Details
Originalsprache | Englisch |
---|---|
Aufsatznummer | e2023JF007607 |
Seitenumfang | 19 |
Fachzeitschrift | Journal of Geophysical Research: Earth Surface |
Jahrgang | 129 |
Ausgabenummer | 3 |
Publikationsstatus | Veröffentlicht - 25 März 2024 |
Abstract
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.
ASJC Scopus Sachgebiete
- Erdkunde und Planetologie (insg.)
- Geophysik
- Erdkunde und Planetologie (insg.)
- Erdoberflächenprozesse
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in: Journal of Geophysical Research: Earth Surface, Jahrgang 129, Nr. 3, e2023JF007607, 25.03.2024.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Automated Bedform Identification
T2 - A Meta-Analysis of Current Methods and the Heterogeneity of Their Outputs
AU - Scheiber, Leon
AU - Zomer, Judith
AU - Wang, Li
AU - Cisneros, Julia
AU - Gutierrez, Ronald R.
AU - Lefebvre, Alice
N1 - Funding Information: Open Access funding enabled and organized by Projekt DEAL.
PY - 2024/3/25
Y1 - 2024/3/25
N2 - 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.
AB - 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.
KW - bedform analysis
KW - dune identification
KW - geomorphology
KW - meta-analysis
KW - underwater dunes
UR - http://www.scopus.com/inward/record.url?scp=85188516976&partnerID=8YFLogxK
U2 - 10.1029/2023JF007607
DO - 10.1029/2023JF007607
M3 - Article
AN - SCOPUS:85188516976
VL - 129
JO - Journal of Geophysical Research: Earth Surface
JF - Journal of Geophysical Research: Earth Surface
SN - 2169-9003
IS - 3
M1 - e2023JF007607
ER -