Long term deformation time series: 10 years of Earth observation through ENVISAT multi-mode ASAR sensor (Contributo in atti di convegno)

Type
Label
  • Long term deformation time series: 10 years of Earth observation through ENVISAT multi-mode ASAR sensor (Contributo in atti di convegno) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Alternative label
  • P. Berardino, M. Bonano, F. Calò, F. Casu, S. Elefante, M. Manunta, M. Manzo, L. Paglia, A. Pepe, S. Pepe, E. Sansosti, G. Solaro, P. Tizzani, G. Zeni, R. Lanari (2012)
    Long term deformation time series: 10 years of Earth observation through ENVISAT multi-mode ASAR sensor
    in IGARSS 2012, Munich, Germany, 23-27 July 2012
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • P. Berardino, M. Bonano, F. Calò, F. Casu, S. Elefante, M. Manunta, M. Manzo, L. Paglia, A. Pepe, S. Pepe, E. Sansosti, G. Solaro, P. Tizzani, G. Zeni, R. Lanari (literal)
Pagina inizio
  • 1840 (literal)
Pagina fine
  • 1843 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • 2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Natl Res Council Italy, Ist Rilevamento Elettromagnet Ambiente, Via Diocleziano 328, I-80124 Naples, Italy (literal)
Titolo
  • Long term deformation time series: 10 years of Earth observation through ENVISAT multi-mode ASAR sensor (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-1-4673-1159-5 (literal)
Abstract
  • We present some of the main advances on long term deformation time series analysis achieved thanks to the 10 years of operation of ENVISAT ASAR sensor. This is done by considering a number of selected case studies, which are mostly based on the use of the Small BAseline Subset (SBAS) technique. In particular, we show how we benefit from the ENVISAT data availability to extend the ERS time series, thus allowing us to obtain almost 20 years of deformation history. Moreover, we demonstrate how the multi-mode capability of ENVISAT permits improving the temporal sampling in SBAS time series. Finally, we introduce a novel technique, tested on ENVISAT data, to generate displacement time series in areas affected by large deformation phenomena. (literal)
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