The
study area is located in western Pacific Ocean, Mariana Trench. The aim of the
data analysis is to analyze the potential influence of how various geological
and tectonic factors may affect the geomorphological shape of the Mariana
Trench. Statistical analysis of the data
set in marine geology and oceanography requires an adequate strategy on big
data processing. In this context, current research proposes a combination of
the Python-based methodology that couples GIS geospatial data analysis. The
Quantum GIS part of the methodology produces an optimized representative
sampling dataset consisting of 25 cross-section profiles having in total 12,590
bathymetric observation points. The sampling of the geospatial dataset are
located across the Mariana Trench. The second part of the methodology consists
of statistical data processing by means of high-level programming language
Python. Current research uses libraries Pandas, NumPy and SciPy. The data
processing also involves the subsampling of two auxiliary masked data frames
from the initial large data set that only consists of the target variables:
sediment thickness, slope angle degrees and bathymetric observation points
across four tectonic plates: Pacific, Philippine, Mariana, and Caroline.
Finally, the data were analyzed by several approaches: 1) Kernel Density
Estimation (KDE) for analysis of the probability of data distribution; 2)
stacked area chart for visualization of the data range across various segments
of the trench; 3) spacial series of radar charts; 4) stacked bar plots showing
the data distribution by tectonic plates; 5) stacked bar charts for correlation
of sediment thickness by profiles, versus distance from the igneous volcanic
areas; 6) circular pie plots visualizing data distribution by 25 profiles; 7)
scatterplot matrices for correlation analysis between marine geologic
variables. The results presented a distinct correlation between the geologic,
tectonic and oceanographic variables. Six Python codes are provided in full for
repeatability of this research.
Mariana Trench Pacific Ocean Python SciPy NumPy Pandas Programming language Statistics Data analysis
Birincil Dil | İngilizce |
---|---|
Konular | Hidrobiyoloji, Deniz Mühendisliği |
Bölüm | Research Articles |
Yazarlar | |
Yayımlanma Tarihi | 1 Nisan 2019 |
Gönderilme Tarihi | 24 Mart 2019 |
Yayımlandığı Sayı | Yıl 2019Cilt: 2 Sayı: 2 |
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