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.     

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.     

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.     

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.     

Assessing the performance of structure‐from‐motion photogrammetry and terrestrial LiDAR for reconstructing soil surface microtopography of naturally vegetated plots

Soil microtopography is a property of critical importance in many earth surface processes but is often difficult to quantify. Advances in computer vision technologies have made image‐based three‐dimensional (3D) reconstruction or Structure‐from‐Motion (SfM) available to many scientists as a low cost alternative to laser‐based systems such as terrestrial laser scanning (TLS). While the performance of SfM at acquiring soil surface microtopography has been extensively compared to that of TLS on bare surfaces, little is known about the impact of vegetation on reconstruction performance. This article evaluates the performance of SfM and TLS technologies at reconstructing soil microtopography on 6 m × 2 m erosion plots with vegetation cover ranging from 0% to 77%. Results show that soil surface occlusion by vegetation was more pronounced with TLS compared to SfM, a consequence of the single viewpoint laser scanning strategy adopted in this study. On the bare soil surface, elevation values estimated with SfM were within 5 mm of those from TLS although long distance deformations were observed with the former technology. As vegetation cover increased, agreement between SfM and TLS slightly degraded but was significantly affected beyond 53% of ground cover. Detailed semivariogram analysis on meter‐square‐scale surface patches showed that TLS and SfM surfaces were very similar even on highly vegetated plots but with fine scale details and the dynamic elevation range smoothed out with SfM. Errors in the TLS data were mainly caused by the distance measurement function of the instrument especially at the fringe of occlusion regions where the laser beam intersected foreground and background features simultaneously. From this study, we conclude that a realistic approach to digitizing soil surface microtopography in field conditions can be implemented by combining strengths of the image‐based method (simplicity and effectiveness at reconstructing soil surface under sparse vegetation) with the high accuracy of TLS‐like technologies. Copyright © 2015 John Wiley & Sons, Ltd.     

Ultra‐rapid topographic surveying for complex environments: the hand‐held mobile laser scanner (HMLS)

Terrestrial laser scanning is the current technique of choice for acquiring high resolution topographic data at the site scale (i.e. over tens to hundreds of metres), for accurate volume measurements or process modelling. However, in regions of complex topography with multiple local horizons, restricted lines of sight significantly hinder use of such tripod‐based instruments by requiring multiple setups to achieve full coverage of the area. We demonstrate a novel hand‐held mobile laser scanning technique that offers particular promise for site‐scale topographic surveys of complex environments. To carry out a survey, the hand‐held mobile laser scanner (HMLS) is walked across a site, mapping around the surveyor continuously en route. We assess the accuracy of HMLS data by comparing survey results from an eroding coastal cliff site with those acquired by a state‐of‐the‐art terrestrial laser scanner (TLS) and also with the results of a photo‐survey, processed by structure from motion and multi‐view stereo (SfM‐MVS) algorithms. HMLS data are shown to have a root mean square (RMS) difference to the benchmark TLS data of 20 mm, not dissimilar to that of the SfM‐MVS survey (18 mm). The efficiency of the HMLS system in complex terrain is demonstrated by acquiring topographic data covering ~780 m² of salt‐marsh gullies, with a mean point spacing of 4.4 cm, in approximately six minutes. We estimate that HMLS surveying of gullies is approximately 40 times faster than using a TLS and six times faster than using SfM‐MVS. © 2013 The Authors. Earth Surface Processes and Landforms Published by 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.     

An automatic approach for rill network extraction to measure rill erosion by terrestrial and low‐cost unmanned aerial vehicle photogrammetry

For an erosion event (October 2016) occurred at the Sparacia experimental area (Southern Italy), both terrestrial and low‐altitude aerial surveys were carried out by consumer grade camera and quadcopter (low‐cost unmanned aerial vehicle [UAV]) to measure rill erosion on two plots with steepness of 22% and 26%. Applying the structure from motion (SfM) technique, the three‐dimensional digital terrain models (3D‐DTMs) and the quasi three‐dimensional models (2.5D‐digital elevation model [DEM]) were obtained by the two surveys. Furthermore, 3D‐DTM and DEM were built using the available aerial photographs (166) and adding 40 terrestrial photographs. For the first time, the convergence index was applied to high‐resolution rill data for extracting the rill network, and a subsequent separation into contributing and non‐contributing rills was carried out. The comparison among the three surveys (terrestrial, UAV, and UAV + terrestrial) was developed using two morphometric parameters of the rill network (drainage density and drainage frequency). Moreover, using as reference the weight of sediment stored on the tanks located downstream of the plots, the reliability of soil loss measurement by 3D models was tested. For both contributing and non‐contributing rills, the morphometric parameters were higher for the terrestrial than for UAV and UAV + terrestrial surveys. For both plots, SfM always provided reliable soil loss measurements, which were affected by errors ranging from ?8% to 13%. Although the applied technique used a low‐cost UAV and a consumer grade camera, the obtained results demonstrated that a reliable estimate of rill erosion can be obtained in an area of interest.     

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.     

Testing the utility of structure‐from‐motion photogrammetry reconstructions using small unmanned aerial vehicles and ground photography to estimate the extent of upland soil erosion

Quantifying the extent of soil erosion at a fine spatial resolution can be time consuming and costly; however, proximal remote sensing approaches to collect topographic data present an emerging alternative for quantifying soil volumes lost via erosion. Herein we compare terrestrial laser scanning (TLS), and both unmanned aerial vehicle (UAV) and ground photography (GP) structure‐from‐motion (SfM) derived topography. We compare the cost‐effectiveness and accuracy of both SfM techniques to TLS for erosion gully surveying in upland landscapes, treating TLS as a benchmark. Further, we quantify volumetric soil loss estimates from upland gullies using digital surface models derived by each technique and subtracted from an interpolated pre‐erosion surface. Soil loss estimates from UAV and GP SfM reconstructions were comparable to those from TLS, whereby the slopes of the relationship between all three techniques were not significantly different from 1:1 line. Only for the TLS to GP comparison was the intercept significantly different from zero, showing that GP is more capable of measuring the volumes of very small erosion features. In terms of cost‐effectiveness in data collection and processing time, both UAV and GP were comparable with the TLS on a per‐site basis (13.4 and 8.2 person‐hours versus 13.4 for TLS); however, GP was less suitable for surveying larger areas (127 person‐hours per ha^?1 versus 4.5 for UAV and 3.9 for TLS). Annual repeat surveys using GP were capable of detecting mean vertical erosion change on peaty soils. These first published estimates of whole gully erosion rates (0.077 m a^?1) suggest that combined erosion rates on gully floors and walls are around three times the value of previous estimates, which largely characterize wind and rainsplash erosion of gully walls. Copyright © 2017 John Wiley & Sons, Ltd.     

Archival photogrammetric analysis of river–floodplain systems using Structure from Motion (SfM) methods

In this study we evaluate the extent to which accurate topographic data can be obtained by applying Structure from Motion (SfM) photogrammetric methods to archival imagery. While SfM has proven valuable in photogrammetric applications using specially acquired imagery (e.g. from unmanned aerial vehicles), it also has the potential to improve the precision of topographic data and the ease with which can be produced from historical imagery. We evaluate the application of SfM to a relatively extreme case, one of low relative relief: a braided river–floodplain system. We compared the bundle adjustments of SfM and classical photogrammetric methods, applied to eight dates. The SfM approach resulted in data quality similar to the classical approach, although the lens parameter values (e.g. focal length) recovered in the SfM process were not necessarily the same as their calibrated equivalents. Analysis showed that image texture and image overlap/configuration were critical drivers in the tie‐point generation which impacted bundle adjustment quality. Working with archival imagery also illustrated the general need for the thorough understanding and careful application of (commercial) SfM software packages. As with classical methods, the propagation of (random) error in the estimation of lens and exterior orientation parameters using SfM methods may lead to inherent systematic error in the derived point clouds. We have shown that linear errors may be accounted for by point cloud registration based on a reference dataset, which is vital for the further application in quantitative morphological analyses when using archival imagery. Copyright © 2016 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.     

Using structure‐from‐motion to create glacier DEMs and orthoimagery from historical terrestrial and oblique aerial imagery

Increased resolution and availability of remote sensing products, and advancements in small‐scale aerial drone systems, allows observations of glacial changes at unprecedented levels of detail. Software developments, such as structure‐from‐motion (SfM), now allow users an easy and efficient method to generate three‐dimensional (3D) models and orthoimages from aerial or terrestrial datasets. While these advancements show promise for current and future glacier monitoring, many regions still suffer a lack of observations from earlier time periods. We report on the use of SfM to extract spatial information from various historic imagery sources. We focus on three geographic regions, the European Alps, high Arctic Norway and the Nepal Himalayas. We used terrestrial field photographs from 1896, high oblique aerial photographs from 1936 and aerial handheld photographs from 1978 to generate digital elevation models (DEMs) and orthophotos of the Rhone glacier, Brøggerhalvøya and the lower Khumbu glacier, respectively. Our analysis shows that applying SfM to historic imagery can generate high quality models using only ground control points. Limited camera/orientation information was largely reproduced using self‐calibrated model data. Using these data, we calculated mean ground sampling distances across each site which demonstrates the high potential resolution of resulting models. Vertical errors for our models are ±5.4 m, ±5.2 m and ±3.3 m. Differencing shows similar patterns of thinning at lower Rhone (European Alps) and Brøggerhalvøya (Norway) glaciers, which have mean thinning rates of 0.31 m a^?1 (1896–2010) to 0.86 m a^?1 (1936–2010) respectively. On these clean ice glaciers thinning is highest in the terminus region and decreasing up‐glacier. In contrast to these glaciers, uneven topography, exposed ice‐cliffs and debris cover on the Khumbu glacier create a highly variable spatial distribution of thinning. The mean thinning rate for the Khumbu study area was found to be 0.54 ± 0.9 m a^?1 (1978–2015). Copyright © 2017 John Wiley & Sons, Ltd.     

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.     

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.     

Mitigating systematic error in topographic models derived from UAV and ground‐based image networks

High resolution digital elevation models (DEMs) are increasingly produced from photographs acquired with consumer cameras, both from the ground and from unmanned aerial vehicles (UAVs). However, although such DEMs may achieve centimetric detail, they can also display systematic broad‐scale error that restricts their wider use. Such errors which, in typical UAV data are expressed as a vertical ‘doming’ of the surface, result from a combination of near‐parallel imaging directions and inaccurate correction of radial lens distortion. Using simulations of multi‐image networks with near‐parallel viewing directions, we show that enabling camera self‐calibration as part of the bundle adjustment process inherently leads to erroneous radial distortion estimates and associated DEM error. This effect is relevant whether a traditional photogrammetric or newer structure‐from‐motion (SfM) approach is used, but errors are expected to be more pronounced in SfM‐based DEMs, for which use of control and check point measurements are typically more limited. Systematic DEM error can be significantly reduced by the additional capture and inclusion of oblique images in the image network; we provide practical flight plan solutions for fixed wing or rotor‐based UAVs that, in the absence of control points, can reduce DEM error by up to two orders of magnitude. The magnitude of doming error shows a linear relationship with radial distortion and we show how characterization of this relationship allows an improved distortion estimate and, hence, existing datasets to be optimally reprocessed. Although focussed on UAV surveying, our results are also relevant to ground‐based image capture. © 2014 The Authors. Earth Surface Processes and Landforms published by 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     

Long‐range terrestrial laser scanning for geomorphological change detection in alpine terrain – handling uncertainties

Long‐range terrestrial laser scanning (TLS) is an emerging method for the monitoring of alpine slopes in the vicinity of infrastructure. Nevertheless, deformation monitoring of alpine natural terrain is difficult and becomes even more challenging with larger scan distances. In this study we present approaches for the handling of spatially variable measurement uncertainties in the context of geomorphological change detection using multi‐temporal data sets. A robust distance measurement is developed, which deals with surface roughness and areas of lower point densities. The level of detection (LOD), i.e. the threshold distinguishing between real surface change and data noise, is based on a confidence interval considering the spatial variability of TLS errors caused by large laser footprints, low incidence angles and surface roughness. Spatially variable positional uncertainties are modelled for each point according to its range and the object geometry hit. The local point cloud roughness is estimated in the distance calculation process from the variance of least‐squares fitted planes. Distance calculation and LOD assessment are applied in two study areas in the Eastern Alps (Austria) using multi‐temporal laser scanning data sets of slopes surrounding reservoir lakes. At Finstertal, two TLS point clouds of high alpine terrain and scanned from ranges between 300 and 1800 m are compared. At Gepatsch, the comparison is done between an airborne laser scanning (ALS) and a TLS point cloud of a vegetated mountain slope scanned from ranges between 600 and 3600 m. Although these data sets feature different conditions regarding the scan setup and the surface conditions, the presented approach makes it possible to reliably analyse the geomorphological activity. This includes the automatic detection of rock glacier movement, rockfall and debris slides, even in areas where a difference in vegetation cover could be observed. Copyright © 2016 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.     

Three-dimensional reconstruction of fluvial surface sedimentology and topography using personal mobile laser scanning

High-resolution quantification of fluvial topography has been enabled by a number of geomatics technologies. Hyperscale surveys with spatial extents of <1 km² have been widely demonstrated by means of terrestrial laser scanning (TLS) and structure-from-motion (SfM) photogrammetry. Recent advances in the development and integration of global navigation satellite system (GNSS), inertial measurement unit (IMU) and lightweight laser scanning technologies are now resulting in the emergence of personal mobile laser scanners (MLS) that have the potential to increase data acquisition and processing rates by one to two orders of magnitude compared to TLS/SfM, and thus challenge the recent dominance of these technologies. This investigation compares a personal MLS survey using a Leica Pegasus Backpack that integrates Velodyne Puck VLP-16 sensors, and a multi-station static TLS survey using a Riegl VZ-1000 scanner, to produce digital elevation models (DEMs) and surface sedimentology maps. The assessment is undertaken on a 500 m long reach of the braided River Feshie. Comparison to 107 independent real-time kinematic (RTK)-GNSS check points resulted in similar mean error (ME) and standard deviation error (SDE) for TLS (ME = −0.025 m; SDE = 0.038 m) and personal MLS (ME = −0.014 m; SDE = 0.019 m). Direct cloud-to-cloud (C2C) comparison between a sample of TLS and personal MLS observations (2.8 million points) revealed that C2C distances follow a sharply decreasing Burr distribution (a = 2.35, b = 3.19, rate parameter s = 9.53). Empirical relationships between sub-metre topographic variability and median sediment grain size (10–100 mm) demonstrate that surface roughness from personal MLS can be used to map median grain size. Differences between TLS and personal MLS empirical relationships suggest such relationships are dependent on survey technique. Personal MLS offers distinct logistical advantages over SfM photogrammetry and TLS for particular survey situations and is likely to become a widely applied technique. © 2019 John Wiley & Sons, Ltd.