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.     

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.     

Digital elevation models derived from airborne laser scanning point clouds: appropriate spatial resolutions for multi‐temporal characterization and quantification of geomorphological processes

Digital terrain models (DTMs) are a standard data source for a variety of applications. DTM differencing is also widely used for detection and quantification of topographic changes. While several investigations have been made on the accuracy of DTMs, calculated from different kinds of input data, little has been published on the error of DTM differencing, specifically for the quantification of geomorphological processes. In this study, an extensive, multi‐temporal set of airborne laser scanning (ALS) data is used to investigate the accuracy of topographic change calculations in a high alpine environment, caused by different geomorphic processes. Differences from DTMs with cell sizes ranging from 0.25 m to 10 m were calculated and compared to very accurate point‐to‐point calculations for a variety of processes and in nearby stable areas which show no significant surface changes. The representativeness of the DTM differences is then compared to the terrain slope and surface roughness of the investigated areas to show the influence of these parameters on the errors in the differences. Those errors are then taken into account for analyses of the applicability of different cell sizes for the investigation of geomorphic processes with different magnitudes and over different time periods. The analyses show that the error of DTM differences increases with lower point densities and higher roughness and slope values. The higher the error, the greater the differences between two elevation datasets have to be in order to quantify certain morphodynamic processes. Lower point densities and higher roughness and slope values require greater process rates or longer time intervals in order to obtain valid results. Copyright © 2013 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.     

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.     

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.     

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.     

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.     

The topographic data source of digital terrain models as a key element in the accuracy of hydraulic flood modelling

The effects of the topographic data source and resolution on the hydraulic modelling of floods were analysed. Seven digital terrain models (DTMs) were generated from three different altimetric sources: a global positioning system (GPS) survey and bathymetry; high‐resolution laser altimetry data LiDAR (light detection and ranging); and vectorial cartography (1:5000). Hydraulic results were obtained, using the HEC‐RAS one‐dimensional model, for all seven DTMs. The importance of the DTM's accuracy on the hydraulic modelling results was analysed within three different hydraulic contexts: (1) the discharge and water surface elevation results from the hydraulic model; (2) the delineation of the flooded area; and (3) the relative sensitivity of the hydraulic model to changes in the Manning's n roughness coefficient. The contour‐based DTM was the least accurate with a root mean square error (RMSE) of 4·5 m in the determination of the water level and a variation of up to 50 per cent in the estimation of the inundated area of the floodplain. The GPS‐based DTM produced more realistic water surface elevation results and variations of up to 8 per cent in terms of the flooded area. The laser‐based model's RMSE for water level was 0·3 m, with the flooded area varying by less than 1 per cent. The LiDAR data also showed the greatest sensitivity to changes in the Manning's roughness coefficient. An analysis of the effect of mesh resolution indicated an influence on the delineation of the flooded area with variations of up to 7·3 per cent. In addition to determining the accuracy of the hydraulic modelling results produced from each DTM, an analysis of the time–cost ratio of each topographic data source illustrates that airborne laser scanning is a cost‐effective means of developing a DTM of sufficient accuracy, especially over large areas. Copyright © 2006 John Wiley & Sons, Ltd.     

DATA COMPARATIVE ANALYSIS BETWEEN SFM DATA AND DGPS DATA: A CASE STUDY FROM FAULT SCARP IN THE EAST BANK OF HONGSHUIBA RIVER,NORTHERN MARGIN OF THE QILIAN SHAN

With the development of the techniques acquiring high-resolution digital terrain data,the digital terrain data acquisition technology has been widespread applied to the geoscience research.A revolutionary,low-cost and simply operative SfM (Structure from Motion) technology will make obtain high-resolution DEM data more convenient for researches on active tectonics.This paper summarizes the basic principles and workflows of SfM technology and processes and selects the Hongshuiba River area along the northern margin of the Qilian Shan to conduct data collection.We use a series of digital pictures to produce a texture with geographic information,in which data resolution is 6.73cm/pix and average density of point cloud is 220.667 point/m².The coverage area is 0.286km².Further,in order to compare the accuracy between SfM data and differential GPS (DGPS) data in details,SfM data are vertically shifted and tilt-corrected.After optimizing corrections of SfM data,the absolute value of elevation difference between two data substantially concentrates around 20cm,roughly equivalent to 2-folds of data error only after the elevation error correction.Elevation difference between two data is 10~15cm in 90% confidence interval.The maximum error is about 30cm,but accounts for less than 10%.Along the direction of fault trace,the height of fault scarp extracted from SfM data shows that vertical displacement of the latest tectonic activity in the east bank of Hongshuiba River is about 1m,and some minimum scarps height may be 0.3m.The results show SfM technology with high vertical accuracy can be able to replace differential GPS in high-precision topographic survey.After correcting of SfM data,elevation difference still exists,which may be associated with methods of generating DEM and SfM data accuracy,which in turn is controlled by the number and distribution of Ground Control Points (GCPs),photos density and camera shooting height,but also related to surface features,Fodongmiao-Hongyazi Fault     

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.     

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.     

Use of fused airborne scanning laser altimetry and digital map data for urban flood modelling

Flood modelling of urban areas is still at an early stage, partly because until recently topographic data of sufficiently high resolution and accuracy have been lacking in urban areas. However, digital surface models (DSMs) generated from airborne scanning laser altimetry (LiDAR) having sub‐metre spatial resolution have now become available, and these are able to represent the complexities of urban topography. This paper describes the development of a LiDAR post‐processor for urban flood modelling based on the fusion of LiDAR and digital map data. The map data are used in conjunction with LiDAR data to identify different object types in urban areas, though pattern recognition techniques are also employed. Post‐processing produces a digital terrain model (DTM) for use as model bathymetry, and also a friction parameter map for use in estimating spatially distributed friction coefficients. In vegetated areas, friction is estimated from LiDAR‐derived vegetation height, and (unlike most vegetation removal software) the method copes with short vegetation less than ～1 m high, which may occupy a substantial fraction of even an urban floodplain. The DTM and friction parameter map may also be used to help to generate an unstructured mesh of a vegetated urban floodplain for use by a two‐dimensional finite element model. The mesh is decomposed to reflect floodplain features having different frictional properties to their surroundings, including urban features (such as buildings and roads) and taller vegetation features (such as trees and hedges). This allows a more accurate estimation of local friction. The method produces a substantial node density due to the small dimensions of many urban features. Copyright © 2007 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.     

Mitigating systematic error in topographic models for geomorphic change detection: accuracy,precision and considerations beyond off-nadir imagery

Unmanned aerial vehicles (UAVs) and structure-from-motion photogrammetry enable detailed quantification of geomorphic change. However, rigorous precision-based change detection can be compromised by survey accuracy problems producing systematic topographic error (e.g. ‘doming’), with error magnitudes greatly exceeding precision estimates. Here, we assess survey sensitivity to systematic error, directly correcting topographic data so that error magnitudes align more closely with precision estimates. By simulating conventional grid-style photogrammetric aerial surveys, we quantify the underlying relationships between survey accuracy, camera model parameters, camera inclination, tie point matching precision and topographic relief, and demonstrate a relative insensitivity to image overlap. We show that a current doming-mitigation strategy of using a gently inclined (<15°) camera can reduce accuracy by promoting a previously unconsidered correlation between decentring camera lens distortion parameters and the radial terms known to be responsible for systematic topographic error. This issue is particularly relevant for the wide-angle cameras often integrated into current-generation, accessible UAV systems, frequently used in geomorphic research. Such systems usually perform on-board image pre-processing, including applying generic lens distortion corrections, that subsequently alter parameter interrelationships in photogrammetric processing (e.g. partially correcting radial distortion, which increases the relative importance of decentring distortion in output images). Surveys from two proglacial forefields (Arolla region, Switzerland) showed that results from lower-relief topography with a 10°-inclined camera developed vertical systematic doming errors > 0·3 m, representing accuracy issues an order of magnitude greater than precision-based error estimates. For higher-relief topography, and for nadir-imaging surveys of the lower-relief topography, systematic error was < 0·09 m. Modelling and subtracting the systematic error directly from the topographic data successfully reduced error magnitudes to values consistent with twice the estimated precision. Thus, topographic correction can provide a more robust approach to uncertainty-based detection of event-scale geomorphic change than designing surveys with small off-nadir camera inclinations and, furthermore, can substantially reduce ground control requirements. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd     

How do sediment yields from post‐wildfire debris‐laden flows depend on terrain slope,soil burn severity class,and drainage basin area? Insights from airborne‐LiDAR change detection

We derived a high‐resolution, spatially continuous map of erosion and deposition associated with the debris‐laden flows triggered by the 2011 Las Conchas wildfire and subsequent rainstorms over a 197 km² area in New Mexico, USA. This map was produced using airborne‐LiDAR‐derived bare‐earth digital elevation models (DEMs) acquired approximately one year before and one year after the wildfire. Differencing of the pre‐wildfire and post‐wildfire‐and‐rainstorm bare‐earth DEMs yielded a DEM‐of‐difference (DoD) map that quantifies the magnitude of ground‐surface elevation changes due to erosion/deposition within each 1 m² pixel. We applied a 0.3 m threshold filter to our DoD to remove changes that could have been due to artifacts and/or imperfect georeferencing. The 0.3 m value for the threshold filter was chosen based on the stated accuracy of the LiDAR as well as a comparison of areas of significant topographic change mapped in aerial photographs with those predicted using a range of candidate threshold values for the DoD filter. We developed an automated procedure that accepts the DoD map as input and computes, for every pixel in the DEM, the net sediment volume exported through each pixel by colluvial and/or fluvial processes using a digital routing algorithm. An analysis of the resulting sediment volume map for the Las Conchas fire demonstrates that sediment volume is proportional to upstream contributing area. After normalized by contributing area, the average sediment yield (defined as the sediment volume divided by the contributing area) increases as a power‐law functions of the average terrain slope and soil burn severity class (SBSC) with exponents equal to approximately 1.5. Our analysis quantifies the relationships among sediment yield, average terrain slope, and average soil burn severity class at the watershed scale and should prove useful for predicting the geomorphic response of wildfire‐affected drainage basins. Copyright © 2014 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.     

Accurate automated assessment of gully cross‐section geometry using the photogrammetric interface FreeXSapp

During recent years, 3‐D techniques such as LiDAR and Structure‐from‐Motion (SfM) photogrammetry have been increasingly used for gully erosion assessment. However, innovative image‐based approaches based on these advances may also be used to provide accurate cross‐sectional measurements which are less expensive and time‐demanding. In this work, we present the FreeXSapp methodology, a new piece of freely‐available software based on existing SfM tools (MicMac and PMVS2) and augmented‐reality targets (ArUco markers) which performs the automated 3‐D reconstruction, scaling, orientation and analysis of gully cross‐sections (XSs) from images taken from the gully margin using a smartphone camera. As a field application, the volume of a 60‐m‐long medium‐size gully was evaluated, where a total of 10 XSs were measured and analyzed in approximately 30 min. The relative accuracy in estimating width and depth dimensions was in the order of 0.5%, with a precision ratio (relative to the camera–XS distance) of ~1500. Overall, using this methodology showed excellent performance in terms of time and cost requirements when compared with typical 3‐D and conventional 2‐D techniques. The FreeXSapp interface is downloadable for free for Windows operating systems at http://www.uco.es/users/ccastillo/freexsapp. Copyright © 2018 John Wiley & Sons, Ltd.     

Variations in multiscale curvature distribution and signatures of LiDAR DTM errors

The development of high resolution LiDAR digital terrain models (DTMs) has enabled the exploration of the statistical signature of morphology on curvature distributions. This work analyzes Minimum Curvature distributions to identify the statistical signature of two types of LiDAR‐DTM errors (outliers and striping artifacts) in the derived estimates, rather than morphology itself. The analysis shows the importance of modeling these errors correctly, in relation to the scale of analysis and DTM resolution, in order to have reliable curvature estimates. Nine DTMs of different morphological areas are considered, and grouped into a training dataset (without errors) and a test dataset (with errors). In the training dataset, the original DTMs are considered as true values; errors are then applied to these data. Minimum Curvature is computed at multiple scales from each DTM: changes in curvature distributions due only to morphology and scale are characterized from the original data; error effects are then identified from the datasets with simulated errors, and validated against the test dataset. The analysis shows that outliers and striping artifacts can be realistically simulated by heavily left tailed distributions. For DTMs without errors, the scale‐dependent change in curvature distribution is primarily controlled by real morphology. When DTMs include errors, curvature distributions become controlled by these errors, whose propagation depends on error distribution, error spatial correlation, and the scale of analysis. This study shows that the curvature distributions are impacted upon differently by striping artifacts and outliers, and that these are clearly distinguishable from the signal of morphological features: a scale‐dependent change in curvature distribution can therefore be interpreted as the signature of these specific errors, rather than morphology. Copyright © 2012 John Wiley & Sons, Ltd.