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Item type:Publication, Towards adopting open and data‐driven science practices in bed form dynamics research, and some steps to this end(Wiley, 2020-01-15)Abstract In recent years, open and data‐driven science has fostered very important scientific breakthroughs. This study describes the challenges and opportunities for the scientific community devoted to bed form dynamics research in adopting such scientific paradigms through, for example, engineered data sharing, formal recognition of scientists who collect the data, and collaborative development of free accessible software. It highlights that once these actions are completed, the potential application of deep learning techniques could substantially improve bed form models and the scientific understanding of bed form dynamics. Likewise, it discusses the potential of Bedforms‐ATM, a free available software, to standardize some bed form data analysis techniques. We propose that the technical challenges be tackled by following scholarly accepted/proposed standards (e.g. FAIR Guiding Principles, Geoscience Papers of the Future), using the body of knowledge being built on the matter by some institutions (e.g. Federation of Earth Science Information Partners), and through technical discussions at scientific meetings such as MARID. © 2020 John Wiley & Sons, Ltd. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Spoilt for choice -- when to use which bedform identification tool for what purpose?(Wiley, 2021-12-28)Subaqueous dunes are fascinating morphological features that exist in diverse environments such as the deep sea, continental shelves and inland streams or rivers. Due to their rhythmic and oftentimes very frequent occurrence along the predominant flow direction, the analysis of these bedforms is usually assigned to bedform identification tools. Such algorithms automatically determine crest and trough locations and calculate dune dimensions accordingly. Over the last years, the number of these tools has notably increased with specialized methodologies for every environment and bedform scale. Although many of them are readily available to interested researchers, there may be uncertainty as to which method should be applied in view of a specific research question. As authors of some of the most recent bedform identification tools, we have started to systematically compare our approaches by analyzing an agreed set of diverse bathymetric data. The bed features assessed in this context range from river dunes formed under unidirectional flow over tidally constrained compound dunes to bed elevation profiles gained from flume experiments. The resulting dune characteristics, which each scientist obtained by applying his/her particular algorithm, are thereupon contrasted in a qualitative and quantitative manner uncovering the similarities and differences between individual methodologies. Our preliminary results suggest a strong influence of the original focus of each algorithm and therefore corroborate the need for systematic comparison. In the next step, the gained insights will be used to find and explain the optimum fields of application and, in the end, provide user-oriented guidelines that may support the bedform community in deciding which identification tool should be used for what purpose. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Bridging worlds in bedform research with an open access, universal toolbox: the Bedform Analysis Toolbox(Wiley, 2021-12-21)Bedforms (ripples, dunes, sandwaves) are ubiquitous features in many sandy subaqueous settings. They have been observed in a wide variety of flows, including rivers, the surf zone, estuaries, tidal inlets, shallow seas, and deep waters. Bedforms exert a major influence on a range of processes, from small-scale turbulence and sediment transport to large-scale coastal geomorphology. Therefore, knowledge on the dimensions, morphological characteristics and dynamics of large bedforms is relevant for a range of fundamental and applied research. Several methods have been developed over the years to characterise bedform dimensions from bathymetric data. Each method has been created for a specific (e.g. discriminate bedform scale, calculate bedform size and/or shape, detect crestlines) and environment (unidirectional, constrained tidal or open marine) and with a certain accuracy (precise time-consuming detection or coarse rapid detection). Although some of these methods are freely available, it may be difficult for scientists to use them due to the specificity of their design. A unique toolbox which combines the available methods into one easy-to-use software would help the bedform community advance knowledge on bedform research by facilitating the analysis of bedform characteristics. This should also include recommendations of which method should be used for which purpose. The present project aims at creating a Bedform Analysis Toolbox which combines several methods already available. The toolbox will be made open source and freely available. Feedback on the need of the community or required design and specificity would help us create a toolbox which is useful to many scientists. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Automated bedform identification—A meta-analysis of current methods and the heterogeneity of their outputs(John Wiley and Sons Inc, 2024-03-01)Ongoing efforts to characterize underwater dunes have led to a considerable number of freely available tools that identify these bedforms in a (semi-)automated way. However, these tools differ with regard to their research focus and appear to produce results that are far from unequivocal. We scrutinize this assumption by comparing the results of five recently published dune identification tools in a comprehensive meta-analysis. Specifically, we analyze dune populations identified in three bathymetries under diverse flow conditions and compare the resulting dune characteristics in a quantitative manner. Besides the impact of underlying definitions, it is shown that the main heterogeneity arises from the consideration of a secondary dune scale, which has a significant influence on statistical distributions. Based on the quantitative results, we discuss the individual strengths and limitations of each algorithm, with the aim of outlining adequate fields of application. However, the concerted bedform analysis and subsequent combination of results have another benefit: the creation of a benchmarking data set which is inherently less biased by individual focus and therefore a valuable instrument for future validations. Nevertheless, it is apparent that the available tools are still very specific and that end-users would profit by their merging into a universal and modular toolbox. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Automated Bedform Identification: A Meta-Analysis of Current Methods and the Heterogeneity of Their Outputs(2023-12-26)Ongoing efforts to characterize underwater dunes have led to a considerable number of freely available tools that identify these bedforms in a (semi-)automated way. However, these tools differ with regard to their research focus and appear to produce results that are far from unequivocal. We scrutinize this assumption by comparing the results of five recently published dune identification tools in a comprehensive meta-analysis. Specifically, we analyse dune populations identified in three bathymetries under diverse flow conditions and compare the resulting dune characteristics in a quantitative manner. Besides the impact of underlying definitions, it is shown that the main heterogeneity arises from the consideration of a secondary dune scale, which has a significant influence on statistical distributions. Based on the quantitative results, we discuss the individual strengths and limitations of each algorithm, with the aim of outlining adequate fields of application. Yet, the concerted bedform analysis and subsequent combination of results have another benefit: the creation of a benchmarking data set which is inherently less biased by individual focus and therefore a valuable instrument for future validations. Nevertheless, it is apparent that the available tools are still very specific and that end-users would profit by their merging into a universal and modular toolbox.