;Regalla et al, 2022;Reitman et al, 2022;Sampietro-Vattuone et al, 2021;Schoch-Baumann et al, 2022;Souza Fonseca et al, 2022;Spiske et al, 2022;Thompson et al, 2022;Uphues et al, 2022;Valentine et al, 2022;Van Soest et al, 2022;Wohl, 2022;Zhang et al, 2022 (Continues)…”

“…Many of the major research directions in contemporary geomorphology are reflected in this collection of papers. With respect to fluvial environments, including alluvial fans, individual papers examine use of images to detect sediment motion during physical experiments (Vah et al, 2022); comparison of grain‐size distributions from field measurements and remotely acquired images (Marchetti et al, 2022); physical experiments on bedload saltation under differing conditions (Demiral et al, 2022); numerical modelling of critical shear stress for grain entrainment based on imagery of bed‐rock channels (Hodge & Buechel, 2022); biogeomorphology (Bywater‐Reyes et al, 2022; Gurnell et al, 2022); channel morphology and classification (Lane et al, 2022), hydromorphology of ephemeral streams (Rabanaque et al, 2022) and interpretation of geomorphic unit assemblages (Fryirs & Brierley, 2022); flood effectiveness (Gervasi et al, 2021); channel evolution, terraces and sediment sources (Guyez et al, 2022) and the influence of sediment supply on gravel‐bed river widening (Rachelly et al, 2022); hydrological variation and meander morphodynamics (Hooke, 2022); the dynamics of wood in river corridors (Guiney & Lininger, 2022; Gurnell et al, 2022; Wohl, 2022) and numerical modelling of wood‐related processes (Friedrich et al, 2022); numerical model validation (Negreiros et al, 2022) and numerical modelling of groundwater‐driven network evolution (Cullen et al, 2022); base‐level controls and landscape evolution (Fadul et al, 2022); long‐term dryland channel response to urbanization (Chin, 2022); watershed restoration and management, including human alterations of process and form (Atkins et al, 2023; Davis et al, 2021; Goodman et al, in press; Gurnell et al, 2022; Hinshaw et al, 2022; Mossa & Chen, 2022; Sampietro‐Vattuone et al, 2021; Valentine et al, 2022); and alluvial fan dynamics (Opalka et al, 2022; Quock et al, 2022; Regalla et al, 2022; Schoch‐Baumann et al, 2022). Papers addressing process and form in coastal environments include examinations of dune morphodynamics and evolution (Hovenga et al,...…”