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Earth Surface Dynamics An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/esurf-2019-20
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-2019-20
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 23 Apr 2019

Research article | 23 Apr 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Earth Surface Dynamics (ESurf).

Introducing PebbleCounts: A grain-sizing tool for photo surveys of dynamic gravel-bed rivers

Benjamin Purinton and Bodo Bookhagen Benjamin Purinton and Bodo Bookhagen
  • Institute of Earth and Environmental Science, Universität Potsdam, Potsdam, Germany

Abstract. Grain-size distributions are a key geomorphic metric of gravel-bed rivers. Traditional measurement methods include manual counting or photo sieving, but these are achievable only at the 1–10 m2 scale. With the advent of unmanned aerial vehicles and increasingly high-resolution cameras, we can now generate orthoimagery over hectares at sub-cm resolution. These scales, along with the complexity of high-mountain rivers, necessitate different approaches for photo sieving. As opposed to other image segmentation methods that use a watershed approach to automatically segment entire images, our open-source algorithm, PebbleCounts, relies on k-means clustering in the spatial and spectral domain and rapid manual selection of well-delineated grains. The result is improved grain-size estimates for complex river-bed imagery, without any post processing. In a second step, we develop a fully automated method, PebbleCountsAuto, that relies on edge detection and filtering suspect grains, without the k-means clustering or manual selection steps. The algorithms are tested in controlled indoor conditions on three arrays of pebbles and then applied to 12 × 1 m2 orthomosaic clips of high-energy mountain rivers collected with a camera-on-mast setup (akin to a low-flying drone). A 20-pixel b-axis length lower truncation is necessary for attaining accurate grain-size distributions. For the k-means PebbleCounts approach, average percentile bias and precision are 0.03 and 0.09 ψ, respectively, for ~ 1.16 mm/pixel images, and 0.07 and 0.05 ψ for one 0.32 mm/pixel image. The automatic approach has higher bias and precision of 0.13 and 0.15 ψ, respectively, for ~ 1.16 mm/pixel images, but similar values of −0.06 and 0.05 ψ for one 0.32 mm/pixel image. For the automatic approach, only at best 70 % of the grains are correct identifications, and typically around 50 %. PebbleCounts operates most effectively at the 1 m2 scale, where the algorithm can be rapidly applied in ~ 5 minutes in many small areas to acquire accurate grain-size data over 10–100 m2 areas. These data can be used to validate PebbleCountsAuto applied at the scale of entire survey sites (102–104 m2). We synthesize results and recommend best practices for image collection, orthomosaic generation, and grain-size measurement using both algorithms.

Benjamin Purinton and Bodo Bookhagen
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Status: open (until 04 Jun 2019)
Status: open (until 04 Jun 2019)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Benjamin Purinton and Bodo Bookhagen
Model code and software

PebbleCounts B. Purinton and B. Bookhagen https://doi.org/10.5880/fidgeo.2019.007

Benjamin Purinton and Bodo Bookhagen
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Latest update: 22 May 2019
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Short summary
We develop and test new methods for counting pebble-size distributions in photos of gravel-bed rivers. Our open-source algorithms provide good estimates in complex imagery from high-energy mountain rivers. We discuss methods of river cross section photo collection and processing into seamless georeferenced imagery. Application of a semi-automated version of the algorithm in small patches can be used as validation data for upscaling to entire survey sites using a fully automated version.
We develop and test new methods for counting pebble-size distributions in photos of gravel-bed...
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