Catchment‐scale mapping of surface grain size in gravel bed rivers using airborne digital imagery

Carbonneau, Patrice; Lane, Stuart N.; Bergeron, Normand

doi:10.1029/2003wr002759

Cited by 172 publications

(262 citation statements)

References 34 publications

(42 reference statements)

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“…In ground-based photography (Rubin, 2004;Warrick et al, 2009) and airborne photography (Carbonneau et al, 2004(Carbonneau et al, , 2005Dugdale et al, 2010), relationships were found between grain-size properties and the pixel properties. These properties, such as pixel brightness, are measured using approaches based on spatial statistics.…”

Section: Introductionmentioning

confidence: 99%

“…This method used as well by Warrick et al (2009) can be applied to a large range of grain sizes. The second approach based on spatial statistics consists in measuring the local semi-variance, which is a function of the difference in brightness and the distance between these pixels (Carbonneau et al, 2004). This second method was applied in airborne photography for the grain-size mapping of river catchment areas (Carbonneau et al, 2004(Carbonneau et al, , 2005Dugdale et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…The second approach based on spatial statistics consists in measuring the local semi-variance, which is a function of the difference in brightness and the distance between these pixels (Carbonneau et al, 2004). This second method was applied in airborne photography for the grain-size mapping of river catchment areas (Carbonneau et al, 2004(Carbonneau et al, , 2005Dugdale et al, 2010). An application of the Carbonneau et al (2005) method was used to study the evolution of braided river deposit in a flume experiment (Gardner and Ashmore, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Image analysis for measuring the size stratification in sand–gravel laboratory experiments

et al. 2014

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Abstract. Measurements of spatial and temporal changes in the grain-size distribution of the bed surface and substrate are crucial to improving the modelling of sediment transport and associated grain-size selective processes. We present three complementary techniques to determine such variations in the grain-size distribution of the bed surface in sand-gravel laboratory experiments, as well as the resulting size stratification: (1) particle colouring, (2) removal of sediment layers, and (3) image analysis. The resulting stratification measurement method was evaluated in two sets of experiments. In both sets three grain-size fractions within the range of coarse sand to fine gravel were painted in different colours. Sediment layers are removed using a wet vacuum cleaner. Subsequently areal images are taken of the surface of each layer. The areal fraction content, that is, the relative presence of each size fraction over the bed surface, is determined using a colour segmentation algorithm which provides the areal fraction content of a specific colour (i.e. grain size) covering the bed surface. Particle colouring is not only beneficial to this type of image analysis but also to the observation and understanding of grain-size selective processes. The size stratification based on areal fractions is measured with sufficient accuracy. Other advantages of the proposed size stratification measurement method are (a) rapid collection and processing of a large amount of data, (b) a very high spatial density of information on the grain-size distribution, (c) the lack of disturbances to the bed surface, (d) only minor disturbances to the substrate due to the removal of sediment layers, and (e) the possibility to return a sediment layer to its original elevation and continue the flume experiment. The areal fractions are converted into volumetric fractions using an existing conversion model.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Image analysis for measuring the size stratification in sand–gravel laboratory experiments

et al. 2014

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“…For example, image texture has been used successfully to estimate bed sediment size as areas with larger sediment have more shadows, which suggest a more heterogeneous texture (Carbonneau et al 2004(Carbonneau et al , 2005Buscombe et al 2010). Hyperspectral data have been particularly useful at this scale.…”

Section: Woody Debris (Smikrud and Prakash 2006)mentioning

confidence: 99%

“…Bed sediment size (Carbonneau et al 2004(Carbonneau et al , 2005 Bank sediment size (Rainey et al 2003) High resolution multi-spectral Hyperspectral…”

Section: Sediment Sizementioning

confidence: 99%

The use of remote sensing to characterise hydromorphological properties of European rivers

et al. 2015

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Remote sensing (RS) technology offers unparalleled opportunities to explore river systems using RADAR, multispectral, hyper spectral, and LiDAR data. The accuracy reached by these technologies recently has started to satisfy the spatial and spectral resolutions required to properly analyse the hydromorphological character of river systems at multiple scales. Using the River Hierarchical Framework (RHF) as a reference we describe the state-of-the-art RS technologies that can be implemented to quantify hydromorphological characteristics at each of the spatial scales incorporated in the RHF (i. e. catchment, landscape unit, river segment, river reach, sub-reach-geomorphic and hydraulic units). We also report the results of a survey on RS data availability in EU member states that shows the current potential to derive RHF hydromorphological indicators from high-resolution multispectral images and topographic LiDAR at the national scale across Europe. This paper shows that many of the assessment indicators proposed by the RHF can be derived by different RS sources and existing methodologies, and that EU countries have sufficient RS data at present to already begin their incorporation into hydromorphological assessment and monitoring, as mandated by WFD. With cooperation and planning, RS data can form a fundamental component of hydromorphological assessment and monitoring in the future to help support the effective and sustainable management of rivers, and this would be done most effectively through the establishment of multi-purpose RS acquisition campaigns and the development of shared and standardized hydromorphological RS databases updated regularly through planned resurveyed campaigns.

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Morphodynamics: Rivers beyond steady state

Church

Ferguson

2015

Water Resources Research

167

116

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The morphology of an alluvial river channel affects the movement of water and sediment along it, but in the longer run is shaped by those processes. This interplay has mostly been investigated empirically within the paradigm of Newtonian mechanics. In rivers, this has created an emphasis on equilibrium configurations with simple morphology and uniform steady flow. But transient adjustment, whether between equilibrium states or indefinitely, is to be expected in a world in which hydrology, sediment supply, and base level are not fixed. More fundamentally, water flows and all the phenomena that accompany them are inherently unsteady, and flows in natural channels are characteristically nonuniform. The morphodynamics of alluvial river channels is the striking consequence. In this paper, we develop the essential connection between the episodic nature of bed material transport and the production of river morphology, emphasizing the fundamental problems of sediment transport, the role of bar evolution in determining channel form, the role of riparian vegetation, and the wide range of time scales for change. As the key integrative exercise, we emphasize the importance of physics-based modeling of morphodynamics. We note consequences that can be of benefit to society if properly understood. These include the possibility to better be able to model how varying flows drive morphodynamic change, to understand the influence of the sediments themselves on morphodynamics, and to recognize the inherent necessity for rivers that transport bed material to deform laterally. We acknowledge pioneering contributions in WRR and elsewhere that have introduced some of these themes.

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Catchment‐scale mapping of surface grain size in gravel bed rivers using airborne digital imagery

Cited by 172 publications

References 34 publications

Image analysis for measuring the size stratification in sand–gravel laboratory experiments

Image analysis for measuring the size stratification in sand–gravel laboratory experiments

The use of remote sensing to characterise hydromorphological properties of European rivers

Morphodynamics: Rivers beyond steady state

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