English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
  Local TagsRelease HistoryDetailsSummary

Released
Conference Paper

Adjoint-state traveltime tomography in Central Java enhanced by a machine-learning-assisted catalog

Authors

Bai,  Yiming
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Ramdhan,  Mohamad
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Yang,  Shun
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Li,  Tianjue
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Chen,  Jing
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Nagaso,  Masaru
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Tong,  Ping
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in GFZpublic
Supplementary Material (public)
There is no public supplementary material available
Citation

Bai, Y., Ramdhan, M., Yang, S., Li, T., Chen, J., Nagaso, M., Tong, P. (2023): Adjoint-state traveltime tomography in Central Java enhanced by a machine-learning-assisted catalog, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-3791


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5020754
Abstract
As one of the most populous regions, Central Java in Indonesia is prone to high seismic and volcanic hazards, primarily due to the progressive northward subduction of the Australian plate beneath the Sunda plate. Detailed velocity structure of the crust and uppermost mantle beneath Central Java is critical for an improved understanding of the subduction processes and the associated seismicity and volcanism. Despite several independent isotropic velocity models proposed for the region, crustal-scale anisotropic structure, which reflects past and ongoing deformation, has rarely been investigated. Our goal is to image the crustal-scale P-wave azimuthally anisotropic structure beneath Central Java. Seismic data used were recorded by > 200 seismic stations from multiple projects. To make full use of the open access data, machine learning phase picking and subsequent event association and location were applied to build a local earthquake catalog. The machine-learning-based workflow detects > 1000 events, roughly triple the amount from previous manual picking. Notably, the preliminary catalog includes a large number of earthquakes that were located in the offshore areas but were recorded by land stations to the north, resulting in huge back azimuthal gaps and potential bias in earthquake relocation. The ongoing study attempts to involve depth phases, such as sPn and sPg, for more accurate earthquake locations and thus more reliable tomographic images. With the expanded and refined seismicity catalog, a ray-free adjoint-state traveltime tomography package called TomoATT will be used for the 3-D velocity heterogeneity and azimuthal anisotropy beneath Central Java.