Size Ratio of Fluvial Grains’ Intermediate Axes Assessed by Image Processing and Square-Hole Sieving

Stähly, Severin; Friedrich, Heide; Detert, Martin

doi:10.1061/(asce)hy.1943-7900.0001286

Cited by 24 publications

(21 citation statements)

References 7 publications

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“…The software program BASEGRAIN (Detert and Weitbrecht 2013) was utilized to obtain the B-axis measurements for all visible particles in the bed surface photos. Further technical details on the software capabilities can be found in Stähly et al 2017. A 50 cm x 50 cm area in the center of the study reach was used for the analysis.…”

Section: Particle Clustering Analysismentioning

confidence: 99%

How Large Immobile Sediments in Gravel Bed Rivers Impact Sediment Transport and Bed Morphology

et al. 2021

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Section: Particle Clustering Analysismentioning

confidence: 99%

How Large Immobile Sediments in Gravel Bed Rivers Impact Sediment Transport and Bed Morphology

et al. 2021

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“…Differences in particle shape and size favour burial and overlapping due to imbrication of stones when they settle. These effects have been studied in the application of image‐based surface sampling methods (Graham et al, 2010; Stähly et al, 2017) and contributed to the limited recovery rate. Particles with the same b ‐axis are transported at a significantly smaller discharge when they are disc shaped rather than rod‐like shaped.…”

Section: Discussionmentioning

confidence: 99%

“…The d 90 value corresponds to the grain size of the armour layer in the riverbed. The grain size distribution was determined by analysing 21 samples using pebble counts (Fehr, 1987) and photo sieving from BASEGRAIN (Stähly et al, 2017). The fine sediment contribution to d m and d 90 was estimated to be 25% (Fehr, 1987).…”

Section: Introductionmentioning

confidence: 99%

Erosion, transport and deposition of a sediment replenishment under flood conditions

Stähly

Franca

Robinson

et al. 2020

Earth Surf Processes Landf

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River reaches downstream of dams with constant residual discharge often lack sediment supply and periodic high flows due to dam sediment retention and flow regulation, respectively. To test a novel multi-deposit methodology for defining environmental flows for activating the dynamics of the river morphology downstream of dams, a flood was released from Rossens Dam in Switzerland. This event was combined for the first time with a multi-deposit configuration of sediment replenishment consisting of four artificial deposits allocated as alternate bars along the riverbanks as a restoration measure. To validate the sediment transport behaviour observed in laboratory tests, stones were equipped with radiofrequency identification (RFID) passive integrated transponder (PIT) tags, a fixed antenna was installed at the river bed and a mobile antenna was used to enable the investigation of the erosion, transport and deposition of replenished sediments. The duration of the erosion period was determined for the tracked stones, and average transport velocities were found to be on the order of 10-3 m/s. To estimate the erosion efficiency of the flood, defined as the eroded tagged stones compared with the released water volume, the hydrograph was divided into different periods: rising limb, constant peak discharge, decreasing limb. During the rising limb of the flood, which lasted for 20% of the total flood duration, more than 40% of the PIT tags were transported. The defined erosion efficiency is a measure to support the hydrographic design of artificial flood releases from dams. The deposition of tagged stones resulted in a repeating cluster formation, as expected from previous laboratory experiments, creating an increase in hydraulic habitat diversity. Comparison of the results obtained in the field and from laboratory experiments confirmed the robustness of the multi-deposit sediment replenishment method. Combined with the knowledge gained on the erosion efficiency, these results could motivate further applications and research into multi-deposit sediment replenishment techniques as a habitat-oriented river restoration measure.

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“…(2) Calculation of atmospheric light intensity Using the dark channel a priori theory, the atmospheric light intensity G of the non-sky part of the sub-image is calculated, which can overcome the adverse interference of high-level noise or high-luminance scenes on the atmospheric light intensity calculation [22].…”

Section: ) Image Area Divisionmentioning

confidence: 99%

Real-time Defogging of Single Image of IoTs-based Surveillance Video Based on MAP

Liu

2020

Teh. vjesn.

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Due to the atmospheric scattering phenomenon in fog weather, the current monitoring video image defogging method cannot estimate the fog density of the image. This paper proposes a real-time defogging algorithm for single images of IoTs surveillance video based on maximum a posteriori (MAP). Under the condition of single image sequence, the posterior probability of the high-resolution single image is set to the maximum, which improves the MAP design super-resolution image reconstruction. This paper introduces fuzzy classification to calculate atmospheric light intensity, and obtains a single image of IoTs surveillance video by the atmospheric dissipation function. The improved algorithm has the largest signal-to-noise ratio after defogging, and the maximum value is as high as 40.99 dB. The average time for defogging of 7 experimental surveillance video images is only 2.22 s, and the real-time performance is better. It can be concluded that the proposed algorithm has excellent defogging performance and strong applicability.

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Size Ratio of Fluvial Grains’ Intermediate Axes Assessed by Image Processing and Square-Hole Sieving

Cited by 24 publications

References 7 publications

How Large Immobile Sediments in Gravel Bed Rivers Impact Sediment Transport and Bed Morphology

How Large Immobile Sediments in Gravel Bed Rivers Impact Sediment Transport and Bed Morphology

Erosion, transport and deposition of a sediment replenishment under flood conditions

Real-time Defogging of Single Image of IoTs-based Surveillance Video Based on MAP

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