학술논문
The use of massive deformation datasets for the analysis of spatial and temporal evolution of Mauna Loa volcano (Hawai’i)
Document Type
Conference
Author
Source
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium Geoscience and Remote Sensing Symposium, IGARSS 2019 - 2019 IEEE International. :10075-10078 Jul, 2019
Subject
Language
ISSN
2153-7003
Abstract
We exploit large DInSAR and GPS datasets to create a 4D image of the magma transfer processes at Mauna Loa volcano from 2005 to 2015. The datasets consists of 23 continuous GPS time series and 307 SAR images acquired from ascending and descending orbits by ENVISAT and COSMO-SkyMed satellites. The joint use of SAR data acquired from different orbits together with deformation data from GPS networks and geological information can significantly improve the constraints on the geometry and location of the sources responsible for the observed deformation. The analysis of these datasets has been realized using an innovative method that allows to image a complex configuration of different type of sources. The results suggest that the deformation pattern observed from 2005 to 2015 has been controlled by three deformation sources: the ascent of magma along a conduit, the opening of a dike and the slip along the basal decollement.