Geospatial Analysis by Python and R: Geomorphology of the Philippine Trench, Pacific Ocean - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Electronic Letters on Science and Engineering Année : 2019

Geospatial Analysis by Python and R: Geomorphology of the Philippine Trench, Pacific Ocean

Polina Lemenkova

Résumé

The study area is focused on the Philippine Trench, a hadal trench located in the axe of the collision of the Philippine Sea Plate and Sunda Plate, west Pacific Ocean. The research is aimed at the analysis of the trench geomorphology by a correlation between changes in slope steepness and environmental variables. The methodology consists in modeling data by statistical libraries of Python and R programming languages. The results revealed that variations in the slope steepness correlate with the sediment thickness across the Philippine Trench. Variations in the landform are caused by a combination of various factors that include geology, tectonic slab dynamics, and increasing depths in bathymetry. Algorithms of the advanced machine learning and graph-based analysis applied for the marine geological data set demonstrated in this research enabled to gain insights into the seafloor geomorphology that can only be accessible by remote sensing methods and modeling. Application of the statistical methods of the data analysis by Python and R packages has broad applicability to similar research aimed at modeling landform variations in the submarine geomorphology of the hadal trenches.
Fichier principal
Vignette du fichier
Geospatial Analysis by Python and R Geomorphology of the Philippine Trench, Pacific Ocean.pdf (1.99 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-02425688 , version 1 (31-12-2019)

Licence

Paternité - Pas d'utilisation commerciale

Identifiants

Citer

Polina Lemenkova. Geospatial Analysis by Python and R: Geomorphology of the Philippine Trench, Pacific Ocean. Electronic Letters on Science and Engineering, 2019, 15 (3), pp.81-94. ⟨10.6084/m9.figshare.11449362⟩. ⟨hal-02425688⟩

Collections

TDS-MACS
75 Consultations
250 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More