Topographic structure from motion: a new development in photogrammetric measurement

The production of topographic datasets is of increasing interest and application throughout the geomorphic sciences, and river science is no exception. Consequently, a wide range of topographic measurement methods have evolved. Despite the range of available methods, the production of high resolution, high quality digital elevation models (DEMs) requires a significant investment in personnel time, hardware and/or software. However, image‐based methods such as digital photogrammetry have been decreasing in costs. Developed for the purpose of rapid, inexpensive and easy three‐dimensional surveys of buildings or small objects, the ‘structure from motion’ photogrammetric approach (SfM) is an image‐based method which could deliver a methodological leap if transferred to geomorphic applications, requires little training and is extremely inexpensive. Using an online SfM program, we created high‐resolution digital elevation models of a river environment from ordinary photographs produced from a workflow that takes advantage of free and open source software. This process reconstructs real world scenes from SfM algorithms based on the derived positions of the photographs in three‐dimensional space. The basic product of the SfM process is a point cloud of identifiable features present in the input photographs. This point cloud can be georeferenced from a small number of ground control points collected in the field or from measurements of camera positions at the time of image acquisition. The georeferenced point cloud can then be used to create a variety of digital elevation products. We examine the applicability of SfM in the Pedernales River in Texas (USA), where several hundred images taken from a hand‐held helikite are used to produce DEMs of the fluvial topographic environment. This test shows that SfM and low‐altitude platforms can produce point clouds with point densities comparable with airborne LiDAR, with horizontal and vertical precision in the centimeter range, and with very low capital and labor costs and low expertise levels. Copyright © 2012 John Wiley & Sons, Ltd.     

Time lapse structure‐from‐motion photogrammetry for continuous geomorphic monitoring

Recent advances are made in earth surface reconstruction with high spatial resolution due to SfM photogrammetry. High flexibility of data acquisition and high potential of process automation allows for a significant increase of the temporal resolution, as well, which is especially interesting to assess geomorphic changes. Two case studies are presented where 4D reconstruction is performed to study soil surface changes at 15 seconds intervals: (a) a thunderstorm event is captured at field scale and (b) a rainfall simulation is observed at plot scale. A workflow is introduced for automatic data acquisition and processing including the following approach: data collection, camera calibration and subsequent image correction, template matching to automatically identify ground control points in each image to account for camera movements, 3D reconstruction of each acquisition interval, and finally applying temporal filtering to the resulting surface change models to correct random noise and to increase the reliability of the measurement of signals of change with low intensity. Results reveal surface change detection with cm‐ to mm‐accuracy. Significant soil changes are measured during the events. Ripple and pool sequences become obvious in both case studies. Additionally, roughness changes and hydrostatic effects are apparent along the temporal domain at the plot scale. 4D monitoring with time‐lapse SfM photogrammetry enables new insights into geomorphic processes due to a significant increase of temporal resolution. Copyright © 2017 John Wiley & Sons, Ltd.     

Camera system considerations for geomorphic applications of SfM photogrammetry

The availability of high‐resolution, multi‐temporal, remotely sensed topographic data is revolutionizing geomorphic analysis. Three‐dimensional topographic point measurements acquired from structure‐from‐motion (SfM) photogrammetry have been shown to be highly accurate and cost‐effective compared to laser‐based alternatives in some environments. Use of consumer‐grade digital cameras to generate terrain models and derivatives is becoming prevalent within the geomorphic community despite the details of these instruments being largely overlooked in current SfM literature. A practical discussion of camera system selection, configuration, and image acquisition is presented. The hypothesis that optimizing source imagery can increase digital terrain model (DTM) accuracy is tested by evaluating accuracies of four SfM datasets conducted over multiple years of a gravel bed river floodplain using independent ground check points with the purpose of comparing morphological sediment budgets computed from SfM‐ and LiDAR‐derived DTMs. Case study results are compared to existing SfM validation studies in an attempt to deconstruct the principle components of an SfM error budget. Greater information capacity of source imagery was found to increase pixel matching quality, which produced eight times greater point density and six times greater accuracy. When propagated through volumetric change analysis, individual DTM accuracy (6–37 cm) was sufficient to detect moderate geomorphic change (order 100 000 m³) on an unvegetated fluvial surface; change detection determined from repeat LiDAR and SfM surveys differed by about 10%. Simple camera selection criteria increased accuracy by 64%; configuration settings or image post‐processing techniques increased point density by 5–25% and decreased processing time by 10–30%. Regression analysis of 67 reviewed datasets revealed that the best explanatory variable to predict accuracy of SfM data is photographic scale. Despite the prevalent use of object distance ratios to describe scale, nominal ground sample distance is shown to be a superior metric, explaining 68% of the variability in mean absolute vertical error. Published 2016. This article is a U.S. Government work and is in the public domain in the USA     

Cost‐effective non‐metric photogrammetry from consumer‐grade sUAS: implications for direct georeferencing of structure from motion photogrammetry

The declining costs of small Unmanned Aerial Systems (sUAS), in combination with Structure‐from‐Motion (SfM) photogrammetry have triggered renewed interest in image‐based topography reconstruction. However, the potential uptake of sUAS‐based topography is limited by the need for ground control acquired with expensive survey equipment. Direct georeferencing (DG) is a workflow that obviates ground control and uses only the camera positions to georeference the SfM results. However, the absence of ground control poses significant challenges in terms of the data quality of the final geospatial outputs. Notably, it is generally accepted that ground control is required to georeference, refine the camera calibration parameters, and remove any artefacts of optical distortion from the topographic model. Here, we present an examination of DG carried out with low‐cost consumer‐grade sUAS. We begin with a study of surface deformations resulting from systematic perturbations of the radial lens distortion parameters. We then test a number of flight patterns and develop a novel error quantification method to assess the outcomes. Our perturbation analysis shows that there exists families of predictable equifinal solutions of K₁‐K₂ which minimize doming in the output model. The equifinal solutions can be expressed as K₂ = f (K₁) and they have been observed for both the DJI Inspire 1 and Phantom 3 sUAS platforms. This equifinality relationship can be used as an external reliability check of the self‐calibration and allow a DG workflow to produce topography exempt of non‐affine deformations and with random errors of 0.1% of the flying height, linear offsets below 10 m and off‐vertical tilts below 1°. Whilst not yet of survey‐grade quality, these results demonstrate that low‐cost sUAS are capable of producing reliable topography products without recourse to expensive survey equipment and we argue that direct georeferencing and low‐cost sUAS could transform survey practices in both academic and commercial disciplines. Copyright © 2016 John Wiley & Sons, Ltd.     

3‐D uncertainty‐based topographic change detection with structure‐from‐motion photogrammetry: precision maps for ground control and directly georeferenced surveys

Structure‐from‐motion (SfM) photogrammetry is revolutionising the collection of detailed topographic data, but insight into geomorphological processes is currently restricted by our limited understanding of SfM survey uncertainties. Here, we present an approach that, for the first time, specifically accounts for the spatially variable precision inherent to photo‐based surveys, and enables confidence‐bounded quantification of 3D topographic change. The method uses novel 3D precision maps that describe the 3D photogrammetric and georeferencing uncertainty, and determines change through an adapted state‐of‐the‐art fully 3D point‐cloud comparison (M3C2), which is particularly valuable for complex topography. We introduce this method by: (1) using simulated UAV surveys, processed in photogrammetric software, to illustrate the spatial variability of precision and the relative influences of photogrammetric (e.g. image network geometry, tie point quality) and georeferencing (e.g. control measurement) considerations; (2) we then present a new Monte Carlo procedure for deriving this information using standard SfM software and integrate it into confidence‐bounded change detection; before (3) demonstrating geomorphological application in which we use benchmark TLS data for validation and then estimate sediment budgets through differencing annual SfM surveys of an eroding badland. We show how 3D precision maps enable more probable erosion patterns to be identified than existing analyses, and how a similar overall survey precision could have been achieved with direct survey georeferencing for camera position data with precision half as good as the GCPs'. Where precision is limited by weak georeferencing (e.g. camera positions with multi‐metre precision, such as from a consumer UAV), then overall survey precision can scale as n^‐½ of the control precision (n = number of images). Our method also provides variance–covariance information for all parameters. Thus, we now open the door for SfM practitioners to use the comprehensive analyses that have underpinned rigorous photogrammetric approaches over the last half‐century. Copyright © 2017 John Wiley & Sons, Ltd.     

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

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.     

Evaluating river morphology change with a geomorphic form variation approach

Geomorphic river design strives for natural resilience by encouraging geomorphic form complexity and morphological processes linked to greater habitat diversity. Increasing availability of high-resolution topographic data and spatial feature mapping methods provide advantages for morphological analysis and river restoration planning. We propose and evaluate an approach to quantifying topographic variability of geomorphic form and pixel-level surface roughness resulting from channel planform geometry differences using spatially continuous variety computation applied to component metrics including flow direction, aspect and planform curvature. We define this as the geomorphic form variation (GFV) approach and found it scalable, repeatable and a multi-stage analytical metric for quantifying physical aspects of river-bed topographic variability. GFV may complement process-based morphological feature mapping applications, hydraulic assessment indices and spatial habitat heterogeneity metrics commonly used for ecological quality evaluation and river restoration. The GFV was tested on controlled synthetic channels derived from River Builder software and quasi-controlled sinuous planform flume experiment channels. Component variety metrics respond independently to specific geometric surface changes and are sensitive to multi-scaled morphology change, including coarser-grained sediment distributions of pixel-level surface roughness. GFV showed systematic patterns of change related to the effects of channel geometry, vertical bed feature (pool-bar) frequency and amplitude, and bar size, shape and orientation. Hotspot analysis found that bar margins were major components of topographic complexity, whereas grain-scale variety class maps further supported the multi-stage analytical capability and scalability of the GFV approach. The GFV can provide an overall variety value that may support river restoration decision-making and planning, particularly when geomorphic complexity enhancement is a design objective. Analysing metric variety values with statistically significant hotspot cluster maps and complementary process-based software and mapping applications allows variety correspondence to systematic feature changes to be assessed, providing an analytical approach for river morphology change comparison, channel design and geomorphic process restoration.     

Geomorphic process from topographic form: automating the interpretation of repeat survey data in river valleys

The ability to quantify the processes driving geomorphic change in river valley margins is vital to geomorphologists seeking to understand the relative role of transport mechanisms (e.g. fluvial, aeolian, and hillslope processes) in landscape dynamics. High‐resolution, repeat topographic data are becoming readily available to geomorphologists. By contrasting digital elevation models derived from repeat surveys, the transport processes driving topographic changes can be inferred, a method termed ‘mechanistic segregation.’ Unfortunately, mechanistic segregation largely relies on subjective and time consuming manual classification, which has implications both for its reproducibility and the practical scale of its application. Here we present a novel computational workflow for the mechanistic segregation of geomorphic transport processes in geospatial datasets. We apply the workflow to seven sites along the Colorado River in the Grand Canyon, where geomorphic transport is driven by a diverse suite of mechanisms. The workflow performs well when compared to field observations, with an overall predictive accuracy of 84% across 113 validation points. The approach most accurately predicts changes due to fluvial processes (100% accuracy) and aeolian processes (96%), with reduced accuracy in predictions of alluvial and colluvial processes (64% and 73%, respectively). Our workflow is designed to be applicable to a diversity of river systems and will likely provide a rapid and objective understanding of the processes driving geomorphic change at the reach and network scales. We anticipate that such an understanding will allow insight into the response of geomorphic transport processes to external forcings, such as shifts in climate, land use, or river regulation, with implications for process‐based river management and restoration. Copyright © 2017 John Wiley & Sons, Ltd.     

Robotic photosieving from low‐cost multirotor sUAS: a proof‐of‐concept

Measurement of riverbed material grain sizes is now a routine part of fieldwork in fluvial geomorphology and lotic ecology. In the last decade, several authors have proposed remote sensing approaches of grain size measurements based on terrestrial and aerial imagery. Given the current rise of small unmanned aerial system (sUAS) applications in geomorphology, there is now increasing interest in the application of these remotely sensed grain size mapping methods to sUAS imagery. However, success in this area has been limited owing to two fundamental problems: lack of constraint of image scale for sUAS imagery and blurring effects in sUAS images and resulting orthomosaics. In this work, we solve the former by showing that SfM‐photogrammetry can be used in a direct georeferencing (DG) workflow (i.e. with no ground validation) in order to predict image scale within margins of 3%. We then propose a novel approach of robotic photosieving of dry exposed riverbed grains that relies on near‐ground images acquired from a low‐cost sUAS and which does not require the presence of ground control points or visible scale objects. We demonstrate that this absence of scale objects does not affect photosieving outputs thus resulting in a low‐cost and efficient sampling method for surficial grains. Copyright © 2017 John Wiley & Sons, Ltd.     

Stream channel erosion in a rapidly urbanizing region of the US–Mexico border: documenting the importance of channel hardpoints with Structure‐from‐Motion photogrammetry

Urbanization can lead to accelerated stream channel erosion, especially in areas experiencing rapid population growth, unregulated urban development on erodible soils, and variable enforcement of environmental regulations. A combination of field surveys and Structure‐from‐Motion (SfM) photogrammetry techniques was used to document spatial patterns in stream channel geometry in a rapidly urbanizing watershed, Los Laureles Canyon (LLCW), in Tijuana, Mexico. Ground‐based SfM photogrammetry was used to map channel dimensions with 1 to 2 cm vertical mean error for four stream reaches (100–300 m long) that were highly variable and difficult to survey with a differential GPS. Regional channel geometry curves for LLCW had statistically larger slopes and intercepts compared with regional curves developed for comparable, undisturbed reference channels. Cross‐sectional areas of channels downstream of hardpoints, such as concrete reaches or culverts, were up to 64 times greater than reference channels, with enlargement persisting, in some cases, up to 230 m downstream. Percentage impervious cover was not a good predictor of channel enlargement. Proximity to upstream hardpoint, and lack of riparian and bank vegetation paired with highly erodible bed and bank materials may account for the instability of the highly enlarged and unstable cross‐sections. Channel erosion due to urbanization accounts for approximately 25–40% of the total sediment budget for the watershed, and channel erosion downstream of hardpoints accounts for one‐third of all channel erosion. Channels downstream of hardpoints should be stabilized to prevent increased inputs of sediment to the Tijuana Estuary and local hazards near the structures, especially in areas with urban settlements near the stream channel. Copyright © 2017 John Wiley & Sons, Ltd.     

Combining historical and process perspectives to infer ranges of geomorphic variability and inform river restoration in a wandering gravel‐bed river

Restoration approaches such as dam removal and channel reconstruction have moved beyond the realm of small streams and are being applied to larger rivers. This development has substantial economic and ecological implications but may test gaps in our understanding of larger river systems and of restoration science. We examine how information about historical ranges of geomorphic variability can inform stream restoration in the context of the Clark Fork River, Montana, focusing on a study reach where one of the largest restoration projects to date was implemented, upstream of the recently removed Milltown Dam. Analysis of historical sources and aerial photographs of the Clark Fork River's pre‐mining, mining, and more recent history suggest that a wandering channel pattern has persisted despite variations in sediment supply and transport capacity. Predictive metrics for channel pattern also suggest a wandering pattern, transitional between braided and meandering, in this geomorphic setting. These analyses suggest that the creation of a single‐thread meandering channel, which incorporates structures to limit erosion and channel movement, is inconsistent with the historical range of variability in this reach. The perils of restoring channels to a condition different than the historical range of variability for their geomorphic setting were illustrated on the Clark Fork by flood‐induced avulsions of the restored channel that occurred soon after project construction. Application of an experimental approach to restoration, founded on the method of multiple working hypotheses, provides a means for embracing uncertainty, can maximize the potential for site‐specific restoration success, and can foster advances in restoration science. Copyright © 2012 John Wiley & Sons, Ltd.     

Drone photogrammetry and KMeans point cloud filtering to create high resolution topographic and inundation models of coastal sediment archives

Coastal areas are vulnerable to the impacts of tropical cyclones (TC), tsunamis and other water super‐elevation events, but the frequency of these events is often poorly represented by conventional records. Coastal overwash deposits (including washover fans) can provide a longer‐term archive of event frequency. Because of their low‐gradient geomorphic form, washover fans require high accuracy (centimetre‐resolution) topographic models to understand patterns of connectivity and dynamics that control archive formation. Using images collected by a remotely piloted aircraft system (RPAS, or ‘drone’) and Structure‐from‐Motion (SfM) photogrammetry techniques, we apply a novel point‐cloud filtering technique based on KMeans classification of the R‐G‐B colour of each X‐Y‐Z point to remove vegetation and create a centimetre‐resolution and accuracy bare‐earth digital terrain model (DTM) of a washover fan in Exmouth Gulf (Western Australia). Using the RPAS‐SfM orphophoto and DEM data, supported by ground‐penetrating radar (GPR) and field stratigraphic analysis, we show how this approach can be applied to understand dynamics controlling low‐gradient geomorphic landforms, using an example of a washover fan sedimentary archive in northwestern Australia created by extreme overwash events. Our approach reveals the likely role of backflooding and terrestrial runoff in creating backwater environment for sub‐aqueous deposition and good sediment preservation and identifies key areas to target for detailed dating and stratigraphic analysis of a potentially decadal to sub‐millennial resolution sediment archive of TC activity. Copyright © 2018 John Wiley & Sons, Ltd.     

Bathymetric Structure‐from‐Motion: extracting shallow stream bathymetry from multi‐view stereo photogrammetry

Stream bathymetry is a critical variable in a number of river science applications. In larger rivers, bathymetry can be measured with instruments such as sonar (single or multi‐beam), bathymetric airborne LiDAR (light detection and ranging), or acoustic Doppler current profilers. However, in smaller streams with depths less than 2 m, bathymetry is one of the more difficult variables to map at high‐resolution. Optical remote sensing techniques offer several potential solutions for collecting high‐resolution bathymetry. In this research, I focus on direct photogrammetric measurements of bathymetry using multi‐view stereo photogrammetry, specifically Structure‐from‐Motion (SfM). The main barrier to accurate bathymetric mapping with any photogrammetric technique is correcting for the refraction of light as it passes between the two different media (air and water), which causes water depths to appear shallower than they are. I propose and test an iterative approach that calculates a series of refraction correction equations for every point/camera combination in a SfM point cloud. This new method is meant to address shortcomings of other correction techniques and works within the current preferred method for SfM data collection, oblique and highly convergent photographs. The multi‐camera refraction correction presented here produces bathymetric datasets with accuracies of ~0.02% of the flying height and precisions of ~0.1% of the flying height. This methodology, like many fluvial remote sensing methods, will only work under ideal conditions (e.g. clear water), but it provides an additional tool for collecting high‐resolution bathymetric datasets for a variety of river, coastal, and estuary systems. Copyright © 2016 John Wiley & Sons, Ltd.     

USING UNMANNED AERIAL VEHICLE PHOTOGRAMMETRY TECHNOLOGY TO OBTAIN QUANTITATIVE PARAMETERS OF ACTIVE TECTONICS

With the development of photogrammetry technology and the popularity of unmanned aerial vehicles (UAVs)technology in recent years, using UAV photogrammetry technology to rapidly acquire high precision and high resolution topographic and geomorphic data on the fault zone has gradually become an important technical means. This paper first summarizes the basic principle and workflow of a new digital photogrammetry technology, SfM (Structure from Motion), which is simple, efficient and low cost. Using this technology, we conducted aerial image acquisition and data processing for a typical fault landform on the northern of Caka Basin in Qinghai. The digital elevation model (DEM)with 6.1cm/pix resolution is generated and the density of point cloud is as high as 273 points/m². The coverage area is 0.463km². Further, the terrain and slope data parallel to the fault direction are extracted by topographic analysis method, and combined with the contour map and the slope diagram generated by the DEM, a fine interpretation and quantitative study of complex multilevel geomorphic surfaces is carried out. Finally, based on the results of sophisticated interpretation of geomorphology, we got the vertical displacements of the T₁ terrace to the T₃ terrace as (1.01±0.06)m, (1.37±0.13)m and (3.10±0.11)m, and the minimum vertical displacements of the T₄ terrace and the T₅ terrace as (3.77±0.14)m and (5.46±0.26)m, respectively, through the topographic profile data extracted by DEM. Such vertical displacement parameters are difficult to obtain directly by traditional remote sensing images, which shows the great application prospect of UAV photogrammetry technology in the quantitative study of active tectonics.     

Bank erosion in agricultural drainage networks: new challenges from structure‐from‐motion photogrammetry for post‐event analysis

Drainage channels are an integral part of agricultural landscapes, and their impact on catchment hydrology is strongly recognized. In cultivated and urbanized floodplains, channels have always played a key role in flood protection, land reclamation, and irrigation. Bank erosion is a critical issue in channels. Neglecting this process, especially during flood events, can result in underestimation of the risk in flood‐prone areas. The main aim of this work is to consider a low‐cost methodology for the analysis of bank erosion in agricultural drainage networks, and in particular for the estimation of the volumes of eroded and deposited material. A case study located in the Veneto floodplain was selected. The research is based on high‐resolution topographic data obtained by an emerging low‐cost photogrammetric method (structure‐from‐motion or SfM), and results are compared to terrestrial laser scanning (TLS) data. For the SfM analysis, extensive photosets were obtained using two standalone reflex digital cameras and an iPhone5® built‐in camera. Three digital elevation models (DEMs) were extracted at the resolution of 0.1 m using SfM and were compared with the ones derived by TLS. Using the different DEMs, the eroded areas were then identified using a feature extraction technique based on the topographic parameter Roughness Index (RI). DEMs derived from SfM were effective for both detecting erosion areas and estimating quantitatively the deposition and erosion volumes. Our results underlined how smartphones with high‐resolution built‐in cameras can be competitive instruments for obtaining suitable data for topography analysis and Earth surface monitoring. This methodology could be potentially very useful for farmers and/or technicians for post‐event field surveys to support flood risk management. Copyright © 2015 John Wiley & Sons, Ltd.     

Removal of water‐surface reflection effects with a temporal minimum filter for UAV‐based shallow‐water photogrammetry

The recent development of structure‐from‐motion (SfM) and multi‐view stereo (MVS) photogrammetry techniques has enabled semi‐automatic high‐resolution bathymetry using aerial images taken by consumer‐grade digital cameras mounted on unmanned aerial vehicles (UAVs). However, the applicability of these techniques is sometimes limited by sun and sky reflections at the water surface, which render the point‐cloud density and accuracy insufficient. In this research, we present a new imaging technique to suppress the effect of these water‐surface reflections. In this technique, we order a drone to take a short video instead of a still picture at each waypoint. We then apply a temporal minimum filter to the video. This filter extracts the smallest RGB values in all the video frames for each pixel, and composes an image with greatly reduced reflection effects. To assess the performance of this technique, we applied it at three small shallow‐water sites. Specifically, we evaluated the effect of the technique on the point cloud density and the accuracy and precision of the photogrammetry. The results showed that the proposed technique achieved a far denser point cloud than the case in which a randomly chosen frame was used for each waypoint, and also showed better overall accuracy and precision in estimating water‐bottom elevation. The effectiveness of this new technique should depend on the surface wave state and sky radiance distribution, and this dependence, as well as the applicability to large areas, should be investigated in future research. Copyright © 2018 John Wiley & Sons, Ltd.     

Influence of river channel morphology and bank characteristics on water surface boundary delineation using high‐resolution passive remote sensing and template matching

Accurate mapping of water surface boundaries in rivers is an important step for monitoring water stages, estimating discharge, flood extent, and geomorphic response to changing hydrologic conditions, and assessing riverine habitat. Nonetheless, it is a challenging task in spatially and spectrally heterogeneous river environments, commonly characterized by high spatiotemporal variations in morphology, bed material, and bank cover. In this study, we investigate the influence of channel morphology and bank characteristics on the delineation of water surface boundaries in rivers using high spatial resolution passive remote sensing and a template‐matching (object‐based) algorithm, and compare its efficacy with that of Support Vector Machine (SVM) (pixel‐based) algorithm. We perform a detailed quantitative evaluation of boundary‐delineation accuracy using spatially explicit error maps in tandem with the spatial maps of geomorphic and bank classes. Results show that template matching is more successful than SVM in delineating water surface boundaries in river sections with spatially challenging geomorphic landforms (e.g. sediment bar structures, partially submerged sediment deposits) and shallow water conditions. However, overall delineation accuracy by SVM is higher than that of template matching (without iterative hierarchical learning). Vegetation and water indices, especially when combined with texture information, improve the accuracy of template matching, for example, in river sections with overhanging trees and shadows – the two most problematic conditions in water surface boundary delineation. By identifying the influence of channel morphology and bank characteristics on water surface boundary mapping, this study helps determine river sections with higher uncertainty in delineation. In turn, the most suitable methods and data sets can be selectively utilized to improve geomorphic/hydraulic characterization. The methodology developed here can also be applied to similar studies on other geomorphic landforms including floodplains, wetlands, lakes, and coastlines. Copyright © 2014 John Wiley & Sons, Ltd.     

Hydro-morphological mapping of river reaches using videos captured with UAS

Unoccupied aerial systems (UASs) are frequently used in the field of fluvial geomorphology due to their capabilities for observing the continuum rather than single sample points. We introduce a (semi-)automatic workflow to measure river bathymetry and surface flow velocities of entire river reaches at high resolution, based on UAS videos and imagery. Video frame filtering improved the visibility of the riverbed using frame co-registration and averaging with a median filter. Subsequently, these video frames were incorporated with still images acquired by UASs into a structure from motion (SfM) photogrammetry approach to reconstruct the camera poses (i.e. positions and orientations) and the 3D point cloud of the river reach. The heights of submerged points were further processed using small-angle and multi-view refraction correction approaches to account for the refraction impact. The flow velocity pattern of the river surface was measured using the estimated camera pose from SfM, the reconstructed bathymetric point cloud and the co-registered video frames in combination with image velocimetry analysis. Finally, discharge was estimated at selected cross-sections, considering the average surface velocity and the bathymetry. Three case studies were considered to assess the performance of the workflow under different environmental conditions. The studied river reaches spanned a length between 0.15 and 1 km. The bathymetry was reconstructed with average deviations to RTK-GNSS point measurements as low as 1 cm with a standard deviation of 6 cm. If frames were processed with the median filter, the number of underwater points increased by up to 21%. The image-based surface velocities revealed an average deviation to reference measurements between 0.05 and 0.08 m s⁻¹. The image-based discharge was estimated with deviations to ADCP references of up to 5%, however this was sensitive to errors in water-level retrieval. The output of our workflow can provide a valuable input to hydro-morphological models.     

UAS‐based remote sensing of fluvial change following an extreme flood event

The effects of large floods on river morphology are variable and poorly understood. In this study, we apply multi‐temporal datasets collected with small unmanned aircraft systems (UASs) to analyze three‐dimensional morphodynamic changes associated with an extreme flood event that occurred from 19 to 23 June 2013 on the Elbow River, Alberta. We documented reach‐scale spatial patterns of erosion and deposition using high‐resolution (4–5 cm/pixel) orthoimagery and digital elevation models (DEMs) produced from photogrammetry. Significant bank erosion and channel widening occurred, with an average elevation change of ?0.24 m. The channel pattern was reorganized and overall elevation variation increased as the channel adjusted to full mobilization of most of the bed surface sediments. To test the extent to which geomorphic changes can be predicted from initial conditions, we compared shear stresses from a two‐dimensional hydrodynamic model of peak discharge to critical shear stresses for bed surface sediment sizes. We found no relation between modeled normalized shear stresses and patterns of scour and fill, confirming the complex nature of sediment mobilization and flux in high‐magnitude events. However, comparing modeled peak flows through the pre‐ and post‐flood topography showed that the flood resulted in an adjustment that contributes to overall stability, with lower percentages of bed area below thresholds for full mobility in the post‐flood geomorphic configuration. Overall, this work highlights the potential of UAS‐based remote sensing for measuring three‐dimensional changes in fluvial settings and provides a detailed analysis of potential relationships between flood forces and geomorphic change. Copyright © 2015 John Wiley & Sons, Ltd.     

Flood‐driven topographic changes in a gravel‐cobble river over segment,reach, and morphological unit scales

Regulated rivers generally incise below dams that cut off sediment supply, but how that happens and what the consequences are at different spatial scales is poorly understood. Modern topographic mapping at meter‐scale resolution now enables investigation of the details of spatial processes. In this study, spatial segregation was applied to a meter‐scale raster map of topographic change from 1999 to 2008 on the gravel‐cobble, regulated lower Yuba River in California to answer specific scientific questions about how a decadal hydrograph that included a flood peak of 22 times bankfull discharge affected the river at segment, reach, and morphological unit scales. The results show that the river preferentially eroded sediment from floodplains compared to the channel, and this not only promoted valley‐wide sediment evacuation, but also facilitated the renewal and differentiation of morphological units, especially in the channel. At the reach scale, area of fill and mean net rate of elevational change were directly correlated with better connectivity between the channel and floodplain, while the mean rate of scour in scour areas was influenced by the ratio of slope to bankfull Froude number, a ratio indicative of lateral migration versus vertical downcutting. Hierarchical segregation of topographic change rasters proved useful for understanding multi‐scalar geomorphic dynamics. Copyright © 2016 John Wiley & Sons, Ltd.