SWE_of_Bathymetry

버전 1.0 (23.7 MB) 작성자: Gabriella Alodia

A Matlab-based geomorphometric algorithm to obtain the numerical description of magmatic and detachment crust in a slow-spreading ridges.

https://github.com/gabriella-alodia/SWE_of_Bathymetry

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업데이트 날짜: 2022/3/17

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SWE_of_Bathymetry.m

SWE_of_Bathymetry.m is a Matlab-based geomorphometric algorithm to obtain the numerical description of both magmatic and tectonic crust in a slow-spreading ridge through a series of calculation based on the distribution of the azimuth and plunge observed in the seafloor morphology.

Input: A gridded shipborne multibeam bathymetry (depths in metres) in *.xyz format (here: 'Input_Bathymetry_15s.xyz')

Output

Terrain eccentricity (here: 'Output_eccentricity.xyz')
Weight matrix: 1-sin(slope) (here: 'Output_weight.xyz')
SWE: Slope-weighted eccentricity (here: 'Output_SWE.xyz')
Masked SWE (here: 'Output_SWE_masked.xyz')

Each output is exported in *.xyz format. The resulting *.xyz data can be converted into *.grd using the xyz2grd function in GMT (http://gmt.soest.hawaii.edu/doc/5.3.2/xyz2grd.html)

The shipborne multibeam bathymetry data sample is downloaded from the GMRT MapTool (https://www.gmrt.org/GMRTMapTool/) with the extent xmin/xmax/ymin/ymax of -46/-44/12.5/13.15

Full paper:

Alodia, G., Green, C. M., & McCaig, A. M. (2022). SWE_of_Bathymetry.m: A geomorphometric tool to automate discrimination between detachment and magmatic seafloor at slow-spreading ridges from shipboard multibeam bathymetry, Computers & Geosciences, Volume 166, 105177. [https://doi.org/10.1016/j.cageo.2022.105177]

Preprint & EGU Presentation:

Alodia, G., Green, C., McCaig, A., & Paton, D. (2020). A novel approach for oceanic spreading terrain classification at the Mid-Atlantic Ridge using Eigenvalues of high-resolution bathymetry. In EGU General Assembly Conference Abstracts (p. 337). [https://presentations.copernicus.org/EGU2020/EGU2020-337_presentation.pdf]

Alodia, G., Green, C., McCaig, A., & Paton, D. (2020). Slope-Weighted Eccentricity: Automatic Terrain Classification of Atlantic Ocean Crust. ESSOAr: Earth and Space Science Open Archive. [https://doi.org/10.1002/essoar.10502634.1]