Claudia Meisina

Dr. Claudia Meisina

Dipartimento di Scienze della Terra e dell’Ambiente (DSTA), University of Pavia, Via Ferrata 1, 27100 Pavia, Italy
orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2015 in Engineering Geology
Verified
Journal Article
Closed access
MBM. Bordoni
M. Bordoni
Claudia MeisinaClaudia Meisina
Claudia Meisina
RVR. Valentino
R. Valentino
NLN. Lu
N. Lu
MBM. Bittelli
M. Bittelli
SCS. Chersich
S. Chersich

6 March 2014 in International Journal of Remote Sensing
Verified
Journal Article
Closed access
Davide NottiDavide Notti
Davide Notti
Gerardo HerreraGerardo Herrera
Gerardo Herrera
SBSilvia Bianchini
Silvia Bianchini
Claudia MeisinaClaudia Meisina
Claudia Meisina
JGJuan Carlos García-Davalillo
Juan Carlos García-Davalillo
FZFrancesco Zucca
Francesco Zucca
In this work, we present a methodology for improving persistent scatterer interferometry (PSI) data analysis for landslide studies. This methodology is a revision of previously described procedures with several improved and newly proposed aspects. To both evaluate and validate the results from this methodology, we used various persistent scatterer (PS) datasets from different satellites (ERS – ENVISAT, Radarsat, TerraSAR-X, and ALOS PALSAR) that were processed using three PSI techniques (stable point network – SPN, permanent scatterer interferometry – PSInSAR™, and SqueeSAR™) to map and monitor landslides in various mountainous environments in Spain and Italy. This methodology consists of a preprocessing model that predicts the presence of a PS over a certain area and a post-processing method used to determine the stability threshold, project the line of sight (LOS) velocity along the slope, estimate the E–W and vertical components of the velocity, and identify anomalous areas.

1 January 2018 in CATENA
Verified
Journal Article
Closed access
MPMaria Giuseppina Persichillo
Maria Giuseppina Persichillo
MBMassimiliano Bordoni
Massimiliano Bordoni
MCMarco Cavalli
Marco Cavalli
SCStefano Crema
Stefano Crema
Claudia MeisinaClaudia Meisina
Claudia Meisina

1 January 2017 in Science of The Total Environment
Verified
Journal Article
Closed access
MPMaria Giuseppina Persichillo
Maria Giuseppina Persichillo
MBMassimiliano Bordoni
Massimiliano Bordoni
Claudia MeisinaClaudia Meisina
Claudia Meisina

24 November 2008 in Sensors
Verified
Journal Article
Open access
PDF file
Claudia MeisinaClaudia Meisina
Claudia Meisina
FZFrancesco Zucca
Francesco Zucca
Davide NottiDavide Notti
Davide Notti
ACAlessio Colombo
Alessio Colombo
ACAnselmo Cucchi
Anselmo Cucchi
MBMarco Bianchi
Marco Bianchi
Results of a PSInSAR™ project carried out by the Regional Agency for Environmental Protection (ARPA) in Piemonte Region (Northern Italy) are presented and discussed. A methodology is proposed for the interpretation of the PSInSARTM data at the regional scale, easy to use by the public administrations and by civil protection authorities. Potential and limitations of the PSInSARTM technique for ground movement detection on a regional scale and monitoring are then estimated in relationship with different geological processes and various geological environments.

5 March 2013 in Natural Hazards and Earth System Sciences
Verified
Journal Article
Open access
PDF file
DZD. Zizioli
D. Zizioli
Claudia MeisinaClaudia Meisina
Claudia Meisina
Roberto ValentinoRoberto Valentino
Roberto Valentino
LML. Montrasio
L. Montrasio
On the 27 and 28 April 2009, the area of Oltrepo Pavese in northern Italy was affected by a very intense rainfall event that caused a great number of shallow landslides. These instabilities occurred on slopes covered by vineyards or recently formed woodlands and caused damage to many roads and one human loss. Based on aerial photographs taken immediately after the event and field surveys, more than 1600 landslides were detected. After acquiring topographical data, geotechnical properties of the soils and land use, susceptibility analysis on a territorial scale was carried out. In particular, different physically based models were applied to two contiguous sites with the same geological context but different typologies and sizes of shallow landslides. This paper presents the comparison between the ex-post results obtained from the different approaches. On the basis of the observed landslide localizations, the accuracy of the different models was evaluated, and the significant results are highlighted.