Learning Change from Synthetic Aperture Radar Images: Performance Evaluation of 
a Support Vector Machine to Detect Earthquake and Tsunami-Induced Changes

Wieland, Marc; Liu, Wen; Yamazaki, Fumio; 2.6 Seismic Hazard and Stress Field, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum

doi:10.3390/rs8100792

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Learning Change from Synthetic Aperture Radar Images: Performance Evaluation of a Support Vector Machine to Detect Earthquake and Tsunami-Induced Changes

Authors

/persons/resource/mwieland

Wieland, Marc
7.1 Centre for Early Warning Systems, 7.0 Geoservices, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Liu, Wen
External Organizations;

Yamazaki, Fumio
External Organizations;

External Ressource

No external resources are shared

Fulltext (public)

1975919.pdf
(Publisher version), 7MB

Supplementary Material (public)

There is no public supplementary material available

Citation

Wieland, M., Liu, W., Yamazaki, F. (2016): Learning Change from Synthetic Aperture Radar Images: Performance Evaluation of a Support Vector Machine to Detect Earthquake and Tsunami-Induced Changes. - Remote Sensing, 8, 10, 792.
https://doi.org/10.3390/rs8100792

https://gfzpublic.gfz-potsdam.de/pubman/item/item_1975919

Abstract

There is no abstract available