Toolboxes

To share a research tool, you can email maridwebsite@gmail.com with a short description of the toobox and the location of the source codes. Please write “toolbox” in the subject line of your email.

Links to metadata files and associated documents:

BAMBI: Bedform Analysis Method for Bathymetric Information

BAMBI was developed to automatically measure the geometric characteristics of dunes in big rivers using MBES data acquired for several large rivers. The BAMBI can also be used to measure dunes from single echosounder lines, but additional steps must be taken so that the lines are in a matrix format. BAMBI works at the resolution of the data while decreasing data measurement time to a few hours of code run time.

Related publication

Cisneros, J., Best, J., van Dijk, T. et al. Dunes in the world’s big rivers are characterized by low-angle lee-side slopes and a complex shape (2020). Nature Geoscience 13, 156–162. https://doi.org/10.1038/s41561-019-0511-7

Code and user guide

https://github.com/juliamorphology/bambi_0.1.0

Bedform-analysis

An automated method has been developed by which the geometry of superimposed rhythmic bedforms can be analysed. The method combines two-dimensional (2D) Fourier analysis, wavelet transform, zero-crossing analysis and a variety of filters. Instead of applying conventional manual procedures, the wavelength of interest can be automatically determined by a series of 2D Fourier analyses, which is a critical first step for automated analysis of dune geometries. Based on such efficient data preprocessing, the method can accurately determine dune orientation, separate target bedform profiles, and identify crests and troughs. With the input of bathymetry, the dominant regional dune orientation can be determined together with the geometric parameters of individual dunes (wavelength, height, leeside angles) and their spatial distribution.

Related publication

Wang, L., Yu, Q., Zhang, Y., Flemming, B. W., Wang, Y., and Gao, S. (2020) An automated procedure to calculate the morphological parameters of superimposed rhythmic bedforms. Earth Surf. Process. Landforms, 45: 3496– 3509. https://doi.org/10.1002/esp.4983

Code and user guide

https://github.com/twilight5284/Bedform-analysis

Bedform separation loess

Matlab code to separate bathymetric data representing multiscale bedforms based on LOESS.

Related publication

Zomer, J. Y., Naqshband, S., Vermeulen, B., & Hoitink, A. J. F. (2021). Rapidly migrating secondary bedforms can persist on the lee of slowly migrating primary river dunes. Journal of Geophysical Research: Earth Surface, 126, e2020JF005918. https://doi.org/10.1029/2020JF005918

Code and user guide

https://github.com/j-zomer/bedformseparation-loess

Bedforms-ATM

Bedforms-ATM is intended to standardize the scale-based discrimination of bed forms. Bedforms-ATM V1.2 is presented as a free MATLAB software and comprises the following applications: [1] Bed forms wavelet analysis, [2] Power Hovmöller analysis, [3] Bed forms multiscale discrimination, and [4] Three-dimensionality analysis.

Related publications

Núñez-González, F., Hesse, D., Ettmer, B., Gutierrez, R.R., Link, O. (2021). Development and validation of a novel metric for describing the three-dimensionality of bed forms. Geomorphology 390, 107856. https://doi.org/10.1016/j.geomorph.2021.107856.

Gutierrez, R. R., Mallma, J. A., Núñez-González, F., Link, O., & Abad, J. D. (2018). Bedforms-ATM, an open source software to analyze the scale-based hierarchies and dimensionality of natural bed forms. SoftwareX, 7, 184-189. https://doi.org/10.1016/j.softx.2018.06.001

Gutierrez, R. R., Abad, J. D., Parsons, D. R., and Best, J. L. (2013). Discrimination of bed form scales using robust spline filters and wavelet transforms: Methods and application to synthetic signals and bed forms of the Ro Parana, Argentina. Journal of Geophysical Research: Earth Surface, 118(3):1400-1418.

Code and user guide

https://github.com/rgutierrezl/BedformsATM

pybedforms

‘pybedforms’ is a Python version of ‘Bedforms 4.0’, a Matlab program written by David Rubin and Carissa Carter. The bedform topographies are created in exactly the same way as they were in Bedforms 4.0; however, the 3D visualization is different. We use Mayavi to build the block diagrams; these plotting functions were simplified from the ‘blockdiagram’ Python package. The ‘Notebook_with_examples’ jupyter notebook illustrates how to build bedform models using (1) the default parameters and (2) a set of parameters predefined by Rubin & Carter.

Related publication

Rubin and Carter, 2013. Bedforms 4.0: MATLAB Code for Simulating Bedforms and Cross-Bedding, https://pubs.usgs.gov/of/2005/1272/

Code and user guide

https://github.com/AndrewAnnex/pybedfroms

Weser Bedform Analysis

These codes were developed to analyse the bedforms from the Weser Estaury. We had a large spatial and temporal seties of bathymetric data (2 m resolution) in the Weser Estaury that we wanted to characterise. The codes were developed specifically to detect cerstlines and troughlines on the data, and also calculate properties of so-called BEP bedforms. To know nore about the processing, please check the publication.

Related publication

Lefebvre, A., Herrling, G., Becker, M., Zorndt, A., Krämer, K., Winter, C. (2021). Morphology of estuarine bedforms, Weser Estuary, Germany. Earth Surface Processes and Landforms https://doi.org/10.1002/esp.5243

Code and user guide

https://github.com/DrAliceLefebvre/Weser_Bedform_Analysis_Codes