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Erschienen in: Earth Science Informatics 4/2021

09.07.2021 | Software Article

FKgrain: A topography-based software tool for grain segmentation and sizing using factorial kriging

verfasst von: Fu-Chun Wu, Chi-Kuei Wang, Hong Ping Lo

Erschienen in: Earth Science Informatics | Ausgabe 4/2021

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Abstract

The grain size distribution (GSD) of a river bed is fundamental information required for studies of fluvial, morphological, and ecological processes. To achieve higher efficiency, numerous efforts have been devoted to developing the techniques of automated grain sizing. These techniques can be categorized as the image-based or topography-based approach according to the input data used. Each category is further subdivided into three groups based on the output result, namely: individual GSD, statistical GSD, or characteristic grain sizes. Existing software for automated grain sizing covers the image-based approaches for all three types of output, and topography-based approaches for statistical GSD and characteristic grain sizes. To date, however, no software has been developed that uses 3D topographic data to delineate individual grains and estimate their GSD. Here, we present a first-ever topography-based software tool, FKgrain, for automated grain segmentation and sizing. FKgrain adopts factorial kriging to decompose the grain-scale component of digital elevation model (DEM), whose zero-level contours are then used as the input for morphological grain segmentation. FKgrain exports the shapefiles of the delineated grains and their ellipse fits, whose minor axes can be used to derive the individual GSD. An application example demonstrates that FKgrain is efficient in producing useful results that are comparable to those obtained by traditional, time-consuming and laborious manual digitization of grain images.

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Literatur
Zurück zum Zitat Bunte K, Abt SR (2001) Sampling surface and subsurface particle-size distributions in wadable gravel- and cobble-bed streams for analysis in sediment transport, hydraulics, and streambed monitoring. General Technical Report RMRS-GTR-74. USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, p 428. https://www.fs.usda.gov/treesearch/pubs/4580 Bunte K, Abt SR (2001) Sampling surface and subsurface particle-size distributions in wadable gravel- and cobble-bed streams for analysis in sediment transport, hydraulics, and streambed monitoring. General Technical Report RMRS-GTR-74. USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, p 428. https://​www.​fs.​usda.​gov/​treesearch/​pubs/​4580
Zurück zum Zitat Buscombe D (2008) Estimation of grain-size distributions and associated parameters from digital images of sediment. Sed Geol 210:1–10CrossRef Buscombe D (2008) Estimation of grain-size distributions and associated parameters from digital images of sediment. Sed Geol 210:1–10CrossRef
Zurück zum Zitat Buscombe D (2013) Transferable wavelet method for grain-size distribution from images of sediment surfaces and thin sections, and other natural granular patterns. Sedimentology 60:1709–1732CrossRef Buscombe D (2013) Transferable wavelet method for grain-size distribution from images of sediment surfaces and thin sections, and other natural granular patterns. Sedimentology 60:1709–1732CrossRef
Zurück zum Zitat Buscombe D (2016) Spatially explicit spectral analysis of point clouds and geospatial data. Comput Geosci 86:92–108CrossRef Buscombe D (2016) Spatially explicit spectral analysis of point clouds and geospatial data. Comput Geosci 86:92–108CrossRef
Zurück zum Zitat Buscombe D (2020) SediNet: a configurable deep learning model for mixed qualitative and quantitative optical granulometry. Earth Surf Process Landforms 45:638–651CrossRef Buscombe D (2020) SediNet: a configurable deep learning model for mixed qualitative and quantitative optical granulometry. Earth Surf Process Landforms 45:638–651CrossRef
Zurück zum Zitat Butler JB, Lane SN, Chandler JH (2001) Automated extraction of grain-size data from gravel surfaces using digital image processing. J Hydraul Res 39:519–529CrossRef Butler JB, Lane SN, Chandler JH (2001) Automated extraction of grain-size data from gravel surfaces using digital image processing. J Hydraul Res 39:519–529CrossRef
Zurück zum Zitat Chardon V, Schmitt L, Piégay H, Lague D (2020) Use of terrestrial photosieving and airborne topographic LiDAR to assess bed grain size in large rivers: a study on the Rhine River. Earth Surf Process Landforms 45:2314–2330CrossRef Chardon V, Schmitt L, Piégay H, Lague D (2020) Use of terrestrial photosieving and airborne topographic LiDAR to assess bed grain size in large rivers: a study on the Rhine River. Earth Surf Process Landforms 45:2314–2330CrossRef
Zurück zum Zitat Entwistle NS, Heritage GL, Johnson K, Hetherington D (2007) Repeat terrestrial laser scanner survey of pebble cluster creation and formation in response to flow change. Proceedings of the Annual Conference. Remote Sensing and Photogrammetry Society, Nottingham Entwistle NS, Heritage GL, Johnson K, Hetherington D (2007) Repeat terrestrial laser scanner survey of pebble cluster creation and formation in response to flow change. Proceedings of the Annual Conference. Remote Sensing and Photogrammetry Society, Nottingham
Zurück zum Zitat Fehr R (1987) Einfache Bestimmung der Korngrössenverteilung von Geschiebematerial mit Hilfe der Linienzahlanalyse [Simple detection of grain size distribution of sediment material using line-count analysis]. Schweizer Ingenieur Und Architekt 105:1104–1109 ((in German)) Fehr R (1987) Einfache Bestimmung der Korngrössenverteilung von Geschiebematerial mit Hilfe der Linienzahlanalyse [Simple detection of grain size distribution of sediment material using line-count analysis]. Schweizer Ingenieur Und Architekt 105:1104–1109 ((in German))
Zurück zum Zitat Graham DJ, Reid I, Rice SP (2005a) Automated sizing of coarse-grained sediments: Image-processing procedures. Math Geol 37:1–28CrossRef Graham DJ, Reid I, Rice SP (2005a) Automated sizing of coarse-grained sediments: Image-processing procedures. Math Geol 37:1–28CrossRef
Zurück zum Zitat Heritage GL, Milan DJ (2009) Terrestrial Laser Scanning of grain roughness in a gravel-bed river. Geomorphology 113:4–11CrossRef Heritage GL, Milan DJ (2009) Terrestrial Laser Scanning of grain roughness in a gravel-bed river. Geomorphology 113:4–11CrossRef
Zurück zum Zitat Hodge R, Brasington J, Richards K (2009a) Analysing laser-scanned digital terrain models of gravel bed surfaces: linking morphology to sediment transport processes and hydraulics. Sedimentology 56:2024–2043CrossRef Hodge R, Brasington J, Richards K (2009a) Analysing laser-scanned digital terrain models of gravel bed surfaces: linking morphology to sediment transport processes and hydraulics. Sedimentology 56:2024–2043CrossRef
Zurück zum Zitat Hodge R, Brasington J, Richards K (2009b) In situ characterization of grain-scale fluvial morphology using Terrestrial Laser Scanning. Earth Surf Process Landforms 34:954–968 Hodge R, Brasington J, Richards K (2009b) In situ characterization of grain-scale fluvial morphology using Terrestrial Laser Scanning. Earth Surf Process Landforms 34:954–968
Zurück zum Zitat Huang G-H, Wang C-K (2012) Multiscale geostatistical estimation of gravel-bed roughness from terrestrial and airborne laser scanning. IEEE Geosci Remote Sens Lett 9:1084–1088CrossRef Huang G-H, Wang C-K (2012) Multiscale geostatistical estimation of gravel-bed roughness from terrestrial and airborne laser scanning. IEEE Geosci Remote Sens Lett 9:1084–1088CrossRef
Zurück zum Zitat Ibbeken H, Schleyer R (1986) Photo-sieving: a method for grain-size analysis of coarse-grained, unconsolidated bedding surfaces. Earth Surf Proc Land 11:59–77CrossRef Ibbeken H, Schleyer R (1986) Photo-sieving: a method for grain-size analysis of coarse-grained, unconsolidated bedding surfaces. Earth Surf Proc Land 11:59–77CrossRef
Zurück zum Zitat Lang N, Irniger A, Rozniak A, Hunziker R, Wegner JD, Schindler K (2021) GRAINet: Mapping grain size distributions in river beds from UAV images with convolutional neural networks. Hydrol Earth Syst Sci 25:2567–2597CrossRef Lang N, Irniger A, Rozniak A, Hunziker R, Wegner JD, Schindler K (2021) GRAINet: Mapping grain size distributions in river beds from UAV images with convolutional neural networks. Hydrol Earth Syst Sci 25:2567–2597CrossRef
Zurück zum Zitat McEwan IK, Sheen TM, Cunningham GJ, Allen AR (2000) Estimating the size composition of sediment surfaces through image analysis. Proc. Instn Civ. Engrs Water & Mar Engng 142:189–195 McEwan IK, Sheen TM, Cunningham GJ, Allen AR (2000) Estimating the size composition of sediment surfaces through image analysis. Proc. Instn Civ. Engrs Water & Mar Engng 142:189–195
Zurück zum Zitat Pearson E, Smith MW, Klaar MJ, Brown LE (2017) Can high resolution 3D topographic surveys provide reliable grain size estimates in gravel bed rivers? Geomorphology 293:143–155CrossRef Pearson E, Smith MW, Klaar MJ, Brown LE (2017) Can high resolution 3D topographic surveys provide reliable grain size estimates in gravel bed rivers? Geomorphology 293:143–155CrossRef
Zurück zum Zitat Rubin DM (2004) A simple autocorrelation algorithm for determining grain size from digital images of sediment. J Sediment Res 74:160–165CrossRef Rubin DM (2004) A simple autocorrelation algorithm for determining grain size from digital images of sediment. J Sediment Res 74:160–165CrossRef
Zurück zum Zitat Rychkov I, Brasington J, Vericat D (2012) Computational and methodological aspects of terrestrial surface analysis based on point clouds. Comput Geosci 42:64–70CrossRef Rychkov I, Brasington J, Vericat D (2012) Computational and methodological aspects of terrestrial surface analysis based on point clouds. Comput Geosci 42:64–70CrossRef
Zurück zum Zitat Sime LC, Ferguson RI (2003) Information on grain sizes in gravel-bed rivers by automated image analysis. J Sediment Res 73:630–636CrossRef Sime LC, Ferguson RI (2003) Information on grain sizes in gravel-bed rivers by automated image analysis. J Sediment Res 73:630–636CrossRef
Zurück zum Zitat Strom KB, Kuhns RD, Lucas HJ (2010) Comparison of automated image-based grain sizing to standard pebble-count methods. J Hydraul Eng 136:461–473CrossRef Strom KB, Kuhns RD, Lucas HJ (2010) Comparison of automated image-based grain sizing to standard pebble-count methods. J Hydraul Eng 136:461–473CrossRef
Zurück zum Zitat Wang C-K, Wu F-C, Huang G-H, Lee C-Y (2011) Mesoscale terrestrial laser scanning of fluvial gravel surfaces. IEEE Geosci Remote Sens Lett 8:1075–1079CrossRef Wang C-K, Wu F-C, Huang G-H, Lee C-Y (2011) Mesoscale terrestrial laser scanning of fluvial gravel surfaces. IEEE Geosci Remote Sens Lett 8:1075–1079CrossRef
Zurück zum Zitat Warrick JA, Rubin DM, Ruggiero P, Harney JN, Draut AE, Buscombe D (2009) Cobble cam: grain-size measurements of sand to boulder from digital photographs and autocorrelation analyses. Earth Surf Process Landforms 34:1811–1821CrossRef Warrick JA, Rubin DM, Ruggiero P, Harney JN, Draut AE, Buscombe D (2009) Cobble cam: grain-size measurements of sand to boulder from digital photographs and autocorrelation analyses. Earth Surf Process Landforms 34:1811–1821CrossRef
Zurück zum Zitat Wolman MG (1954) A method of sampling coarse river-bed material. EOS Trans Am Geophys Union 35:951–956CrossRef Wolman MG (1954) A method of sampling coarse river-bed material. EOS Trans Am Geophys Union 35:951–956CrossRef
Zurück zum Zitat Woodget AS, Austrums R (2017) Subaerial gravel size measurement using topographic data derived from a UAV-SfM approach. Earth Surf Process Landforms 42:1434–1443CrossRef Woodget AS, Austrums R (2017) Subaerial gravel size measurement using topographic data derived from a UAV-SfM approach. Earth Surf Process Landforms 42:1434–1443CrossRef
Zurück zum Zitat Wu F-C, Wang C-K, Huang G-H (2018) Delineation of gravel-bed clusters via factorial kriging. Geomorphology 308:161–174CrossRef Wu F-C, Wang C-K, Huang G-H (2018) Delineation of gravel-bed clusters via factorial kriging. Geomorphology 308:161–174CrossRef
Metadaten
Titel
FKgrain: A topography-based software tool for grain segmentation and sizing using factorial kriging
verfasst von
Fu-Chun Wu
Chi-Kuei Wang
Hong Ping Lo
Publikationsdatum
09.07.2021
Verlag
Springer Berlin Heidelberg
Erschienen in
Earth Science Informatics / Ausgabe 4/2021
Print ISSN: 1865-0473
Elektronische ISSN: 1865-0481
DOI
https://doi.org/10.1007/s12145-021-00660-z

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