Mauna Loa is a basaltic shield volcano, located in in the Big Island of the Hawaii archipelago (USA), which rises over 4 km above sea and the first well-documented historical eruption occurred in 1843; most recent eruption occurred in 1984. After this eruption, the volcano entered in a phase of quiescence, interrupted by three main episodes of unrest. The latest episode began in April 2014 and continues to date, with a variable rate of inflation behavior. We investigate the ground deformation process affecting the Mauna Loa volcano from 2003 to 2014 by exploiting the advanced Interferometric Synthetic Aperture Radar (InSAR) technique referred to as Small BAseline Subset (SBAS) algorithm. The time series of Line-Of-Sight displacements derived from the multi-temporal and multi-platform SAR data were obtained using ENVISAT dataset, acquired by ascending and descending orbits over the 2003-2010 time period and COSMO-SkyMed images from both orbits in 2012-2014 time span. Moreover, we analyzed also SENTINEL 1A interferograms pairs obtained from both orbits acquired in 2014 - 2015 time interval. The final step consists in the inversion of the retrieved DInSAR results, in order to model both deep geological structures and magmatic sources to better understand the dynamics that drive on the volcano process. To characterize the geometry and the evolution of the volcano deformation source, we apply both forward and inverse modeling techniques. The former technique allowed defining roughly the geometrical parameters of the source, while the latter allowed retrieving its temporal evolution. The obtained results have direct implication in the interpretation of the last unrest episode, providing a useful tool to aid the forecast of possible future eruptions at Mauna Loa.

The Unrest phenomenon at Mauna Loa volcano detected via multi-temporal and multi-platform InSAR measurements

S Pepe;M Bonano;R Castaldo;F Casu;C De Luca;V De Novellis;M Manunta;E Sansosti;G Solaro;P Tizzani
2015

Abstract

Mauna Loa is a basaltic shield volcano, located in in the Big Island of the Hawaii archipelago (USA), which rises over 4 km above sea and the first well-documented historical eruption occurred in 1843; most recent eruption occurred in 1984. After this eruption, the volcano entered in a phase of quiescence, interrupted by three main episodes of unrest. The latest episode began in April 2014 and continues to date, with a variable rate of inflation behavior. We investigate the ground deformation process affecting the Mauna Loa volcano from 2003 to 2014 by exploiting the advanced Interferometric Synthetic Aperture Radar (InSAR) technique referred to as Small BAseline Subset (SBAS) algorithm. The time series of Line-Of-Sight displacements derived from the multi-temporal and multi-platform SAR data were obtained using ENVISAT dataset, acquired by ascending and descending orbits over the 2003-2010 time period and COSMO-SkyMed images from both orbits in 2012-2014 time span. Moreover, we analyzed also SENTINEL 1A interferograms pairs obtained from both orbits acquired in 2014 - 2015 time interval. The final step consists in the inversion of the retrieved DInSAR results, in order to model both deep geological structures and magmatic sources to better understand the dynamics that drive on the volcano process. To characterize the geometry and the evolution of the volcano deformation source, we apply both forward and inverse modeling techniques. The former technique allowed defining roughly the geometrical parameters of the source, while the latter allowed retrieving its temporal evolution. The obtained results have direct implication in the interpretation of the last unrest episode, providing a useful tool to aid the forecast of possible future eruptions at Mauna Loa.
2015
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA
Mauna Loa volcano InSar Envisat COSMO-SkyMed SENTINEL 1A SBAS Unrest phenomenon
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/341955
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact