CDW photogrammetry of low relief fluvial features: accuracy and implications for reach-scale sediment budgeting

It is not new to recognize that data from remote sensing platforms is transforming the way we characterize and analyse our environment. The ability to collect continuous data spanning spatial scales now allows geomorphological research in a data rich environment and this special issue [coming just eight years after the 2010 special issue of Earth Surface Processes and Landforms (ESPL) associated with the remote sensing of rivers] highlights the considerable research effort being made to exploit this information, for studies of geomorphic form and process. The 2010 special issue on the remote sensing of rivers noted that fluvial remote sensing articles made up some 14% of the total river related articles in ESPL. A similar review of articles up to 2017 reveals that this figure has increased to around 25% with a recent proliferation of articles utilizing satellite-based data and structure from motion photogrammetry derived data. It is interesting to note, however that many studies published to date are proof of concept, concentrating on confirming the accuracy of the remotely sensed data at the expense of generating new insights and ideas on fluvial form and function. Data is becoming ever more precise and researchers should now be concentrating on analysing these early data sets to develop increased geomorphic insight, to challenge existing paradigms and to advance geomorphic science. The prospect of this occurring is increased by the fact that many of the new remote sensed platforms allow accurate spatial data to be collected cheaply and efficiently, reducing the need for substantial research funding to advance river science. Fluvial geomorphologists have never before been in such a liberated position. As techniques and analytical skills continue to improve it is inevitable that the prediction that remotely sensed data will revolutionize our understanding of geomorphological form and process will prove true, altering our ideas on the very nature of system functioning in the process.

Section: Introductionmentioning

confidence: 97%

Recent remote sensing applications for hydro and morphodynamic monitoring and modelling

Entwistle

Milan

2018

“…As a result, new insights are being offered into fluvial dynamics utilizing three-dimensional DEMs of the riverine environment (e.g. Lane et al, 1994;Milne and Sear, 1997;Heritage et al, 1998;Brasington et al, 2000;Fuller et al, 2005). Many of these studies continue to suffer area or resolution limitations due to a trade-off between spatial coverage and morphologic detail captured ( Figure 1): techniques such as terrestrial photogrammetry produce dense accurate morphometric data but aerial coverage is restricted; aerial photogrammetry offers increased spatial coverage but reduced elevation accuracy; EDM theodolite surveys suffer from long collecting times resulting in reduced data density if large areas are surveyed (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

Towards a protocol for laser scanning in fluvial geomorphology

Hetherington

2006

233

175

Advances in spatial analytical software allow digital elevation models (DEMs) to be produced which accurately represent landform surface variability and offer an important opportunity to measure and monitor morphological change and sediment transfer across a variety of spatial scales. Many of the techniques presently employed (aerial LIDAR, EDM theodolites, GPS, photogrammetry) suffer coverage or resolution limitations resulting in a trade-off between spatial coverage and morphologic detail captured. This issue is particularly important when rates of spatial and temporal change are considered for fluvial systems. This paper describes the field and processing techniques required for oblique laser scanning to acquire 0·01 m resolution digital elevation data of an upland reach of the River Wharfe in the UK. The study site is variable with rapidly changing morphology, diverse vegetation and the presence of water, and these are evaluated with respect to laser data accuracy. Scan location, frequency and distance are discussed with reference to survey accuracy and efficiency, and a field protocol is proposed. Scan data cloud merging was achieved with a high degree of precision (sub-centimetre) and positional data are shown to be very accurate for exposed surfaces. Vegetation and water decrease the accuracy, as the laser pulse is often prevented from reaching the ground surface or is not returned.

“…Recent developments have led to the production of high resolution DEMs of fluvial environments (e.g. Lane et al, 1994;Milne and Sear, 1997;Heritage et al, 1998;Brasington et al, 2000;Eaton and Lapointe, 2001), where acquisition of high-resolution topographic information is central to effective construction of such DEMs (Westaway et al, 2000). However, it is important to note that volumes derived from morphological budgeting represent lower-bound estimates of sediment transfer.…”

Section: Introductionmentioning

confidence: 99%

Reach‐scale sediment transfers: an evaluation of two morphological budgeting approaches

Fuller

Large

Charlton

et al. 2003

136

146

This paper compares two approaches used to derive measures of annual sediment transfers within a 1 km long piedmont reach of the gravel-bed River Coquet in Northumberland, northern England. The techniques utilize: (i) channel planform and cross-section surveys based on a theodolite/electronic distance measurement (EDM) survey of 21 monumented channel cross-sections and channel and gravel bar margins; and (ii) theodolite-EDM survey generating a series of x,y,z coordinates, from which digital elevation models (DEMs) of the reach were constructed. Calculating the difference between DEM surfaces provided a measure of volumetric change between surveys carried out during the spring of 1999 and 2000. The use of kriging in DEM generation and differencing permits computation of estimate variances and confidence intervals for sediment transfer. Error analysis, validating the DEMs using surveyed cross-sections, indicated a mean error between surveyed and DEM-generated cross-sections of around twice the value of the D 50 of the surface sediment in the reach. Comparison of sediment volumes derived from the two approaches suggests that, compared with the DEM method, monumented cross-sections underestimate the magnitude of volumetric changes that occur within the reach. The cross-section approach relies on a simplistic integration of the volumes, whereas DEM differencing provides an estimate at a resolution under the control of the analyst. Furthermore, the cross-section approach does not permit a reliable estimate of the uncertainty of the volumes calculated. In addition, the DEM methodology based on the morphological unit scale provides an explicit identification of spatial patterns of erosion and deposition, a feature that cross-section-based approaches may fail to include.