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.     

Handling dip discrimination phenomenon in common‐reflection‐surface stack via combination of output‐imaging‐scheme and migration/demigration

In the application of a conventional common‐reflection‐surface (CRS) stack, it is well‐known that only one optimum stacking operator is determined for each zero‐offset sample to be simulated. As a result, the conflicting dip situations are not taken into account and only the most prominent event contributes to any a particular stack sample. In this paper, we name this phenomenon caused by conflicting dip problems as ‘dip discrimination phenomenon’. This phenomenon is not welcome because it not only leads to the loss of weak reflections and tips of diffractions in the final zero‐offset‐CRS stacked section but also to a deteriorated quality in subsequent migration. The common‐reflection‐surface stack with the output imaging scheme (CRS‐OIS) is a novel technique to implement a CRS stack based on a unified Kirchhoff imaging approach. As far as dealing with conflicting dip problems is concerned, the CRS‐OIS is a better option than a conventional CRS stack. However, we think the CRS‐OIS can do more in this aspect. In this paper, we propose a workflow to handle the dip discrimination phenomenon based on a cascaded implementation of prestack time migration, CRS‐OIS and prestack time demigration. Firstly, a common offset prestack time migration is implemented. Then, a CRS‐OIS is applied to the time‐migrated common offset gather. Afterwards, a prestack time demigration is performed to reconstruct each unmigrated common offset gather with its reflections being greatly enhanced and diffractions being well preserved. Compared with existing techniques dealing with conflicting dip problems, the technique presented in this paper preserves most of the diffractions and accounts for reflections from all possible dips properly. More importantly, both the post‐stacked data set and prestacked data set can be of much better quality after the implementation of the presented scheme. It serves as a promising alternative to other techniques except that it cannot provide the typical CRS wavefield attributes. The numerical tests on a synthetic Marmousi data set and a real 2D marine data set demonstrated its effectiveness and robustness.     

Application of Structure‐from‐Motion photogrammetry to river restoration

Structure‐from‐Motion (SfM) photogrammetry is now used widely to study a range of earth surface processes and landforms, and is fast becoming a core tool in fluvial geomorphology. SfM photogrammetry allows extraction of topographic information and orthophotos from aerial imagery. However, one field where it is not yet widely used is that of river restoration. The characterisation of physical habitat conditions pre‐ and post‐restoration is critical for assessing project success, and SfM can be used easily and effectively for this purpose. In this paper we outline a workflow model for the application of SfM photogrammetry to collect topographic data, develop surface models and assess geomorphic change resulting from river restoration actions. We illustrate the application of the model to a river restoration project in the NW of England, to show how SfM techniques have been used to assess whether the project is achieving its geomorphic objectives. We outline the details of each stage of the workflow, which extend from preliminary decision‐making related to the establishment of a ground control network, through fish‐eye lens camera testing and calibration, to final image analysis for the creation of facies maps, the extraction of point clouds, and the development of digital elevation models (DEMs) and channel roughness maps. The workflow enabled us to confidently identify geomorphic changes occurring in the river channel over time, as well as assess spatial variation in erosion and aggradation. Critical to the assessment of change was the high number of ground control points and the application of a minimum level of detection threshold used to assess uncertainties in the topographic models. We suggest that these two things are especially important for river restoration applications. Copyright © 2016 John Wiley & Sons, Ltd.     

Towards a protocol for laser scanning in fluvial geomorphology

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. Copyright © 2006 John Wiley & Sons, Ltd.     

Stereophotogrammetry of archive data and topographic approaches to debris‐flow torrent measurements: calculation of channel‐sediment states and a partial sediment budget for Manival torrent (Isère,France)

This paper focuses on a topographic methodology to characterize the amount of sediment stored in channels and the use of historical photographs for aerial survey by stereophotogrammetry, as part of wider research on debris‐flow magnitude prediction. The topographic methodology uses equidistant four‐point cross‐sections along the long profile of the channel. Each cross‐section is representative of a 50‐m reach of the channel. To calculate the volume of each reach, the difference is calculated between a reference level and the topographic surface. The reference level is the lowest level where the debris flow can erode, and in the current method this level is estimated from fixed points along the long profile of the channel. The accuracy of the method has been estimated by comparing results of a detailed topographic survey, with a standard deviation corresponding to about 6 per cent of the total calculated sediment volume. This topographic methodology has been used on aerial photographs by photogrammetry. This tool was applied to photographs taken on 12 past dates. The scales of the archive photographs used range from 1:3000 to 1:30 000, but results are consistent and permit us to calculate sediment states of the channel for different past dates with an uncertainty of about 6 per cent of the total volume. The application of the technique to the Manival debris‐flow torrent has permitted us to propose some partial sediment budgets and erosion‐rate estimates. Copyright © 2006 John Wiley & Sons, Ltd.     

Use of terrestrial photogrammetry based on structure‐from‐motion for mass balance estimation of a small glacier in the Italian alps

Different high‐resolution techniques can be employed to obtain information about the three‐dimensional (3D) surface of glaciers. This is typically carried out using efficient, but also expensive and logistically demanding, light detection and ranging (LiDAR) technologies, such as airborne scanners and terrestrial laser scanners. Recent technological improvements in the field of image analysis and computer vision have prompted the development of a low‐cost photogrammetric approach, which is referred to as ‘structure‐from‐motion’ (SfM). Combined with dense image‐matching algorithms, this method has become competitive for the production of high‐quality 3D models. However, several issues typical of this approach should be considered for application in glacial environments. In particular, the surface morphology, the different substrata, the occurrence of sharp contrast from solar shadows and the variable distance from the camera positions can negatively affect the image texture, and reduce the possibility of obtaining a reliable point cloud from the images. The objective of this study is to test the structure‐from‐motion multi view stereo (SfM‐MVS) approach in a small debris‐covered glacier located in the eastern Italian Alps, using a consumer‐grade reflex camera and the computer vision‐based software PhotoScan. The quality of the 3D models produced by the SfM‐MVS process was assessed via the comparison with digital terrain models obtained from terrestrial laser scanning (TLS) surveys that were performed at the same epochs. The effect of different terrain gradients and different substrata (debris, snow and firn) was also evaluated in terms of the accuracy of the reconstruction by SfM‐MVS versus TLS. Our results show that the quality of this new photogrammetric approach is similar to the quality of TLS and that point cloud densities are comparable or even higher compared with TLS. However, special care should be taken while planning the SfM survey geometry, to optimize the 3D model quality and spatial coverage. Copyright © 2015 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.     

Suppression of near‐surface scattered body‐to‐surface waves: a steerable and nonlinear filtering approach

We present an approach based on local‐slope estimation for the separation of scattered surface waves from reflected body waves. The direct and scattered surface waves contain a significant amount of seismic energy. They present great challenges in land seismic data acquisition and processing, particularly in arid regions with complex near‐surface heterogeneities (e.g., dry river beds, wadis/large escarpments, and karst features). The near‐surface scattered body‐to‐surface waves, which have comparable amplitudes to reflections, can mask the seismic reflections. These difficulties, added to large amplitude direct and back‐scattered surface (Rayleigh) waves, create a major reduction in signal‐to‐noise ratio and degrade the final sub‐surface image quality. Removal of these waves can be difficult using conventional filtering methods, such as an filter, without distorting the reflected signal. The filtering algorithm we present is based on predicting the spatially varying slope of the noise, using steerable filters, and separating the signal and noise components by applying a directional nonlinear filter oriented toward the noise direction to predict the noise and then subtract it from the data. The slope estimation step using steerable filters is very efficient. It requires only a linear combination of a set of basis filters at fixed orientation to synthesize an image filtered at an arbitrary orientation. We apply our filtering approach to simulated data as well as to seismic data recorded in the field to suppress the scattered surface waves from reflected body waves, and we demonstrate its superiority over conventional techniques in signal preservation and noise suppression.     

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.     

Investigating the geomorphological potential of freely available and accessible structure‐from‐motion photogrammetry using a smartphone

We test the acquisition of high‐resolution topographic and terrain data using hand‐held smartphone technology, where the acquired images can be processed using technology freely available to the research community. This is achieved by evaluating the quality of digital terrain models (DTM) of a river bank and an Alpine alluvial fan generated with a fully automated, free‐to‐use, structure‐from‐motion package and a smartphone integrated camera (5 megapixels) with terrestrial laser scanning (TLS) data used to provide a benchmark. To evaluate this approach a 16.2‐megapixel digital camera and an established, commercial, close‐range and semi‐automated software are also employed, and the product of the four combinations of the two types of cameras and software are compared. Results for the river bank survey demonstrate that centimetre‐precision DTMs can be achieved at close range (10 m or less), using a smartphone camera and a fully automated package. Results improve to sub‐centimetre precision with either higher‐resolution images or by applying specific post‐processing techniques to the smartphone DTMs. Application to an entire Alpine alluvial fan system shows the degradation of precision scales linearly with image scale, but that (i) the expected level of precision remains and (ii) difficulties in separating vegetation and sediment cover within the results are similar to those typically found when using other photo‐based techniques and laser scanning systems. Copyright © 2014 John Wiley & Sons, Ltd.     

A casting procedure for reproducing coarse‐grained sedimentary surfaces

In the ?eld, the measurement of near‐bed hydraulics remains problematic. Greater precision is possible in the laboratory, but, in the case of gravels, it is dif?cult to create a water‐worked channel‐bed that is realistic enough to replicate faithfully the conditions found in nature. In this paper, a technique to reproduce coarse‐grained sedimentary fabrics of large areal extent is described. It involves moulding natural river‐bed surfaces from which facsimiles are cast. Remarkably realistic casts with dimensions of 1 m by 2 m have been produced and their quality assessed using spatial data derived using automated digital photogrammetry. The casts reproduce the prototype surfaces with errors at millimetre scale (0·5 per cent of the microrelief). The technique has facilitated the introduction of sedimentary surfaces that incorporate natural, complex structures of grains up to cobble size into experimental channels where detailed studies of near‐bed hydraulics can be carried out. Copyright © 2003 John Wiley & Sons, Ltd.     

Temporal observations of a seasonal snowpack using upward‐looking GPR

An increase of the spatial and temporal resolution of snowpack measurements in Alpine or Arctic regions will improve the predictability of flood and avalanche hazards and increase the spatial validity of snowpack simulation models. In the winter season 2009, we installed a ground‐penetrating radar (GPR) system beneath the snowpack to measure snowpack conditions above the antennas. In comparison with modulated frequency systems, GPR systems consist of a much simpler technology, are commercially available and therefore are cheaper. The radar observed the temporal alternation of the snow height over more than 2·5 months. The presented data showed that with moved antennas, it is possible to record the snow height with an uncertainty of less than 8% in comparison with the probed snow depth. Three persistent melt crusts, which formed at the snow surface and were buried by further new snow events, were used as reflecting tracers to follow the snow cover evolution and to determine the strain rates of underlaying layers between adjacent measurements. The height in two‐way travel time of each layer changed over time, which is a cumulative effect of settlement and variation of wave speed in response to densification and liquid water content. The infiltration of liquid water with depth during melt processes was clearly observed during one event. All recorded reflections appeared in concordance with the physical principles (e.g. in phase structure), and one can assume that distinct density steps above a certain threshold result in reflections in the radargram. The accuracy of the used impulse radar system in determining the snow water equivalent is in good agreement with previous studies, which used continuous wave radar systems. The results of this pilot study encourage further investigations with radar measurements using the described test arrangement on a daily basis for continuous destruction‐free monitoring of the snow cover. Copyright © 2010 John Wiley & Sons, Ltd.     

From experimental plots to experimental landscapes: topography,erosion and deposition in sub‐humid badlands from Structure‐from‐Motion photogrammetry

In the last decade advances in surveying technology have opened up the possibility of representing topography and monitoring surface changes over experimental plots (<10 m²) in high resolution (~10³ points m^‐1). Yet the representativeness of these small plots is limited. With ‘Structure‐from‐Motion’ (SfM) and ‘Multi‐View Stereo’ (MVS) techniques now becoming part of the geomorphologist's toolkit, there is potential to expand further the scale at which we characterise topography and monitor geomorphic change morphometrically. Moving beyond previous plot‐scale work using Terrestrial Laser Scanning (TLS) surveys, this paper validates robustly a number of SfM‐MVS surveys against total station and extensive TLS data at three nested scales: plots (<30 m²) within a small catchment (4710 m²) within an eroding marl badland landscape (~1 km²). SfM surveys from a number of platforms are evaluated based on: (i) topography; (ii) sub‐grid roughness; and (iii) change‐detection capabilities at an annual scale. Oblique ground‐based images can provide a high‐quality surface equivalent to TLS at the plot scale, but become unreliable over larger areas of complex terrain. Degradation of surface quality with range is observed clearly for SfM models derived from aerial imagery. Recently modelled ‘doming’ effects from the use of vertical imagery are proven empirically as a piloted gyrocopter survey at 50m altitude with convergent off‐nadir imagery provided higher quality data than an Unmanned Aerial Vehicle (UAV) flying at the same height and collecting vertical imagery. For soil erosion monitoring, SfM can provide data comparable with TLS only from small survey ranges (~5 m) and is best limited to survey ranges ~10–20 m. Synthesis of these results with existing validation studies shows a clear degradation of root‐mean squared error (RMSE) with survey range, with a median ratio between RMSE and survey range of 1:639, and highlights the effect of the validation method (e.g. point‐cloud or raster‐based) on the estimated quality. Copyright © 2015 John Wiley & Sons, Ltd.     

On the use of loss‐on‐ignition techniques to quantify fluvial particulate organic carbon

The fluvial flux of carbon (C) from terrestrial to marine environments represents an important component of the global C‐cycle, which can transfer C from the atmosphere to sedimentary storage. Fluvial fluxes of C are also an essential resource for freshwater ecosystems, critical for habitat heterogeneity and function. As such it is crucial that we are able to quantify this flux accurately. However, at present there are a number of different techniques used to quantify concentrations of fluvial C, and these techniques vary in their accuracy. In this article, we compare particulate organic carbon (POC) measurements derived from two commonly‐used techniques; a simple combustion and loss‐on‐ignition (LOI) technique, and an oxidative–combustion and carbon dioxide (CO₂) detection technique. The techniques were applied to water samples collected from 10 contrasting reference‐condition, temperate river ecosystems. The POC measurements derived from the LOI technique were up to 16 times higher (average four times higher), than those derived from the oxidative–combustion and CO₂ detection technique. This difference was highly variable both across the different river ecosystems and within each river ecosystem over time, suggesting that there is no simple way of converting the mass measured by LOI to estimates of fluvial POC. It is suggested that the difference in POC measured by these two techniques is a consequence of: (1) the loss of inorganic carbon at LOI combustion temperatures of > 425 °C, (2) the potential during the LOI combustion stage to lose hygroscopic and intercrystalline water, not completely driven off by the drying stage at temperatures of < 150 °C, and (3) the variable C content of fluvial organic matter, meaning that the simple application of a fixed correction factor to values obtained from the LOI technique may not be appropriate. These findings suggest that oxidative–combustion and CO₂ detection techniques are preferential for quantifying fluvial POC. Copyright © 2013 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.     

Field application of close‐range digital photogrammetry (CRDP) for grain‐scale fluvial morphology studies

In situ measurement of grain‐scale fluvial morphology is important for studies on grain roughness, sediment transport and the interactions between animals and the geomorphology, topics relevant to many river practitioners. Close‐range digital photogrammetry (CRDP) and terrestrial laser scanning (TLS) are the two most common techniques to obtain high‐resolution digital elevation models (DEMs) from fluvial surfaces. However, field application of topography remote sensing at the grain scale is presently hindered mainly by the tedious workflow challenges that one needs to overcome to obtain high‐accuracy elevation data. A recommended approach for CRDP to collect high‐resolution and high‐accuracy DEMs has been developed for gravel‐bed flume studies. The present paper investigates the deployment of the laboratory technique on three exposed gravel bars in a natural river environment. In contrast to other approaches, having the calibration carried out in the laboratory removes the need for independently surveyed ground‐control targets, and makes for an efficient and effective data collection in the field. Optimization of the gravel‐bed imagery helps DEM collection, without being impacted by variable lighting conditions. The benefit of a light‐weight three‐dimensional printed gravel‐bed model for DEM quality assessment is shown, and confirms the reliability of grain roughness data measured with CRDP. Imagery and DEM analysis evidences sedimentological contrasts between gravel bars within the reach. The analysis of the surface elevations shows the effect variable grain‐size and sediment sorting have on the surface roughness. By plotting the two‐dimensional structure functions and surface slopes and aspects we identify different grain arrangements and surface structures. The calculation of the inclination index allows determining the surface‐forming flow direction(s). We show that progress in topography remote sensing is important to extend our knowledge on fluvial morphology processes at the grain scale, and how a technique customized for use by fluvial geomorphologists in the field benefits this progress. Copyright © 2016 John Wiley & Sons, Ltd.     

The use of small‐format and low‐altitude aerial photos for the realization of high‐resolution DEMs in mountainous areas: application to the Super‐Sauze earthflow (Alpes‐de‐Haute‐Provence,France)

Geomorphologists have to make choices and compromises, as acquisition techniques of geometrical information are numerous, depending on the specific complexity of the targeted three‐dimensional objects and the requirements of the end user. This article presents the methodology and the results over a well known and documented site. This ready‐to‐use, low‐altitude, aerial photo methodology reveals itself to be a satisfying compromise between cost, accuracy and difficulty of implementation. The selected equipment package is light enough to enable a quick reaction to unexpected events and the tools and methods are competitive with field acquisition techniques. An evaluation has demonstrated a sub‐metric accuracy for the final result. Copyright © 2002 John Wiley & Sons, Ltd.     

Assessment of drone‐based surface flow observations

Remote surface flow observations are crucial for improving the comprehension of hydrological phenomena. A recent advancement in remote hydrological measurements involves the use of drones for generating surface flow‐velocity field maps through large‐scale particle image velocimetry (LSPIV). In this work, we perform a comparative analysis of drone‐based LSPIV with fixed implementations. Quantitative indices are introduced to test the efficiency of the techniques with regards to measurement accuracy, sensitivity to the transit of tracers, and platform mobility. Experimental findings support drone‐based observations in outdoor settings. Specifically, measurements from the aerial platform are more sensitive to the transit of tracers and closer to benchmark values than traditional LSPIV implementations. Future work should aim at improving the stability of the aerial platform and mitigating the effects of tracer scarcity. Copyright © 2015 John Wiley & Sons, Ltd.     

From manned to unmanned aircraft: Adapting airborne particle size mapping methodologies to the characteristics of sUAS and SfM

Subaerial particle size data holds a wealth of valuable information for fluvial, coastal, glacial and other sedimentological applications. Recently, we have gained the opportunity to map and quantify surface particle sizes at the mesoscale using data derived from small unmanned aerial system (sUAS) imagery processed using structure from motion (SfM) photogrammetry. Typically, these sUAS‐SfM approaches have been based on calibrating orthoimage texture or point cloud roughness with particle size. Variable levels of success are reported and a single, robust method capable of producing consistently accurate and precise results in a range of settings has remained elusive. In this paper, we develop an original method for mapping surface particle size with the specific constraints of sUAS and SfM in mind. This method uses the texture of single sUAS images, rather than orthoimages, calibrated with particle sizes normalised by individual image scale. We compare results against existing orthoimage texture and roughness approaches, and provide a quantitative investigation into the implications of the use of sUAS camera gimbals. Our results indicate that our novel single image method delivers an optimised particle size mapping performance for our study site, outperforming both other methods and delivering residual mean errors of 0.02 mm (accuracy), standard deviation of residual errors of 6.90 mm (precision) and maximum residual errors of 16.50 mm. Accuracy values are more than two orders of magnitude worse when imagery is collected by a similar drone which is not equipped with a camera gimbal, demonstrating the importance of mechanical image stabilisation for particle size mapping using measures of image texture. Copyright © 2017 John Wiley & Sons, Ltd.     

Spatial interpolation of snow water equivalency using surface observations and remotely sensed images of snow‐covered area

As demand for water continues to escalate in the western Unites States, so does the need for accurate monitoring of the snowpack in mountainous areas. In this study, we describe a simple methodology for generating gridded‐estimates of snow water equivalency (SWE) using both surface observations of SWE and remotely sensed estimates of snow‐covered area (SCA). Multiple regression was used to quantify the relationship between physiographic variables (elevation, slope, aspect, clear‐sky solar radiation, etc.) and SWE as measured at a number of sites in a mountainous basin in south‐central Idaho (Big Wood River Basin). The elevation of the snowline, obtained from the SCA estimates, was used to constrain the predicted SWE values. The results from the analysis are encouraging and compare well to those found in previous studies, which often utilized more sophisticated spatial interpolation techniques. Cross‐validation results indicate that the spatial interpolation method produces accurate SWE estimates [mean R² = 0·82, mean mean absolute error (MAE) = 4·34 cm, mean root mean squared error (RMSE) = 5·29 cm]. The basin examined in this study is typical of many mid‐elevation mountainous basins throughout the western United States, in terms of the distribution of topographic variables, as well as the number and characteristics of sites at which the necessary ground data are available. Thus, there is high potential for this methodology to be successfully applied to other mountainous basins. Copyright © 2010 John Wiley & Sons, Ltd.