Application of Machine Learning to Classification of Volcanic Deformation in Routinely Generated InSAR Data

Recent improvements in the frequency, type, and availability of satellite images mean it is now feasible to routinely study volcanoes in remote and inaccessible regions, including those with no ground‐based monitoring. In particular, Interferometric Synthetic Aperture Radar data can detect surface d...

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Veröffentlicht in:	Journal of geophysical research. Solid earth 2018-08, Vol.123 (8), p.6592-6606
Hauptverfasser:	Anantrasirichai, N., Biggs, J., Albino, F., Hill, P., Bull, D.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial intelligence Atmospheric correction Corrections Data Data processing Deformation Duration Feasibility studies Imagery Inspection Interferometric synthetic aperture radar Interferometry Learning algorithms Machine learning Model updating Radar Radar data SAR (radar) Satellite imagery Satellites Spaceborne remote sensing Synthetic aperture radar Synthetic aperture radar interferometry Training Transfer learning Volcanic activity Volcanoes
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