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.     

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.     

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.     

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.     

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.     

Microtopography of bare peat: a conceptual model and objective classification from high‐resolution topographic survey data

Peatlands globally are at risk of degradation through increased susceptibility to erosion as a result of climate change. Quantification of peat erosion and an understanding of the processes responsible for their degradation is required if eroded peatlands are to be protected and restored. Owing to the unique material properties of peat, fine‐scale microtopographic expressions of surface processes are especially pronounced and present a potentially rich source of geomorphological information, providing valuable insights into the stability and dominant surface process regimes. We present a new process‐form conceptual framework to rigorously describe bare peat microtopography and use Structure‐from‐Motion (SfM) surveys to quantify roughness for different peat surfaces. Through the first geomorphological application of a survey‐grade structured‐light hand‐held 3D imager (HhI), which can represent sub‐millimetre topographic variability in field conditions, we demonstrate that SfM identifies roughness signatures reliably over bare peat plots (<1 m²), although some smoothing is observed. Across 55 plots, the roughness of microtopographic types is quantified using a suite of roughness metrics and an objective classification system derived from decision tree analysis with 98% success. This objective classification requires just five roughness metrics, each of which quantifies a different aspect of the surface morphology. We show that through a combination of roughness metrics, microtopographic types can be identified objectively from high resolution survey data, providing a much‐needed geomorphological process‐perspective to observations of eroded peat volumes and earth surface change. 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.     

Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data

Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R² = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R² = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R² = 0.47 and RMSE 9.34 VWC%, and for the latter R² = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m² digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. 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.     

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     

Plot‐scale measurement of soil erosion at the experimental area of Sparacia (southern Italy)

Obtaining good quality soil loss data from plots requires knowledge of the factors that affect natural and measurement data variability and of the erosion processes that occur on plots of different sizes. Data variability was investigated in southern Italy by collecting runoff and soil loss from four universal soil‐loss equation (USLE) plots of 176 m², 20 ‘large’ microplots (0·16 m²) and 40 ‘small’ microplots (0·04 m²). For the four most erosive events (event erosivity index, R_e ≥ 139 MJ mm ha^?1 h^?1), mean soil loss from the USLE plots was significantly correlated with R_e. Variability of soil loss measurements from microplots was five to ten times greater than that of runoff measurements. Doubling the linear size of the microplots reduced mean runoff and soil loss measurements by a factor of 2·6–2·8 and increased data variability. Using sieved soil instead of natural soil increased runoff and soil loss by a factor of 1·3–1·5. Interrill erosion was a minor part (0·1–7·1%) of rill plus interrill erosion. The developed analysis showed that the USLE scheme was usable to predict mean soil loss at plot scale in Mediterranean areas. A microplot of 0·04 m² could be used in practice to obtain field measurements of interrill soil erodibility in areas having steep slopes. Copyright © 2003 John Wiley & Sons, Ltd.     

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

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

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.     

Partitioned by process: Measuring post-fire debris-flow and rill erosion with Structure from Motion photogrammetry

After wildfire, hillslope and channel erosion produce large amounts of sediment and can contribute significantly to long-term erosion rates. However, pre-erosion high-resolution topographic data (e.g. lidar) is often not available and determining specific contributions from post-fire hillslope and channel erosion is challenging. The impact of post-fire erosion on landscape evolution is demonstrated with Structure from Motion (SfM) Multi-View Stereo (MVS) photogrammetry in a 1 km² Idaho Batholith catchment burned in the 2016 Pioneer Fire. We use SfM-MVS to quantify post-fire erosion without detailed pre-erosion topography and hillslope transects to improve estimates of rill erosion at adequate spatial scales. Widespread rilling and channel erosion produced a runoff-generated debris-flow following modest precipitation in October 2016. We implemented unmanned aerial vehicle (UAV)-based SfM-MVS to derive a 5 cm resolution digital elevation model (DEM) of the channel scoured by debris-flow. In the absence of cm-resolution pre-erosion topography, a synthetic surface was defined by the debris-flow scour's geomorphic signature and we used a DEM of Difference (DoD) to map and quantify channel erosion. We found 3467 ± 422 m³ was eroded by debris-flow scour. Rill dimensions along hillslope transects and Monte Carlo simulation show rilling eroded ~1100 m³ of sediment and define a volume uncertainty of 29%. The total eroded volume (4600 ± 740 m³) we measured in our study catchment is partitioned into 75% channel erosion and 25% rill erosion, reinforcing the importance of catchment size on erosion process-dominance. The deposit volume from the 2016 event was 5700 ± 1140 m³, indicating ~60% contribution from post-fire channel erosion. Dating of charcoal fragments preserved in stratigraphy at the catchment outlet, and reconstructions of prior deposit volumes provide a record of Holocene fire-related debris-flows at this site; results suggest that episodic wildfire-driven erosion (~6 mm/year) dominate millennial-scale erosion (~5 mm/Ka) at this site. © 2019 John Wiley & Sons, Ltd. © 2019 John Wiley & Sons, Ltd.     

Dry aeolian dust accumulation in rocky deserts: ­a medium‐term field experiment based on short‐term wind tunnel simulations

The spatial pattern of medium‐term (a few months) dry aeolian dust accumulation in rocky deserts is predicted using short‐term deposition and erosion experiments in a wind tunnel. The predictions are tested in a field experiment set up in the northern Negev Desert of Israel. The results show that superimposing wind tunnel deposition and erosion maps usually leads to correct predictions of medium‐term dust accumulation. The predictions are somewhat less confident near the inflection lines of windward hillslopes, where small‐scale irregularities in the local topography make it difficult to locate the exact position of the areas of little accumulation. Elsewhere in the topography predictions are good, and the method works satisfactorily. Highest accumulation occurs on concave windward slopes and, to a lesser extent, on slopes parallel to the wind. Little accumulation occurs on the convex windward slopes and in dust separation bubbles. The smallest accumulation rates are observed immediately upwind of the top of pronounced hills and on leeslopes. The rate of dry dust accumulation measured during the field experiment varied from 17 to 93 g m⁻² a⁻¹, depending on the topographic position of the accumulation plots. For most plots, it was of the order of 30–60 g m⁻² a⁻¹. Copyright © 2000 John Wiley & Sons, Ltd.     

Local‐ and regional‐scale biomorphodynamics due to tree uprooting in semi‐natural and managed montane forests of the Sudetes Mountains,Central Europe

In this work, direct and indirect geomorphic consequences of wind‐related tree uprooting are examined, using an extensive dataset from the mountain range of the Sudetes, Poland. The role of local conditions in influencing the geomorphic efficacy of tree uprooting is examined, as well as issues of upscaling individual observations from experimental sites. This problem is approached at a range of spatial and observational scales, from monitoring of root plate degradation over time through to examination of wind effects at a slope scale and region‐wide analysis. In our study area the mean root plate volume is between 0.4 and 4.2 m³ for spruce and 2.4 m³ for beech, and their degradation may last tens of years. The density of relict pit‐and‐mound microtopography varies from 2.7 up to 40 pairs per hectare and the maximum coverage of terrain is 4.7%. The volume of treethrow mounds varies from 0.5 to 3.1 m³ and mounds seem to outlive the pits formed in the same episode of disturbance. However, in specific lithological and topographic conditions, pit‐and‐mound topography does not form. The maximum biogenic transport attributable to a single windstorm event is c. 80 m³ ha^?1, while soil turnover times are calculated in the order of 1000–10 000 years. Rock fragment ‘mining’ is an important biogeomorphic process, both in terms of impact on hillslope surfaces and on soil properties. Gravel armours and small‐scale stepped topography may form instead of typical pit–mound associations in specific circumstances. Managed forests appear more prone to wind damage and associated geomorphic consequences. In the Sudetes Mountains, the variable role of tree uprooting in local and regional hillslope denudation is governed by forest stand structure, topography and regolith properties, with the former significantly influenced by human activity. Copyright © 2016 John Wiley & Sons, Ltd.     

Backward snow depth reconstruction at high spatial resolution based on time‐lapse photography

We report a methodology for reconstructing the daily snow depth distribution at high spatial resolution in a small Pyrenean catchment using time‐lapse photographs and snow depletion rates derived from an on‐site measuring meteorological station. The results were compared with the observed snow depth distribution, determined on a number of separate occasions using a terrestrial laser scanner (TLS). The time‐lapse photographs were projected onto a digital elevation model of the study site, and converted into snow presence/absence information. The melt‐out date (MOD; first occurrence of melt out after peak snow accumulation) was obtained from the projected photograph series. Commencing the backward reconstruction for each grid cell at the MOD, the method uses simulated snow depth depletion rates using a temperature index approach, which are extrapolated to the grid cells of the domain to arrive at the snow distribution of the previous day. Two variants of the reconstruction techniques were applied (1) using a spatially constant degree day factor (DDF) for calculating the daily expected snow depth depletion rate, and (2) allowing a spatially distributed DDF calculated from two consecutive TLS acquisitions compared to the snow depth depletion rate observed at the meteorological station. Validation revealed that both methods performed well (average R² = 0.68; standard RMSE = 0.58), with better results obtained from the spatially distributed approach. Nevertheless, the spatially corrected DDF reconstruction, which requires TLS data, suggests that the constant DDF approach is an efficient, and for most applications sufficiently accurate and easily reproducible method. The results highlight the usefulness of time‐lapse photography for not only determining the snow covered area, but also for estimating the spatial distribution of snow depth. Copyright © 2016 John Wiley & Sons, Ltd.     

Climate–surface–pore‐water interactions on a salt crusted playa: implications for crust pattern and surface roughness development measured using terrestrial laser scanning

Sodium accumulating playas (also termed sodic or natric playas) are typically covered by polygonal crusts with different pattern characteristics, but little is known about the short‐term (hours) dynamics of these patterns or how pore water may respond to or drive changing salt crust patterning and surface roughness. It is important to understand these interactions because playa‐crust surface pore‐water and roughness both influence wind erosion and dust emission through controlling erodibility and erosivity. Here we present the first high resolution (10^?3 m; hours) co‐located measurements of changing moisture and salt crust topography using terrestrial laser scanning (TLS) and infra‐red imagery for Sua Pan, Botswana. Maximum nocturnal moisture pattern change was found on the crests of ridged surfaces during periods of low temperature and high relative humidity. These peaks experienced non‐elastic expansion overnight, of up to 30 mm and up to an average of 1.5 mm/night during the 39 day measurement period. Continuous crusts however showed little nocturnal change in moisture or elevation. The dynamic nature of salt crusts and the complex feedback patterns identified emphasize how processes both above and below the surface may govern the response of playa surfaces to microclimate diurnal cycles. © 2015 The Authors. Earth Surface Processes and Landforms published by 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.