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Hierarchical Cluster Analysis by R language for Pattern Recognition in the Bathymetric Data Frame: a Case Study of the Mariana Trench, Pacific Ocean
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Abstract
The geographic focus of the current study Mariana trench, the deepest point of the Earth located in the west Pacific Ocean. Mariana trench has unique structure and features formed in the complex process of the trench development. There is a range of the environmental factors affecting trench structure and functioning: bathymetry, geography, geology and tectonics. Current research aimed to study interconnections among these determinants. Technically, the research was performed by R programming language, statistical analysis, and QuantumGIS. Methodology includes a range of the statistical methods for data processing, the most important of which is cluster analysis. The results revealed unevenness of the factors affecting trench bathymetric structure, caused by the environmental conditions.
DOI
https://doi.org/10.31223/osf.io/ab6xw
Subjects
Applied Statistics, Earth Sciences, Environmental Education, Environmental Monitoring, Environmental Sciences, Environmental Studies, Geographic Information Sciences, Geography, Geology, Geomorphology, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Other Earth Sciences, Other Oceanography and Atmospheric Sciences and Meteorology, Other Statistics and Probability, Physical and Environmental Geography, Physical Sciences and Mathematics, Social and Behavioral Sciences, Spatial Science, Statistics and Probability, Tectonics and Structure
Keywords
Geology, geostatistics, R, Cluster analysis, Mariana Trench, Pacific Ocean, Programming, Statistical Analysis
Dates
Published: 2019-01-25 09:22
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