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Article 7 - Volume 31/1 - 2021

Paper title:

Georeferenced gridded data handled by GMT: cartographic solutions for geophysical mapping

Author(s):

1Université Libre de Bruxelles, École Polytechnique de Bruxelles (Brussels Faculty of Engineering), Laboratory of Image Synthesis and Analysis (LISA)
2 Schmidt Institute of Physics of the Earth, Russian Academy of Sciences. Department of Natural Disasters, Anthropogenic Hazards and Seismicity of the Earth. Laboratory of Regional Geophysics and Natural Disasters

Pages:

78 - 93

Publishing date:

01 November 2021

Abstract:

The functionality of Generic Mapping Tools (GMT) to process and visualize geospatial information is crucial to the development of the advanced cartographic method. This paper presents modelling and spatial analysis of the marine geological data using GMT shell scripting. GMT demonstrated effective cartographic solutions for visualization of the georeferenced data. The particular feature of GMT consists in its scripting modular approach that enables to use machine learning to explore reliable georeferenced data. Here, the study applies a sequential shell scripting to devise GMT modules for depicting marine geological data on the Mariana Trench. The data cover bathymetry, geophysics, tectonics and geology. The first method makes use of the 'nearneighbor' GMT module for grid contour modelling using Nearest Neighbor algorithm. This form of modelling classifies the geospatial data based on a similarity. The second method presents surface modelling from the initial XYZ-ASCII dataset by a combination of the 'blockmean' and 'surface' modules. The third method includes the use of the modules 'grdimage', 'psbasemap' and 'grdcontour' for plotting. Compared to GIS methods in which data are processed in a menu, GMT presents the console-based approach which automates cartographic data processing. The results present seven new maps and explanations of scripts.A combination of visual approaches applied using a color fill and various textures to represent data, which is effective in allowing readers to assess geophysical setting. The study demonstrated the effectiveness of GMT in geodata visualization.

Keywords:

cartography, machine learning, GMT, scripting, data analysis, data visualization.