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

Verdú, Joan M.; Batalla, Ramón J.; Martínez‐Casasnovas, José A.

doi:10.1016/j.geomorph.2005.04.015

Cited by 70 publications

(76 citation statements)

References 24 publications

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“…Fonstad and Marcus, 2010). Early progress toward automated estimation of bed material grain size at bar-scales (Chandler et al, 2004;Verdu et al, 2005) and along entire rivers (Carbonneau et al, 2004(Carbonneau et al, , 2005 has been extended by using imagery to accomplish the necessary grain-size calibration (Dugdale et al, 2010), by avoiding the need for calibration at all (Buscombe and Masselink, 2009;Buscombe et al, 2010) and by using hyperspatial data (<100mm resolution) to map sub-pixel grain sizes (Black et al, 2014). These advances mean that it is feasible to aquire continuous bed material grain size information and identify tributary-driven confluence aggradation and sedimentary links at network scales (Fonstad and Marcus, 2010).…”

Section: Discussionmentioning

confidence: 99%

Tributary connectivity, confluence aggradation and network biodiversity

Rice

2017

Geomorphology

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In fluvial networks, some confluences are associated with tributary-driven aggradation where coarse sediment is stored, downstream sediment connectivity is interrupted and substantial hydraulic and morphological heterogeneity is generated. To the extent that biological diversity is supported by physical diversity, it has been proposed that the distribution and frequency of tributary-driven aggradation is important for the magnitude and spatial structure of river biodiversity. Relevant ideas are formulated within the Link Discontinuity Concept and the Network Dynamics Hypothesis, but many of the issues raised by these conceptual models have not been systematically evaluated. This paper first tests an automated method for predicting the likelihood of tributary-driven aggradation in three large drainage networks in the Rocky Mountain foothills, Canada. The method correctly identified approximately 75% of significant tributary confluences and 97% of insignificant confluences. The method is then used to evaluate two hypotheses of the Network Dynamics Hypothesis: that linear-shaped basins are more likely to show a longitudinal, downstream decline in tributary-driven aggradation; and that larger and more compact basins contain more confluences with a high probability of impact. The use of a predictive model that included a measure of tributary basin sediment delivery, rather than symmetry ratio alone, mediated the outcomes somewhat, but as anticipated, the number of significant confluences increased with basin size and basin shape was a strong control of the number and distribution of significant confluences. Doubling basin area led to a 1.9-fold increase in the number of significant confluences and compact basins contained approximately twice as many significant confluences per unit channel length as linear basins. In compact basins, significant confluences were more widely distributed, whereas in linear basins they were concentrated in proximal reaches. Interesting outstanding issues include the possibility of using spatially-distributed sediment routing models to predict tributary-driven confluence aggradation and the need to gather ecological data sufficient to properly test for increases in local and network-scale biodiversity associated with significant confluences and their network-scale controls.

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Section: Discussionmentioning

confidence: 99%

Tributary connectivity, confluence aggradation and network biodiversity

Rice

2017

Geomorphology

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“…Previous developments in remote sensing have shown that the application of image processing techniques to either airborne multispectral (Rainey et al, 2003) or conventional RGB photographic data (Carbonneau et al, 2004(Carbonneau et al, , 2005aVerdú et al, 2005) can be employed for large-scale fl uvial grain size analysis. Rainey et al (2003) demonstrated that it was possible to produce maps of clay, mud and silt abundance from multispectral imagery with a resolution of 1·75 m. However, the relative cost of multispectral imagery and coarseness of pixel size in comparison with standard RGB aerial photography limits the applicability of such a technique to higher order rivers.…”

Section: Introductionmentioning

confidence: 99%

“…Rainey et al (2003) demonstrated that it was possible to produce maps of clay, mud and silt abundance from multispectral imagery with a resolution of 1·75 m. However, the relative cost of multispectral imagery and coarseness of pixel size in comparison with standard RGB aerial photography limits the applicability of such a technique to higher order rivers. Carbonneau et al (2004Carbonneau et al ( , 2005a and Verdú (2005) used an empirical approach to examine the relationship between fl uvial grain size and local image properties computed on high-resolution (30-100 mm ground resolution) RGB imagery. These authors found that textural properties which quantify local variability in small subgroups of pixels correlated well with human visual perception of grain size variations.…”

Section: Introductionmentioning

confidence: 99%

“…Although Carbonneau et al (2004) only examined the texture/ semivariance-grain size relationship for exposed gravel facies, Carbonneau et al (2005a) extended this method to allow mapping of submerged gravels in the wetted channel, through comparing the image semivariance on the submerged side of the wetted perimeter to adjacent grain size values on the exposed side of the wetted perimeter. Verdú et al (2005) examined the relationship between percentile grain size and semivariance at various distances from a reference pixel in order to investigate the semivariance 'signatures' produced by various grain sizes. They reported that for imagery with a resolution of 60 mm, grain size percentiles greater than D 40 related directly to semivariance.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, minor variations in image resolution and exposure caused by fl ight altitude and velocity may vary between aerial surveys, further emphasising the need for sitespecifi c calibration relationships. Verdú et al (2005) also highlighted the possibility of errors associated with the accurate geolocation of ground samples to georeferenced imagery.…”

Section: Introductionmentioning

confidence: 99%

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

Dugdale¹,

Carbonneau

Campbell³

2010

Earth Surf Processes Landf

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In recent years, fl uvial remote sensing has seen considerable progress in terms of methods capable of system scale characterisation of river catchments. One key development is automated grain size mapping. It has been shown that high resolution aerial photography can be used to automatically produce grain size maps over entire rivers. However, current aerial grain size mapping procedures all require fi eld calibration data. The collection of such data can be costly and problematic in the case of remote areas. This paper presents a method developed to remove the need for fi eld based calibration data. Called 'aerial photosieving', this method consists of using the same very high resolution aerial imagery intended for grain size map production to visually measure particle sizes on-screen in order to provide calibration data. The paper presents a rigorous comparison of fi eldbased photosieving calibration data and aerial photosieving calibration data. Statistical tests are used to demonstrate that aerial photosieving gives similar results when compared with fi eld-based data with only a slight systematic overprediction. The new aerial photosieving method therefore simplifi es the overall procedure required for the production of grain size maps and thus improves the cost-effectiveness and potential availability of this new fl uvial remote sensing technology.

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