We present a new method for the automatic classification of Persistent Scatters Interferometry (PSI) time series based on a conditional sequence of statistical tests. Time series are classified into distinctive predefined target trends, such as uncorrelated, linear, quadratic, bilinear and discontinuous, that describe different styles of ground deformation. Our automatic analysis overcomes limits related to the visual classification of PSI time series, which cannot be carried out systematically for large datasets. The method has been tested with reference to landslides using PSI datasets covering the northern Apennines of Italy. The clear distinction between the relative frequency of uncorrelated, linear and non-linear time series with respect to mean velocity distribution suggests that different target trends are related to different physical processes that are likely to control slope movements. The spatial distribution of classified time series is also consistent with respect the known distribution of flat areas, slopes and landslides in the tests area. Classified time series enhances the radar interpretation of slope movements at the site scale, pointing out significant advantages in comparison with the conventional analysis based solely on the mean velocity. The test application also warns against potentially misleading classification outputs in case of datasets affected by systematic errors. Although the method was developed and tested to investigate landslides, it should be also useful for the analysis of other ground deformation processes such as subsidence, swelling/shrinkage of soils, or uplifts due to deep injections in reservoirs.

Automated classification of Persistent Scatterers Interferometry time series / M., Berti; Corsini, Alessandro; S., Franceschini; Iannacone, JEAN PASCAL. - In: NATURAL HAZARDS AND EARTH SYSTEM SCIENCES. - ISSN 1561-8633. - STAMPA. - 13:8(2013), pp. 1945-1958. [10.5194/nhess-13-1945-2013]

Automated classification of Persistent Scatterers Interferometry time series

CORSINI, Alessandro;IANNACONE, JEAN PASCAL
2013

Abstract

We present a new method for the automatic classification of Persistent Scatters Interferometry (PSI) time series based on a conditional sequence of statistical tests. Time series are classified into distinctive predefined target trends, such as uncorrelated, linear, quadratic, bilinear and discontinuous, that describe different styles of ground deformation. Our automatic analysis overcomes limits related to the visual classification of PSI time series, which cannot be carried out systematically for large datasets. The method has been tested with reference to landslides using PSI datasets covering the northern Apennines of Italy. The clear distinction between the relative frequency of uncorrelated, linear and non-linear time series with respect to mean velocity distribution suggests that different target trends are related to different physical processes that are likely to control slope movements. The spatial distribution of classified time series is also consistent with respect the known distribution of flat areas, slopes and landslides in the tests area. Classified time series enhances the radar interpretation of slope movements at the site scale, pointing out significant advantages in comparison with the conventional analysis based solely on the mean velocity. The test application also warns against potentially misleading classification outputs in case of datasets affected by systematic errors. Although the method was developed and tested to investigate landslides, it should be also useful for the analysis of other ground deformation processes such as subsidence, swelling/shrinkage of soils, or uplifts due to deep injections in reservoirs.
2013
13
8
1945
1958
Automated classification of Persistent Scatterers Interferometry time series / M., Berti; Corsini, Alessandro; S., Franceschini; Iannacone, JEAN PASCAL. - In: NATURAL HAZARDS AND EARTH SYSTEM SCIENCES. - ISSN 1561-8633. - STAMPA. - 13:8(2013), pp. 1945-1958. [10.5194/nhess-13-1945-2013]
M., Berti; Corsini, Alessandro; S., Franceschini; Iannacone, JEAN PASCAL
File in questo prodotto:
File Dimensione Formato  
2013_Berti et al_nhess-13-1945-2013.pdf

Open access

Tipologia: Versione pubblicata dall'editore
Dimensione 5.46 MB
Formato Adobe PDF
5.46 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/982605
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 91
  • ???jsp.display-item.citation.isi??? 76
social impact