Topographic surface modelling using raster grid datasets by GMT: example of the Kuril–Kamchatka Trench, Pacific Ocean
The study area is focused on the Kuril–Kamchatka Trench, North Pacific Ocean. This region is geologically complex, notable for the lithosphere activity, tectonic plates subduction and active volcanism. The submarine geomorphology is complicated through terraces, slopes, seamounts and erosional proce...
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ftdatacite:10.6084/m9.figshare.10259663.v1 2023-05-15T16:59:05+02:00 Topographic surface modelling using raster grid datasets by GMT: example of the Kuril–Kamchatka Trench, Pacific Ocean Lemenkova, Polina 2019 https://dx.doi.org/10.6084/m9.figshare.10259663.v1 https://figshare.com/articles/Topographic_surface_modelling_using_raster_grid_datasets_by_GMT_example_of_the_Kuril_Kamchatka_Trench_Pacific_Ocean/10259663/1 unknown figshare https://dx.doi.org/10.6084/m9.figshare.10259663 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY 90902 Geodesy FOS Environmental engineering 90901 Cartography Geography Physical Geography 40699 Physical Geography and Environmental Geoscience not elsewhere classified FOS Earth and related environmental sciences Geology 49999 Earth Sciences not elsewhere classified Environmental Science Text article-journal Journal contribution ScholarlyArticle 2019 ftdatacite https://doi.org/10.6084/m9.figshare.10259663.v1 https://doi.org/10.6084/m9.figshare.10259663 2021-11-05T12:55:41Z The study area is focused on the Kuril–Kamchatka Trench, North Pacific Ocean. This region is geologically complex, notable for the lithosphere activity, tectonic plates subduction and active volcanism. The submarine geomorphology is complicated through terraces, slopes, seamounts and erosional processes. Understanding geomorphic features of such a region requires precise modelling and effective visualization of the high-resolution data sets. Therefore, current research presents a Generic Mapping Tools (GMT) based algorithm proposing a solution for effective data processing and precise mapping: iterative module-based scripting for the automated digitizing and modelling. Methodology consists of the following steps: topographic mapping of the raster grids, marine gravity and geoid; semi-automatic digitizing of the orthogonal cross-section profiles; modelling geomorphic trends of the gradient slopes; computing raster surfaces from the xyz data sets by modules nearneighbor and XYZ2grd. Several types of the cartographic projections were used: oblique Mercator, Mercator cylindrical, conic equal-area Albers, conic equidistant. The cross-section geomorphic profiles in a perpendicular direction across the two selected segments of the trench were automatically digitized. Developed algorithm of the semi-automated digitizing of the profiles enabled to visualize gradients of the slope steepness of the trench. The data were then modelled to show gradient variations in its two segments. The results of the comparative geomorphic analysis of northern and southern transects revealed variations in different parts of the trench. Presented research provided more quantitative insights into the structure and settings of the submarine landforms of the hadal trench that still remains a question for the marine geology. The research demonstrated the effectiveness of the GMT: a variety of modules, approaches and tools that can be used to produce high-quality mapping and graphics. The GMT listings are provided for repeatability. Text Kamchatka DataCite Metadata Store (German National Library of Science and Technology) Pacific |
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DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
topic |
90902 Geodesy FOS Environmental engineering 90901 Cartography Geography Physical Geography 40699 Physical Geography and Environmental Geoscience not elsewhere classified FOS Earth and related environmental sciences Geology 49999 Earth Sciences not elsewhere classified Environmental Science |
spellingShingle |
90902 Geodesy FOS Environmental engineering 90901 Cartography Geography Physical Geography 40699 Physical Geography and Environmental Geoscience not elsewhere classified FOS Earth and related environmental sciences Geology 49999 Earth Sciences not elsewhere classified Environmental Science Lemenkova, Polina Topographic surface modelling using raster grid datasets by GMT: example of the Kuril–Kamchatka Trench, Pacific Ocean |
topic_facet |
90902 Geodesy FOS Environmental engineering 90901 Cartography Geography Physical Geography 40699 Physical Geography and Environmental Geoscience not elsewhere classified FOS Earth and related environmental sciences Geology 49999 Earth Sciences not elsewhere classified Environmental Science |
description |
The study area is focused on the Kuril–Kamchatka Trench, North Pacific Ocean. This region is geologically complex, notable for the lithosphere activity, tectonic plates subduction and active volcanism. The submarine geomorphology is complicated through terraces, slopes, seamounts and erosional processes. Understanding geomorphic features of such a region requires precise modelling and effective visualization of the high-resolution data sets. Therefore, current research presents a Generic Mapping Tools (GMT) based algorithm proposing a solution for effective data processing and precise mapping: iterative module-based scripting for the automated digitizing and modelling. Methodology consists of the following steps: topographic mapping of the raster grids, marine gravity and geoid; semi-automatic digitizing of the orthogonal cross-section profiles; modelling geomorphic trends of the gradient slopes; computing raster surfaces from the xyz data sets by modules nearneighbor and XYZ2grd. Several types of the cartographic projections were used: oblique Mercator, Mercator cylindrical, conic equal-area Albers, conic equidistant. The cross-section geomorphic profiles in a perpendicular direction across the two selected segments of the trench were automatically digitized. Developed algorithm of the semi-automated digitizing of the profiles enabled to visualize gradients of the slope steepness of the trench. The data were then modelled to show gradient variations in its two segments. The results of the comparative geomorphic analysis of northern and southern transects revealed variations in different parts of the trench. Presented research provided more quantitative insights into the structure and settings of the submarine landforms of the hadal trench that still remains a question for the marine geology. The research demonstrated the effectiveness of the GMT: a variety of modules, approaches and tools that can be used to produce high-quality mapping and graphics. The GMT listings are provided for repeatability. |
format |
Text |
author |
Lemenkova, Polina |
author_facet |
Lemenkova, Polina |
author_sort |
Lemenkova, Polina |
title |
Topographic surface modelling using raster grid datasets by GMT: example of the Kuril–Kamchatka Trench, Pacific Ocean |
title_short |
Topographic surface modelling using raster grid datasets by GMT: example of the Kuril–Kamchatka Trench, Pacific Ocean |
title_full |
Topographic surface modelling using raster grid datasets by GMT: example of the Kuril–Kamchatka Trench, Pacific Ocean |
title_fullStr |
Topographic surface modelling using raster grid datasets by GMT: example of the Kuril–Kamchatka Trench, Pacific Ocean |
title_full_unstemmed |
Topographic surface modelling using raster grid datasets by GMT: example of the Kuril–Kamchatka Trench, Pacific Ocean |
title_sort |
topographic surface modelling using raster grid datasets by gmt: example of the kuril–kamchatka trench, pacific ocean |
publisher |
figshare |
publishDate |
2019 |
url |
https://dx.doi.org/10.6084/m9.figshare.10259663.v1 https://figshare.com/articles/Topographic_surface_modelling_using_raster_grid_datasets_by_GMT_example_of_the_Kuril_Kamchatka_Trench_Pacific_Ocean/10259663/1 |
geographic |
Pacific |
geographic_facet |
Pacific |
genre |
Kamchatka |
genre_facet |
Kamchatka |
op_relation |
https://dx.doi.org/10.6084/m9.figshare.10259663 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.6084/m9.figshare.10259663.v1 https://doi.org/10.6084/m9.figshare.10259663 |
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1766051275597676544 |