Research Article
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An Empirical Study of R Applications for Data Analysis in Marine Geology

Year 2019, Volume: 8 Issue: 1, 1 - 9, 30.06.2019
https://doi.org/10.33714/masteb.486678

Abstract

The study focuses on the application of R
programming language towards marine geological research with a case study of
Mariana Trench. Due to its logical and straightforward syntax, multi–functional
standard libraries, R is especially attractive to the geologists for the
scientific computing. Using R libraries, the unevenness of various factors
affecting Mariana Trench geomorphic structure has been studied. These include
sediment thickness, slope steepness, angle aspect, depth at the basement and
magmatism of the nearby areas. Methods includes using following R libraries:
{ggplot2} for regression analysis, Kernel density curves, compositional charts;
{ggalt} for Dumbbell charts for data comparison by tectonic plates, ranking dot
plots for correlation analysis; {vcd} for mosaic plots, silhouette plots for
compositional similarities among the bathymetric profiles, association plots;
{car} for ANOVA. Bathymetric GIS data processing was done in QGIS and LaTeX.
The innovativeness of the work consists in the multi–disciplinary approach
combining GIS analysis and statistical methods of R which contributes towards
studies of ocean trenches, aimed at geospatial analysis of big data.

Supporting Institution

China Scholarship Council (CSC), State Oceanic Administration (SOA), Marine Scholarship of China

Project Number

2016SOA002

Thanks

The study has been funded by the China Scholarship Council (CSC), State Oceanic Administration (SOA), Marine Scholarship of China [Grant # 2016SOA002, 2016].

References

  • Butuzova, G. Y. (2003). Hydrothermal–Sedimentary Ore Formation in the World Ocean. Geos, Moscow, Russia. 136p.
  • Dubinin, E. P. & Ushakov, S. A. (2001). Oceanic Rift Genesis. Geos, Moscow, Russia. 293p.
  • Gardner, J. V., Armstrong, A. A., Calder, B. R. & Beaudoin, J. (2014). So, How Deep Is The Mariana Trench? Marine Geodesy, 37(1): 1–13.
  • Garfunkel, Z., Anderson, C. A. & Schubert, G. (1986). Mantle Circulation and the Lateral Migration of Subducted Slabs. Journal of Geophysical Research, 91: 7205–7223.
  • Gurevich, E. G. (1998). Metalliferous Sediments in the World Ocean. Nauchnyy Mir, Moscow, Russia. 340p.
  • Horleston, A. C. & Helffrich, G. R. (2012). Constraining Sediment Subduction: A Converted Phase Study of the Aleutians and Marianas. Earth and Planetary Science Letters, 359–360: 141–151.
  • Husson, L. (2012). Trench Migration and Upper Plate Strain over a Convecting Mantle. Physics of the Earth and Planetary Interiors, 212–213: 32–43.
  • Ishibashi, J., Tsunogai, U., Toki, T., Ebina, N., Gamo, T., Sano, Y., Masuda, H. & Chiba, H. (2015). Chemical Composition of Hydrothermal Fluids in the Central and Southern Mariana Trough Backarc Basin. Deep–Sea Research Part II: Topical Studies in Oceanography, 121: 126–136.
  • Lin, J. W. B. (2008). Qtcm 0.1.2: A Python Implementation of the Neelin–Zeng Quasi–Equilibrium Tropical Circulation Model. Geoscientific Model Development, 1: 315–344.
  • Marta–Almeida, M., Ruiz–Villarreal, M., Otero, P., Cobas, P., Peliz, A., Nolasco, R., Cirano, M. & Pereira, J. (2011). OOF3: A Python Engine for Automating Regional and Coastal Ocean Forecasts. Environmental Modelling & Software, 26: 680–682.
  • Oliphant, T. E. (2007). Python for Scientific Computing. Computing in Science & Engineering, 9: 10–20.
  • R Core Team (2018). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. https://www.R–project.org
  • Roberts, J. J., Best, B. D., Dunn, D. C., Treml, E. A. & Halpin, P. N. (2010). Marine Geo–Spatial Ecology Tools: An Integrated Framework for Ecological Geoprocessing with ArcGIS, Python, R, MATLAB, and C++. Environmental Modelling & Software, 25: 1197–1207.
  • Uyeda, S. & Kanamori, H. (1979). Back–Arc Opening and the Mode of Subduction. Journal of Geophysical Research, 84: 2017–2037.
  • Warner, J. C., Perlin, N. & Skyllingstad, E. D. (2008). Using the Model Coupling Toolkit to Couple Earth System Models. Environmental Modelling & Software, 23: 1240–1249.
Year 2019, Volume: 8 Issue: 1, 1 - 9, 30.06.2019
https://doi.org/10.33714/masteb.486678

Abstract

Project Number

2016SOA002

References

  • Butuzova, G. Y. (2003). Hydrothermal–Sedimentary Ore Formation in the World Ocean. Geos, Moscow, Russia. 136p.
  • Dubinin, E. P. & Ushakov, S. A. (2001). Oceanic Rift Genesis. Geos, Moscow, Russia. 293p.
  • Gardner, J. V., Armstrong, A. A., Calder, B. R. & Beaudoin, J. (2014). So, How Deep Is The Mariana Trench? Marine Geodesy, 37(1): 1–13.
  • Garfunkel, Z., Anderson, C. A. & Schubert, G. (1986). Mantle Circulation and the Lateral Migration of Subducted Slabs. Journal of Geophysical Research, 91: 7205–7223.
  • Gurevich, E. G. (1998). Metalliferous Sediments in the World Ocean. Nauchnyy Mir, Moscow, Russia. 340p.
  • Horleston, A. C. & Helffrich, G. R. (2012). Constraining Sediment Subduction: A Converted Phase Study of the Aleutians and Marianas. Earth and Planetary Science Letters, 359–360: 141–151.
  • Husson, L. (2012). Trench Migration and Upper Plate Strain over a Convecting Mantle. Physics of the Earth and Planetary Interiors, 212–213: 32–43.
  • Ishibashi, J., Tsunogai, U., Toki, T., Ebina, N., Gamo, T., Sano, Y., Masuda, H. & Chiba, H. (2015). Chemical Composition of Hydrothermal Fluids in the Central and Southern Mariana Trough Backarc Basin. Deep–Sea Research Part II: Topical Studies in Oceanography, 121: 126–136.
  • Lin, J. W. B. (2008). Qtcm 0.1.2: A Python Implementation of the Neelin–Zeng Quasi–Equilibrium Tropical Circulation Model. Geoscientific Model Development, 1: 315–344.
  • Marta–Almeida, M., Ruiz–Villarreal, M., Otero, P., Cobas, P., Peliz, A., Nolasco, R., Cirano, M. & Pereira, J. (2011). OOF3: A Python Engine for Automating Regional and Coastal Ocean Forecasts. Environmental Modelling & Software, 26: 680–682.
  • Oliphant, T. E. (2007). Python for Scientific Computing. Computing in Science & Engineering, 9: 10–20.
  • R Core Team (2018). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. https://www.R–project.org
  • Roberts, J. J., Best, B. D., Dunn, D. C., Treml, E. A. & Halpin, P. N. (2010). Marine Geo–Spatial Ecology Tools: An Integrated Framework for Ecological Geoprocessing with ArcGIS, Python, R, MATLAB, and C++. Environmental Modelling & Software, 25: 1197–1207.
  • Uyeda, S. & Kanamori, H. (1979). Back–Arc Opening and the Mode of Subduction. Journal of Geophysical Research, 84: 2017–2037.
  • Warner, J. C., Perlin, N. & Skyllingstad, E. D. (2008). Using the Model Coupling Toolkit to Couple Earth System Models. Environmental Modelling & Software, 23: 1240–1249.
There are 15 citations in total.

Details

Primary Language English
Journal Section Research Article
Authors

Polina Lemenkova 0000-0002-5759-1089

Project Number 2016SOA002
Publication Date June 30, 2019
Submission Date November 22, 2018
Acceptance Date March 8, 2019
Published in Issue Year 2019 Volume: 8 Issue: 1

Cite

APA Lemenkova, P. (2019). An Empirical Study of R Applications for Data Analysis in Marine Geology. Marine Science and Technology Bulletin, 8(1), 1-9. https://doi.org/10.33714/masteb.486678
AMA Lemenkova P. An Empirical Study of R Applications for Data Analysis in Marine Geology. Mar. Sci. Tech. Bull. June 2019;8(1):1-9. doi:10.33714/masteb.486678
Chicago Lemenkova, Polina. “An Empirical Study of R Applications for Data Analysis in Marine Geology”. Marine Science and Technology Bulletin 8, no. 1 (June 2019): 1-9. https://doi.org/10.33714/masteb.486678.
EndNote Lemenkova P (June 1, 2019) An Empirical Study of R Applications for Data Analysis in Marine Geology. Marine Science and Technology Bulletin 8 1 1–9.
IEEE P. Lemenkova, “An Empirical Study of R Applications for Data Analysis in Marine Geology”, Mar. Sci. Tech. Bull., vol. 8, no. 1, pp. 1–9, 2019, doi: 10.33714/masteb.486678.
ISNAD Lemenkova, Polina. “An Empirical Study of R Applications for Data Analysis in Marine Geology”. Marine Science and Technology Bulletin 8/1 (June 2019), 1-9. https://doi.org/10.33714/masteb.486678.
JAMA Lemenkova P. An Empirical Study of R Applications for Data Analysis in Marine Geology. Mar. Sci. Tech. Bull. 2019;8:1–9.
MLA Lemenkova, Polina. “An Empirical Study of R Applications for Data Analysis in Marine Geology”. Marine Science and Technology Bulletin, vol. 8, no. 1, 2019, pp. 1-9, doi:10.33714/masteb.486678.
Vancouver Lemenkova P. An Empirical Study of R Applications for Data Analysis in Marine Geology. Mar. Sci. Tech. Bull. 2019;8(1):1-9.

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