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

Yıl 2019, Cilt: 8 Sayı: 1, 1 - 9, 30.06.2019
https://doi.org/10.33714/masteb.486678

Öz

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.

Destekleyen Kurum

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

Proje Numarası

2016SOA002

Teşekkür

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

Kaynakça

  • 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.
Yıl 2019, Cilt: 8 Sayı: 1, 1 - 9, 30.06.2019
https://doi.org/10.33714/masteb.486678

Öz

Proje Numarası

2016SOA002

Kaynakça

  • 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.
Toplam 15 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Polina Lemenkova 0000-0002-5759-1089

Proje Numarası 2016SOA002
Yayımlanma Tarihi 30 Haziran 2019
Gönderilme Tarihi 22 Kasım 2018
Kabul Tarihi 8 Mart 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 8 Sayı: 1

Kaynak Göster

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. Haziran 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, sy. 1 (Haziran 2019): 1-9. https://doi.org/10.33714/masteb.486678.
EndNote Lemenkova P (01 Haziran 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., c. 8, sy. 1, ss. 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 (Haziran 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, c. 8, sy. 1, 2019, ss. 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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