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1.
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.  相似文献   

2.
A key problem in computational fluid dynamics (CFD) modelling of gravel‐bed rivers is the representation of multi‐scale roughness, which spans the range from grain size, through bedforms, to channel topography. These different elements of roughness do not clearly map onto a model mesh and use of simple grain‐scale roughness parameters may create numerical problems. This paper presents CFD simulations for three cases: a plane bed of fine gravel, a plane bed of fine gravel including large, widely‐spaced pebble clusters, and a plane gravel bed with smaller, more frequent, protruding elements. The plane bed of fine gravel is modelled using the conventional wall function approach. The plane bed of fine gravel including large, widely‐spaced pebble clusters is modelled using the wall function coupled with an explicit high‐resolution topographic representation of the pebble clusters. In these cases, the three‐dimensional Reynolds‐averaged continuity and Navier–Stokes equations are solved using the standard k ? ε turbulence model, and model performance is assessed by comparing predicted results with experimental data. For gravel‐bed rivers in the field, it is generally impractical to map the bed topography in sufficient detail to enable the use of an explicit high‐resolution topography. Accordingly, an alternative model based on double‐averaging is developed. Here, the flow calculations are performed by solving the three‐dimensional double‐averaged continuity and Navier‐Stokes equations with the spatially‐averaged 〈k ? ε〉 turbulence model. For the plane bed of fine gravel including large, widely‐spaced pebble clusters, the model performance is assessed by comparing the spatially‐averaged velocity with the experimental data. The case of a plane gravel bed with smaller, more frequent, protruding elements is represented by a series of idealized hypothetical cases. Here, the spatially‐averaged velocity and eddy viscosity are used to investigate the applicability of the model, compared with using the explicit high‐resolution topography. The results show the ability of the model to capture the spatially‐averaged flow field and, thus, illustrate its potential for representing flow processes in natural gravel‐bed rivers. Finally, practical data requirements for implementing such a model for a field example are given. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

3.
We explore the link between channel‐bed texture and river basin concavity in equilibrium catchments using a numerical landscape evolution model. Theory from homogeneous sediment transport predicts that river basin concavity directly increases with bed sediment size. If the effective grain size on a river bed governs its concavity, then natural phenomena such as grain‐size sorting and channel armouring should be linked to concavity. We examine this hypothesis by allowing the bed sediment texture to evolve in a transport‐limited regime using a two grain‐size mixture of sand and gravel. Downstream ?ning through selective particle erosion is produced in equilibrium. As the channel‐bed texture adjusts downstream so does the local slope. Our model predicts that it is not the texture of the original sediment mixture that governs basin concavity. Rather, concavity is linked to the texture of the sorted surface layer. Two different textural regimes are produced in the experiments: a transitional regime where the mobility of sand and gravel changes with channel‐bed texture, and a sand‐dominated region where the mobility of sand and gravel is constant. The concavity of these regions varies depending on the median gravel‐ or sand‐grain size, erosion rate, and precipitation rate. The results highlight the importance of adjustments in both surface texture and slope in natural rivers in response to changes in ?uvial and sediment inputs throughout a drainage network. This adjustment can only be captured numerically using multiple grain sizes or empirical downstream ?ning rules. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

4.
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.  相似文献   

5.
The grain‐scale morphology of fluvial sediments is an important control on the character and dynamics of river systems; however current understanding of its role is limited by the difficulties of robustly quantifying field surface morphology. Terrestrial Laser Scanning (TLS) offers a new methodology for the rapid acquisition of high‐resolution and high‐precision surface elevation data from in situ sediments. To date, most environmental and fluvial applications of TLS have focused on large‐scale systems, capturing macroscale morphologies. Application of this new technology at scales necessary to characterize the complexity of grain‐scale fluvial sediments therefore requires a robust assessment of the quality and sources of errors in close‐range TLS data. This paper describes both laboratory and field experiments designed to evaluate close‐range TLS for sedimentological applications and to develop protocols for data acquisition. In the former, controlled experiments comprising high‐resolution scans of white, grey and black planes and a sphere were used to quantify the magnitude and source of three‐dimensional (3D) point errors resulting from a combination of surface geometry, reflectivity effects and inherent instrument precision. Subsequently, a methodology for the collection and processing of grain‐scale TLS data is described through an application to a coarse grained gravel system, the River Feshie (D50 32 to 63 mm). This stepwise strategy incorporates averaging repeat scans and filtering scan artefact and non‐surface points using local 3D search algorithms. The sensitivity of the results to the filter parameter values are assessed by careful internal validation of Digital Terrain Models (DTMs) created from the resulting point cloud data. The transferability of this methodology is assessed through application to a second river, Bury Green Brook, dominated by finer gravel (D50 18 to 33 mm). The factor limiting the resolution of DTMs created from this second dataset was found to be the relative sizes of the laser footprint and smallest grains. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

6.
If increased sediment supply to a river channel exceeds its transport capacity, deposition necessarily occurs as the bed adjusts to accommodate the increased supply. Both the mean and spatial patterns in bed elevation and grain size may change and an ability to understand their relative importance is needed to predict bed response. We report on an experiment in a field‐scale flume in which sediment supply is increased to a gravel bed with alternate bars. Sediment was recirculated in the experiments, but augmented in two steps, after which the bed was allowed to reach a new steady state. The transport rate at the end of the experiment was three times larger than at the start. High‐resolution sediment flux and topographic measurements, grain size derived from photographs, and hydrodynamic modeling allow us to document the topographic and textural response of the bed to increased sediment supply. The spatial patterns of bed topography and texture were forced by the flume setup and the initial and final steady states included long stationary alternate bars with associated grain size sorting. The transient bed contained several scales of shorter wavelength migrating bedforms superimposed on, and temporarily replacing the stationary alternate bars. Bed topography and textural patterns adjusted to increased sediment supply over different timescales. Bed slope and mean stress increased directly with sediment supply rate to produce a new transport steady state in a time about 2.5 times the minimum needed to deposit the required sediment wedge, indicating a trap efficiency of about 40% for the aggrading wedge. Adjustments in local topography and sorting, primarily in the form of smaller, migrating bars, continued for a period approximately equal to that required to initially reach transport steady state. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

7.
Measurement of riverbed material grain sizes is now a routine part of fieldwork in fluvial geomorphology and lotic ecology. In the last decade, several authors have proposed remote sensing approaches of grain size measurements based on terrestrial and aerial imagery. Given the current rise of small unmanned aerial system (sUAS) applications in geomorphology, there is now increasing interest in the application of these remotely sensed grain size mapping methods to sUAS imagery. However, success in this area has been limited owing to two fundamental problems: lack of constraint of image scale for sUAS imagery and blurring effects in sUAS images and resulting orthomosaics. In this work, we solve the former by showing that SfM‐photogrammetry can be used in a direct georeferencing (DG) workflow (i.e. with no ground validation) in order to predict image scale within margins of 3%. We then propose a novel approach of robotic photosieving of dry exposed riverbed grains that relies on near‐ground images acquired from a low‐cost sUAS and which does not require the presence of ground control points or visible scale objects. We demonstrate that this absence of scale objects does not affect photosieving outputs thus resulting in a low‐cost and efficient sampling method for surficial grains. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   

8.
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.  相似文献   

9.
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  相似文献   

10.
Results from a series of numerical simulations of two‐dimensional open‐channel flow, conducted using the computational fluid dynamics (CFD) code FLUENT, are compared with data quantifying the mean and turbulent characteristics of open‐channel flow over two contrasting gravel beds. Boundary roughness effects are represented using both the conventional wall function approach and a random elevation model that simulates the effects of supra‐grid‐scale roughness elements (e.g. particle clusters and small bedforms). Results obtained using the random elevation model are characterized by a peak in turbulent kinetic energy located well above the bed (typically at y/h = 0·1–0·3). This is consistent with the field data and in contrast to the results obtained using the wall function approach for which maximum turbulent kinetic energy levels occur at the bed. Use of the random elevation model to represent supra‐grid‐scale roughness also allows a reduction in the height of the near‐bed mesh cell and therefore offers some potential to overcome problems experienced by the wall function approach in flows characterized by high relative roughness. Despite these benefits, the results of simulations conducted using the random elevation model are sensitive to the horizontal and vertical mesh resolution. Increasing the horizontal mesh resolution results in an increase in the near‐bed velocity gradient and turbulent kinetic energy, effectively roughening the bed. Varying the vertical resolution of the mesh has little effect on simulated mean velocity profiles, but results in substantial changes to the shape of the turbulent kinetic energy profile. These findings have significant implications for the application of CFD within natural gravel‐bed channels, particularly with regard to issues of topographic data collection, roughness parameterization and the derivation of mesh‐independent solutions. Copyright © 2001 John Wiley & Sons, Ltd.  相似文献   

11.
An estimated 76% of global stream area is occupied by channels with widths above 30 m. Sentinel-2 imagery with resolutions of 10 m could supply information about the composition of river corridors at national and global scales. Fuzzy classification models that infer sub-pixel composition could further be used to compensate for small channel widths imaged at 10 m of spatial resolution. A major challenge to this approach is the acquisition of suitable training data useable in machine learning models that can predict land-cover type information from image radiance values. In this contribution, we present a method which combines unmanned aerial vehicles (UAVs) and Sentinel-2 imagery in order to develop a fuzzy classification approach capable of large-scale investigations. Our approach uses hyperspatial UAV imagery in order to derive high-resolution class information that can be used to train fuzzy classification models for Sentinel-2 data where all bands are super-resolved to a spatial resolution of 10 m. We use a multi-temporal UAV dataset covering an area of 5.25 km2. Using a novel convolutional neural network (CNN) classifier, we predict sub-pixel membership for Sentinel-2 pixels in the fluvial corridor as divided into classes of water, vegetation and dry sediment. Our CNN model can predict fuzzy class memberships with median errors from −5% to +3% and mean absolute errors from 10% to 20%. We also show that our CNN fuzzy predictor can be used to predict crisp classes with accuracies from 95.5% to 99.9%. Finally, we use an example to show how a fuzzy CNN model trained with localized UAV data can be applied to longer channel reaches and detect new vegetation growth. We therefore argue that the novel use of UAVs as field validation tools for freely available satellite data can bridge the scale gap between local and regional fluvial studies. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd  相似文献   

12.
The artificial gravel augmentation of river channels is increasingly being used to mitigate the adverse effects of river regulation and sediment starvation. A systematic framework for designing and assessing such gravel augmentations is still lacking, notably on large rivers. Monitoring is required to quantify the movement of augmented gravel, measure bedform changes, assess potential habitat enhancement, and reduce the uncertainty in sediment management. Here we present the results of an experiment conducted in the Rhine River (French and German border). In 2010, 23 000 m3 of sediments (approximately the mean annual bedload transport capacity) were supplied in a by‐passed reach downstream of the Kembs dam to test the feasibility of enhancing sediment transport and bedform changes. A 620‐m‐long and 12‐m‐wide gravel deposit was created 8 km downstream from the dam. Monitoring included topo‐bathymetric surveys, radio‐frequency particle tracking using passive integrated transponder (PIT) tags, bed grain size measurement, and airborne imagery. Six surveys performed since 2009 have been described (before and after gravel augmentation, and after Q2 and Q15 floods). The key findings are that (i) the augmented gravel was partially dispersed by the first flood event of December 2010 (Q1); (ii) PIT tags were found up to 3200 m downstream of the gravel augmentation site after four years, but the effects of gravel augmentation could not be clearly distinguished from the effects of floods and internal remobilization on more than 3500 m downstream; (iii) linear and log‐linear relationships linking bedload transport, particle mobility, and grain size were established; and (iv) combined bathymetry and PIT tag surveys were useful for evaluating potential environmental risks and the first morpho‐ecological responses. This confirmed the complementary nature of such techniques in the monitoring of gravel augmentation in large rivers. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   

13.
Basin‐scale predictive geomorphic models for river characteristics, particularly grain size, can aid in salmonid habitat identification. However, these basin‐scale methods are largely untested with actual habitat usage data. Here, we develop and test an approach for predicting grain size distributions from high resolution LiDAR (Light Detection and Ranging)‐derived topographic data for a 77 km2 watershed along the central California Coast. This approach improves on previous efforts in that it predicts the full grain size distribution and incorporates an empirically calibrated shear stress partitioning factor. The predicted grain size distributions are used to calculate the fraction of the bed area movable by spawning fish. We then compare the ‘movable fraction’ with 7 years of observed spawning data. We find that predicted movable fraction explains the paucity of spawning in the upper reaches of the study drainage, but does not explain variation along the mainstem. In search of another morphologic characteristic that may help explain the variation within the mainstem, we measure riffle density, a proxy for physical habitat complexity. We find that field surveys of riffle density explain 64% of the variation in spawning in these mainstem reaches, suggesting that within reaches of appropriate sized gravel, spawning density is related to riffle density. Because riffle density varies systematically with channel width, predicting riffle spacing is straightforward with LiDAR data. Taken together, these findings demonstrate the efficacy of basin‐scale spawning habitat predictions made using high‐resolution digital elevation models. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

14.
We present herein clear field evidence for the persistence of a coarse surface layer in a gravel‐bed river during flows capable of transporting all grain sizes present on the channel bed. Detailed field measurements of channel topography and bed surface grain size were made in a gravel‐bed reach of the Colorado River prior to a flood in 2003. Runoff produced during the 2003 snowmelt was far above average, resulting in a sustained period of high flow with a peak discharge of 27 m3/s (170% of normal peak flow); all available grain sizes within the study reach were mobilized in this period of time. During the 2003 peak flow, the river avulsed immediately upstream of the study reach, thereby abandoning approximately one half kilometer of the former channel. The abandonment was rapid (probably within a few hours), leaving the bed texture essentially frozen in place at the peak of the flood. All locations sampled prior to the flood were resampled following the stream abandonment. In response to the high flow, the surface median grain size (D50s) coarsened slightly in the outer part of the bend while remaining nearly constant along the inner part of the bend, resulting in an overall increase from 18 to 21 mm for the study reach. Thus, the coarse bed surface texture persisted despite shear stresses throughout the bend that were well above the critical entrainment value. This may be explained because the response of the bed texture to increases in flow strength depends primarily upon the continued availability of the various grain size percentiles in the supply, which in this case was essentially unlimited for all sizes present in the channel. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

15.
It has recently been demonstrated that surficial grain sizes in fluvial environments could be derived with automated methods applied to airborne digital imagery having a ground resolution of 3 cm. This letter seeks to further examine the potential of digital imagery for automated grain size mapping. In order to broaden the application of automated grain size mapping from airborne imagery, the effect of image resolution needs further study. Automated grain size mapping was attempted on an airborne digital image with a ground resolution of 10 cm. The results show that meaningful grain size information can be derived from 10 cm imagery. However, the ground resolution of the image acts as a size threshold below which no grain size information is detectable. Therefore, these results strongly suggest that future applications of automated grain size mapping will always be dependent on the ground resolution made available by the technology in use at the time of image acquisition. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

16.
Recent developments in remote sensing (RS) technologies lead the way in characterizing river morphology at regional scales and inferring potential channel responses to human pressures. In this paper, a unique regional database of continuous hydromorphological variables (HyMo DB) based on areal and topographic data has been generated from RS analysis. Key riverscape units with specific geomorphic meaning have been automatically mapped for 1700 km2 of river floodplains from simultaneous very‐high‐resolution (VHR) near‐infrared aerial imagery and low‐resolution LiDAR‐derived products. A multi‐level, geographical object‐based architecture (GEOBIA) was employed to integrate both spectral and topographic information and generate a regional classifier able to automatically map heterogeneous fluvial patterns in different geographical and topographical contexts of the Piedmont Region (Italy). This HyMo‐generated DB offers a unique set of tools for hydromorphologists and can be exploited for different purposes. For the first time, topographic information can be exploited regionally per riverscape unit class, allowing for quantitative analysis of their regional spatial and statistical variability. In this manner, river types can be automatically characterized and classified using objective and repeatable hydromorphological variables. We discuss the potential of quantifying functional links between riverscape units and their driving processes, a valuable source of information to start assessing and highlighting the entity of potential channel adjustments at the regional scale to human pressures. The HyMo DB can also be integrated with historical, field‐based information to better comprehend current fluvial changes at a local scale. In view of future RS acquisitions, the present approach will result in a suitable procedure for quantitative, objective and continuous monitoring of river evolutions over large scales. This type of hydromorphological characterization will allow regional trends and patterns to be highlighted through time and river management strategies to thus be implemented at both regional and local scales. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

17.
Subaerial particle size data holds a wealth of valuable information for fluvial, coastal, glacial and other sedimentological applications. Recently, we have gained the opportunity to map and quantify surface particle sizes at the mesoscale using data derived from small unmanned aerial system (sUAS) imagery processed using structure from motion (SfM) photogrammetry. Typically, these sUAS‐SfM approaches have been based on calibrating orthoimage texture or point cloud roughness with particle size. Variable levels of success are reported and a single, robust method capable of producing consistently accurate and precise results in a range of settings has remained elusive. In this paper, we develop an original method for mapping surface particle size with the specific constraints of sUAS and SfM in mind. This method uses the texture of single sUAS images, rather than orthoimages, calibrated with particle sizes normalised by individual image scale. We compare results against existing orthoimage texture and roughness approaches, and provide a quantitative investigation into the implications of the use of sUAS camera gimbals. Our results indicate that our novel single image method delivers an optimised particle size mapping performance for our study site, outperforming both other methods and delivering residual mean errors of 0.02 mm (accuracy), standard deviation of residual errors of 6.90 mm (precision) and maximum residual errors of 16.50 mm. Accuracy values are more than two orders of magnitude worse when imagery is collected by a similar drone which is not equipped with a camera gimbal, demonstrating the importance of mechanical image stabilisation for particle size mapping using measures of image texture. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   

18.
This Virtual Issue highlights 10 recent innovative, unconventional, or otherwise significant contributions to Earth Surface Processes and Landforms that help advance the state‐of‐the‐art in research on linkages between landslides, hillslope erosion, and landscape evolution. The selected studies address this feedback within a temporal spectrum that ranges from the event to the millennial scale, thus underscoring the importance of detailed field observations, high‐resolution digital topographic data, and geochronological methods for increasing our capability of quantifying landslide processes and hillslope erosion. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

19.
Large‐scale flow structures (LSFS) in the streamwise direction are important features of gravel‐bed river flows, because they may contribute to sediment transport and gas exchange. In the present study, these structures are detected using Huang's empirical mode decomposition and reconstructed with phase‐averaging techniques based on a Hilbert transform of the velocity signal. The analysis is based on the fluctuating component of 15 quasi‐instantaneous velocity profiles measured with a three‐dimensional (3D) acoustic Doppler velocity profiler (ADVP) in an armoured gravel‐bed river with a low relative submergence of 2.9 (ratio between flow depth and bed grain diameter). LSFS were identified in most of the measured profiles and consistently showed similar features. We were able to characterize the geometry of these large‐scale coherent structures: the front has a vertical linear shift in the time domain and a vertical profile corresponding to a first quarter moon with the apex situated at z/h ≈ 0.4. In the vertical, the front scales with flow depth h, and in the streamwise direction, LSFS scale with three to seven times the mean flow depth. On the bed, the effect of LSFS is a periodic non‐linear variation of the friction velocity on average between 0.90 and 1.10 times the mean value. A model for the friction velocity cycle resulting from LSFS oscillation is presented. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

20.
Recent growth in the capabilities of unmanned aerial vehicles and systems (UASs) as airborne platforms for collecting environmental data has been very rapid. There are now ample examples in the literature of UASs being deployed to map fine‐scale vegetation, glacial, soil and atmospheric conditions. The purported advantages of UASs are their ability to collect spatial data at lower cost, lower risk, higher resolution and higher frequency than ground surveys or satellite platforms. In this specific study, whether or not obtaining high‐resolution UAS imagery was advantageous for identifying an intermittent stream network was determined by comparing it with coarse‐scale satellite imagery collected for the same purpose. It was also determined if the UAS imagery could be an improvement to Global Positioning System acquired ground‐truth points for classifying an intermittent stream network across the same large‐scale satellite image. The UAS‐acquired and satellite‐acquired imageries were derived from a visible spectrum camera capable of 2‐cm resolution and multispectral SPOT‐5 with 10‐m resolution, respectively. The SPOT‐5 imagery with its relatively coarse resolution could not always detect the narrow intermittent stream, which was well resolved in the UAS imagery. When a classified UAS image was applied as a training area for the SPOT‐5 image, the identification of the stream network and accuracy of the satellite imagery classification did not necessarily improve. UASs have the potential to revolutionize hydrological research the same way that geographic information systems did three decades ago. A final goal of the paper is to provide insight into the advantages and disadvantages of deploying a UAS for this kind of research. © 2015 Her Majesty the Queen in Right of Canada. Hydrological Processes. © 2015 John Wiley & Sons, Ltd.  相似文献   

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