Aerial photosieving of exposed gravel bars for the rapid calibration of airborne grain size maps

2010 ◽  
pp. n/a-n/a ◽  
Author(s):  
Stephen J. Dugdale ◽  
Patrice E. Carbonneau ◽  
David Campbell
Keyword(s):  
Grain Size ◽  
Gravel Bars ◽  
Rapid Calibration

scholarly journals GRAINet: mapping grain size distributions in river beds from UAV images with convolutional neural networks

2021 ◽  
Vol 25 (5) ◽  
pp. 2567-2597
Author(s):  
Nico Lang ◽  
Andrea Irniger ◽  
Agnieszka Rozniak ◽  
Roni Hunziker ◽  
Jan Dirk Wegner ◽  
...  
Keyword(s):  
Grain Size ◽  
Training Data ◽  
Grain Size Analysis ◽  
Training Dataset ◽  
Size Analysis ◽  
Size Distributions ◽  
Mean Diameter ◽  
Grain Size Distributions ◽  
Gravel Bars ◽  
Uav Images

Abstract. Grain size analysis is the key to understand the sediment dynamics of river systems. We propose GRAINet, a data-driven approach to analyze grain size distributions of entire gravel bars based on georeferenced UAV images. A convolutional neural network is trained to regress grain size distributions as well as the characteristic mean diameter from raw images. GRAINet allows for the holistic analysis of entire gravel bars, resulting in (i) high-resolution estimates and maps of the spatial grain size distribution at large scale and (ii) robust grading curves for entire gravel bars. To collect an extensive training dataset of 1491 samples, we introduce digital line sampling as a new annotation strategy. Our evaluation on 25 gravel bars along six different rivers in Switzerland yields high accuracy: the resulting maps of mean diameters have a mean absolute error (MAE) of 1.1 cm, with no bias. Robust grading curves for entire gravel bars can be extracted if representative training data are available. At the gravel bar level the MAE of the predicted mean diameter is even reduced to 0.3 cm, for bars with mean diameters ranging from 1.3 to 29.3 cm. Extensive experiments were carried out to study the quality of the digital line samples, the generalization capability of GRAINet to new locations, the model performance with respect to human labeling noise, the limitations of the current model, and the potential of GRAINet to analyze images with low resolutions.

scholarly journals GRAINet: Mapping grain size distributions in river beds from UAV images with convolutional neural networks

2020 ◽  
Author(s):  
Nico Lang ◽  
Andrea Irniger ◽  
Agnieszka Rozniak ◽  
Roni Hunziker ◽  
Jan Dirk Wegner ◽  
...  
Keyword(s):  
Grain Size ◽  
Training Data ◽  
Grain Size Analysis ◽  
Training Dataset ◽  
Size Distributions ◽  
Line Sampling ◽  
Mean Diameter ◽  
Grain Size Distributions ◽  
Gravel Bars ◽  
Uav Images

Abstract. Grain size analysis is the key to understand the sediment dynamics of river systems. We propose GRAINet, a data-driven approach to analyze grain size distributions of entire gravel bars based on georeferenced UAV images. A convolutional neural network is trained to regress grain size distributions as well as the characteristic mean diameter from raw images. GRAINet allows the holistic analysis of entire gravel bars, resulting in (i) high-resolution maps of the spatial grain size distribution at large scale, and (ii) robust grading curves for entire gravel bars. To collect a large training dataset of 1,491 samples, we introduce digital line sampling as a new annotation strategy, following the widely applied line sampling analysis of Fehr (1987). Our evaluation on 25 gravel bars along 6 different rivers in Switzerland yields high accuracy: The resulting maps of mean diameters have a mean absolute error of 1.1 cm, with no bias. Robust grading curves for entire gravel bars can be extracted if representative training data is available. At the gravel bar level the MAE error of the predicted mean diameter is even reduced to 0.3 cm. Extensive experiments were carried out to study the quality of the digital line samples, the generalization capability of GRAINet to new locations, the model performance w.r.t. human labeling noise, the limitations of the current model, and the potential of GRAINet to analyze images with low resolutions.

scholarly journals PODMÍNKY TRANSPORTU A AKUMULACE SEDIMENTŮ V ČLOVĚKEM OVLIVNĚNÝCH KORYTECH BESKYDSKÝCH TOKŮ: PŘÍKLADOVÁ STUDIE SOUTOKU ŘEKY MORÁVKY A MOHELNICE

2012 ◽  
Vol 19 (1-2) ◽  
Author(s):  
Václav Škarpich ◽  
Tomáš Galia ◽  
Jan Hradecký
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Sediment Supply ◽  
Sediment Flux ◽  
Transport Parameters ◽  
Sediment Delivery ◽  
Load Transport ◽  
Gravel Bars ◽  
Gravel Bed Streams

This paper summarizes results of grain-size distribution of gravel bars and transport conditions in the context of sediment sources in the confl uence area of the Morávka and Mohelnice rivers (Moravskoslezské Beskydy Mts). We deal with a hypothesis that general changes of grain-size distribution of gravel bars are controlled by disconnection in sediment flux in the Morávka River and, by contrast, that higher sediment delivery is related to the Mohelnice river basin. The second focus is the evaluation of fluvial transport parameters of a channel influenced by control works and sediment mining. Bed load transport research was conducted with the application of BAGS (Bedload Assessment for Gravel-bed Streams) spreadsheet-based program. Sediment analysis of the channel confluence showed limited sediment supply character indicated by coarser sediment delivery from the Morávka River. This fact is related to the effect of hungry water caused mainly by the Morávka Reservoir. On the other hand, the Mohelnice River displayed trends of relatively higher sediment delivery without potential disconnectivities in sediment flux. Results of this analysis brought an insight into a potential scheme of the future development of the studied reaches. We suppose preservation of recent trends in case of the occurrence of signifi cant changes in land use or watershed management.

scholarly journals Conglomerate recycling in the Himalayan foreland basin: Implications for grain size and provenance

2019 ◽  
Vol 132 (7-8) ◽  
pp. 1639-1656 ◽  
Author(s):  
Laura Quick ◽  
H.D. Sinclair ◽  
M. Attal ◽  
V. Singh
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Significant Proportion ◽  
Foreland Basin ◽  
Source Area ◽  
Mountain Range ◽  
Gangetic Plain ◽  
Mountain Front ◽  
Gravel Bars

Abstract The nature of coarse sediment in rivers emerging from mountain ranges determines rates of downstream fining, the position of the gravel-sand transition, sediment entrainment thresholds, and channel morphologies. Additionally, in the stratigraphic record, clast size distributions and lithologies are used to reconstruct paleo-hydraulic conditions and source area provenance. Using Himalayan rivers, we demonstrate that the signal of first-generation clasts derived from the hinterland of a mountain range can be significantly altered by recycling older, structurally exhumed foreland deposits. The Siwalik foothills of the Himalaya comprise Neogene fluvial sandstones and quartzite-rich conglomerates with well-rounded clasts that were deposited in the Indo-Gangetic foreland basin and later exhumed by erosion, following uplift along the Himalayan mountain front. Mass balance calculations reveal that the Upper Siwalik conglomerate may contribute a significant proportion of the total gravel flux exported from the main Himalayan catchments (up to 100%) despite forming <1% of the catchment geology. Three end-member catchments with variable proportions of gravel flux from Siwalik conglomerates are analyzed to test for the effects of conglomerate recycling. Catchments that recycle the most Upper Siwalik conglomerate form quartzite-rich gravel bars comprising well-rounded pebbles and a narrow grain size distribution, mimicking the characteristics of the Upper Siwalik conglomerate. Conversely, catchments that recycle the least Upper Siwalik conglomerate form gravel bars with a range of Himalayan lithologies, angular quartzite pebbles and a wider grain size distribution. This study highlights that recycling of quartzite-rich conglomerate can dramatically modify the flux, lithology, grain size, and shape of gravel entering the Indo-Gangetic Plain.

High-resolution grain-size characterisation of gravel bars using imagery analysis and geo-statistics

Geomorphology ◽  
2005 ◽  
Vol 72 (1-4) ◽  
pp. 73-93 ◽  
Author(s):  
Joan M. Verdú ◽  
Ramon J. Batalla ◽  
José A. Martínez-Casasnovas
Keyword(s):  
Grain Size ◽  
High Resolution ◽  
Gravel Bars

Using UAS optical imagery and SfM photogrammetry to characterize the surface grain size of gravel bars in a braided river (Vénéon River, French Alps)

Geomorphology ◽  
2017 ◽  
Vol 285 ◽  
pp. 94-105 ◽  
Author(s):  
Daniel Vázquez-Tarrío ◽  
Laurent Borgniet ◽  
Frédéric Liébault ◽  
Alain Recking
Keyword(s):  
Grain Size ◽  
Braided River ◽  
French Alps ◽  
Gravel Bars ◽  
Optical Imagery

Effect of Shock Loading on the Microstructure of Uniloy 326

1974 ◽  
Vol 32 ◽  
pp. 504-505
Author(s):  
K. P. Staudhammer ◽  
L. E. Murr
Keyword(s):  
Grain Size ◽  
Shock Loading ◽  
Current Investigation ◽  
Two Phase ◽  
05 C ◽  
Shock Deformation ◽  
Heat Treated

The effect of shock loading on a variety of steels has been reviewed recently by Leslie. It is generally observed that significant changes in microstructure and microhardness are produced by explosive shock deformation. While the effect of shock loading on austenitic, ferritic, martensitic, and pearlitic structures has been investigated, there have been no systematic studies of the shock-loading of microduplex structures.In the current investigation, the shock-loading response of millrolled and heat-treated Uniloy 326 (thickness 60 mil) having a residual grain size of 1 to 2μ before shock loading was studied. Uniloy 326 is a two phase (microduplex) alloy consisting of 30% austenite (γ) in a ferrite (α) matrix; with the composition.3% Ti, 1% Mn, .6% Si,.05% C, 6% Ni, 26% Cr, balance Fe.

Aspects of microanalysis in a transmission electron microscope

1978 ◽  
Vol 36 (1) ◽  
pp. 510-511
Author(s):  
R. Sinclair ◽  
B.E. Jacobson
Keyword(s):  
Grain Size ◽  
Electron Beam ◽  
Electron Microscope ◽  
Chemical Analysis ◽  
Transmission Electron Microscope ◽  
Vapor Deposition ◽  
Critical Currents ◽  
X Ray ◽  
Fine Grain ◽  
Transmission Electron

INTRODUCTIONThe prospect of performing chemical analysis of thin specimens at any desired level of resolution is particularly appealing to the materials scientist. Commercial TEM-based systems are now available which virtually provide this capability. The purpose of this contribution is to illustrate its application to problems which would have been intractable until recently, pointing out some current limitations.X-RAY ANALYSISIn an attempt to fabricate superconducting materials with high critical currents and temperature, thin Nb3Sn films have been prepared by electron beam vapor deposition [1]. Fine-grain size material is desirable which may be achieved by codeposition with small amounts of Al2O3 . Figure 1 shows the STEM microstructure, with large (∽ 200 Å dia) voids present at the grain boundaries. Higher quality TEM micrographs (e.g. fig. 2) reveal the presence of small voids within the grains which are absent in pure Nb3Sn prepared under identical conditions. The X-ray spectrum from large (∽ lμ dia) or small (∽100 Ǻ dia) areas within the grains indicates only small amounts of A1 (fig.3).

Sign in / Sign up

Export Citation Format

Share Document