Environmental variables and multivariate seabed classification maps via k means clustering of Potter Cove, Antarctica, link to input and result files in GeoTIFF format

• Main Authors: Jerosch, Kerstin, Scharf, Frauke Katharina, Pehlke, Hendrik, Weber, Lukas, Abele, Doris
• Format: Dataset
• Language: English
• Published: PANGAEA 2016
• Subjects: Carlini/Jubany Station; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems; Antarctica; Jubany_Dallmann; MULT; Multiple investigations; PotterCove; Potter Cove; King George Island; Antarctic Peninsula; Antarctic; Antarc*
• Online Access: https://doi.pangaea.de/10.1594/PANGAEA.856971; https://doi.org/10.1594/PANGAEA.856971

This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.