Quantification of braided river channel change using archival digital image analysis

Abstract

Historical archives of grey-scale river channel imagery are extensive. Here, we present and test a methodology to extract detailed quantitative topographic date from such imagery of sand-bed rivers. Extracting elevation information from rivers is difficult as they are characterized by a low relative relief (less than 4 m); the area of interest may be spatially extensive (e.g. active channel widths > 500 m in large braided rivers); the rate of change of surface elevation is generally low except in the vicinity of individual channel banks where the rate of change is very high: there is the complication that comes from innundation: and there may be an added complication caused by blockage of the field of view by vegetation. Here, we couple archival photogrammetric techniques with image processing methods and test these for quantification of sand-bed braided river dynamics, illustrated for a 500 m wide, 3 km long reach of the Spouth Sasketchewan River, Canada. Digitial photogrammetry was used to quantify dry areas and water edge elevations. A methodology was then used to calibrate the special signature of inundated areas by combining established two media digital photogrammetric methods and image matching. This allowed determination of detailed depth maps for inundated area and, when combined with dry area data, creation of depths detectable from sequential digital elevation models. The result was a series of elevation models that demonstrate the potential for acquiring detailed and precise elevation data from any historical aerial imagery of rivers without needing associated calibration data, provided that imagery is of the necessary scale to capture the features of interest. We use these data to highlight several aspects of channel change on the South Saskatchewan River, including bar movement, bank erosion and channel infilling

Evidence of Bedform Superimposition and Flow Unsteadiness In Unit-Bar Deposits, South Saskatchewan River, Canada

“…The South Saskatchewan River was studied in detail in the 1970s (Cant 1978;Cant and Walker 1978) and was recently the subject of a large research project involving coring, 200 MHz GPR, differential GPS surveys, and time-series analysis of aerial photographs and the digital elevation models derived from them (Woodward et al 2003;Sambrook Smith et al 2005;Best et al 2006;Sambrook Smith et al 2006;Lane et al 2010;Sambrook Smith et al 2010;Ashworth et al in press). The slope heights of ripples, dunes, and unit bars ranged between 0.005 and 0.3 m in this study, and this is the same as the slope heights in recent flume experiments on the formation of cross strata (bedform slope heights of 0.005-0.25 m; Bridge 2007, 2009).…”

Topo-Bathymetric LiDAR for Monitoring River Morphodynamics and Instream Habitats—A Case Study at the Pielach River

“…Vegetation is often overhanging the river channel, but also two media need to be considered for the ray propagation: air and water. Sensing of water color with multi-or hyper-spectral remote sensing is one field of study, providing optical properties and near shore bathymetry [19][20][21][22][23] or water quality [24]. Airborne LiDAR, exploiting near infrared pulses for acquisition of point clouds over land surfaces, has proved to be a suitable method for the assessment of the 3-dimensional structure of vegetation [25][26][27] and terrain surface [28].…”

River morphology monitoring using multitemporal SAR data: preliminary results

“…Surian et al [2009] used aerial photographs to assess morphological effects of different discharges in a gravel-bed river. Some other authors employed passive optical sensors [Bertoldi et al, 2010;Lane et al, 2010], hyperspectral [Fonstad, 2012], or multispectral images [Bertoldi et al, 2011a] to detect channel morphological changes and analyze the dynamic of riparian vegetation. LiDAR (Light Detection And Ranging) was also used in combination with aerial photographs to observe the impact of riparian vegetation on channel forms [Bertoldi et al, 2011b], and in combination with high resolution multispectral images [Demarchi et al, 2016] to map the riverscape units.…”