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SLOW-MOVING LANDSLIDE MONITORING WITH MULTI-TEMPORAL TERRASAR-X DATA BY MEANS OF DINSAR TECHNIQUES IN CROTONE PROVINCE (SOUTHERN ITALY) Confuorto P. 1, Plank S. 2 , Di Martire D. 1 , Ramondini M. 1 , Thuro K. 3 , Calcaterra D. 1 1) University of Napoli Federico II, 2) DLR, 3)Technische Universität München

SLOW-MOVING LANDSLIDE MONITORING WITH MULTI ...seom.esa.int/fringe2015/files/presentation53.pdfPapanice landslide – Main features 140m 23 February 2012 Geological survey - Landslide

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Page 1: SLOW-MOVING LANDSLIDE MONITORING WITH MULTI ...seom.esa.int/fringe2015/files/presentation53.pdfPapanice landslide – Main features 140m 23 February 2012 Geological survey - Landslide

SLOW-MOVING LANDSLIDE MONITORING WITH MULTI-TEMPORAL TERRASAR-X DATA

BY MEANS OF DINSAR TECHNIQUES IN CROTONE PROVINCE (SOUTHERN ITALY)

Confuorto P.1, Plank S.2, Di Martire D.1, Ramondini M.1, Thuro K.3, Calcaterra D.1

1) University of Napoli Federico II, 2) DLR, 3)Technische Universität München

Page 2: SLOW-MOVING LANDSLIDE MONITORING WITH MULTI ...seom.esa.int/fringe2015/files/presentation53.pdfPapanice landslide – Main features 140m 23 February 2012 Geological survey - Landslide

Outline

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Motivation

Agnone Montaguto

Papanice Maierato Maps of the landslide events with ‘victims’ between 1964 – 2013

(CNR-IRPI (2015))

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Study Area

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Papanice Landslide

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Papanice – Geological setting

1) Holocene deposits; 2) Plio-Pleistocene deposits; 3) Tortonian-Pliocene deposits, 4)Mesozoic Liguride Complex; 5) Crystalline bedrock; 6) Fault; 7) Transpressive shear zone; 8) Study Areas. Modified from Corbi (2009)

Papanice

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Geological setting

Recent alluvial deposits (Holocene)

Sant’Anna Synthem (Upper Pleistocene)

Cutro marly clay (Upper Pliocene – Lower Pleistocene)

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Papanice urban growth

Courtesy of the ARPACAL

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Methodology

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Landslide inventory map (2001)

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Papanice landslide – Main features

140m

23 February 2012

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Geological survey

- Landslide updated as active - Retrogressive trend

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Available Dataset

Descending Dataset: 67 Images Track 108

Orbit 4784

Ascending Dataset: 66 Images Track 146

Orbit 9498

TerraSAR-X Science Proposals Geo 1589 - Geo 2641

2008-2010

2012 Slope failure

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DInSAR Techniques

SUBSOFT processor

Coherent Pixel Technique (CPT -

Mora et al., 2003, Blanco et al.,

2008, Iglesias et al., 2015)

Temporal Sublook Spectral

Coherence candidates selection

SARscape® Software

Persistent Scatterers

Interferometry (PSI – Ferretti et al., 2001)

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R-Index (Notti et al., 2004, 2010)

Descending Dataset Ascending Dataset

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1

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TSSC Application

Amplitude Map

Pixel selected with a TSSC threshold of 0.7

Temporal Sublook Spectral Coherence Map

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TSSC Application

Points referable to the displacement: 109 Average velocity of the displacement: -27.7 mm/yr Maximum value of velocity: -36 mm/yr Minimum value of velocity: -14.8 mm/yr

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2

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PSI Application

- Application of a temporal baseline threshold , splitting the stack in two periods

- Application of a spatial baseline threshold

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PSI Application

Amplitude Map Coherence Map

Final PSs with a product coherence threshold of 0.6

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PSI Application

PS 1st period Image selected: 29 Point selected: 1393 Point referable to the displacement: 7 Average velocity of the displacement: -25.4 mm/yr Maximum value of velocity: -32.1mm/yr

PS 2nd period Image selected: 27 Point selected: 1543 Point referable to the displacement: 1 Value of velocity: -32.1mm/yr

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Comparison • General agreement among the two MTI methods exploited (displacement

rates and detection of the landslide)

-80

-70

-60

-50

-40

-30

-20

-10

0

Disp

lace

men

t Rat

e (m

m)

Date

PSI

TSSC

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Comparison

• Higher number of points, referred to the landslide, recognized by the TSSC

• Shift of 150 m westward for the SARscape software

• Confirmation of the results also with preliminary processing through CPT (Coherence pixel selection) and SBAS

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0

20

40

60

80

100

120

140

160

180

200

20-Feb-12 21-Feb-12 22-Feb-12 23-Feb-12

mm

Days

Rainfall Analysis

Cumulated Rainfall: 184.4 mm

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Time Series Analysis

0

50

100

150

200

250

300

350

400

450

-80

-70

-60

-50

-40

-30

-20

-10

0

Disp

lace

men

t (m

m/y

r)

Rainfalls (mm

)

Point 8959 (TSSC)

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Conclusions

• Reliability of DInSAR techniques, especially when coupled with geological and geomorphological surveys

• Ability of MTI techniques to recognize precursor

stages of future slope failures

• Ability of MTI techniques to analyze displacements at a local scale

Page 29: SLOW-MOVING LANDSLIDE MONITORING WITH MULTI ...seom.esa.int/fringe2015/files/presentation53.pdfPapanice landslide – Main features 140m 23 February 2012 Geological survey - Landslide

Outlook & Ideas

• Processing of the 2013-2014 stacks for post-failure analysis and validation with traditional instruments

• Improving the analysis with CPT (Coherence pixel selection) and SBAS

• Application of MTI techniques for regular monitoring shortly after each acquisition

Page 30: SLOW-MOVING LANDSLIDE MONITORING WITH MULTI ...seom.esa.int/fringe2015/files/presentation53.pdfPapanice landslide – Main features 140m 23 February 2012 Geological survey - Landslide

Thanks for your attention!

Any Questions?