10.1080@01431161.2011.630331.pdf

This article was downloaded by: [Northeastern University]
On: 05 January 2015, At: 19:55
Publisher: Taylor & Francis
Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered
office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
International Journal of Remote
Sensing
Publication details, including instructions for authors and
subscription information:
http://www.tandfonline.com/loi/tres20
Assessing the activity of a large
landslide in southern Italy by ground-
monitoring and SAR interferometric
techniques
Fabiana Calò
a
, Domenico Calcaterra
a
, Antonio Iodice
b
, Mario
Parise
c
& Massimo Ramondini
a
a
Department of Hydraulic, Geotechnical and Environmental
Engineering , University of Naples Federico II , Naples , Italy
b
Department of Biomedical, Electronics and Telecommunications
Engineering , University of Naples Federico II , Naples , Italy
c
Institute of Research for the Hydro-geological Protection,
National Research Council , Bari , Italy
Published online: 24 Nov 2011.
To cite this article: Fabiana Calò , Domenico Calcaterra , Antonio Iodice , Mario Parise & Massimo
Ramondini (2012) Assessing the activity of a large landslide in southern Italy by ground-monitoring
and SAR interferometric techniques, International Journal of Remote Sensing, 33:11, 3512-3530,
DOI: 10.1080/01431161.2011.630331
To link to this article: http://dx.doi.org/10.1080/01431161.2011.630331
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the
“Content”) contained in the publications on our platform. However, Taylor & Francis,
our agents, and our licensors make no representations or warranties whatsoever as to
the accuracy, completeness, or suitability for any purpose of the Content. Any opinions
and views expressed in this publication are the opinions and views of the authors,
and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content
should not be relied upon and should be independently verified with primary sources
of information. Taylor and Francis shall not be liable for any losses, actions, claims,
proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or
howsoever caused arising directly or indirectly in connection with, in relation to or arising
out of the use of the Content.

This article may be used for research, teaching, and private study purposes. Any
substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,
systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &
Conditions of access and use can be found at http://www.tandfonline.com/page/terms-
and-conditions
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

International Journal of Remote Sensing
Vol. 33, No. 11, 10 June 2012, 3512–3530
Assessing the activity of a large landslide in southern Italy by
ground-monitoring and SAR interferometric techniques
FABIANA CALÒ*†, DOMENICO CALCATERRA†, ANTONIO IODICE‡,
MARIO PARISE§ and MASSIMO RAMONDINI†
†Department of Hydraulic, Geotechnical and Environmental Engineering, University of
Naples Federico II, Naples, Italy
‡Department of Biomedical, Electronics and Telecommunications Engineering, University of
Naples Federico II, Naples, Italy
§Institute of Research for the Hydro-geological Protection, National Research Council,
Bari, Italy
(Received 14 July 2010; in final form 8 July 2011)
Landslides are recognized as one of the most damaging natural hazards in Italy.
Campania region represents a complex geological setting, where mass movements
of different types are widespread, and urban expansion can be increasingly seen
by the presence of buildings and infrastructure in landslide-prone areas. In such
a context, monitoring of unstable slopes represents a key activity in the pro-
cess of landslide risk prevention and mitigation, in order to correctly establish a
cause–effect correlation and to predict the possible reactivation phases that may
result in high costs for the human society. This article focuses on the application of
different methods of landslide analysis and monitoring, including those developed
more recently and based on data acquired by satellites and processed by synthetic
aperture radar (SAR) interferometric techniques. The study area is a small town,
Calitri, known worldwide for the large landslide reactivated by the 23 November
1980 earthquake that destroyed a large sector of the historical centre. The site
has been investigated by two ground-monitoring campaigns, the analysis of which
allowed identification of the evolution of landslide activity over time. Furthermore,
differential SAR interferometry (DInSAR), based upon two different approaches,
allowed us to produce point-wise and wide area deformation maps after processing
data sets of Earth Resource Satellite 1/2 (ERS-1/2) images, respectively acquired
in 1992–2001 and 1992–1995. The results obtained from this analysis highlighted
the potentiality of remote-sensing tools in landslide hazard assessment and led to
development of a research project based on the installation of corner reflectors
along unstable slopes and aimed at creating a field–Earth observation monitoring
system.
1. Introduction
The role of monitoring has been recognized as central and decisive in the analysis
of landslides (Hutchinson 1983, Turner and McGuffey 1996): it may help to answer
questions such as ‘if, how, and when might slope instability occur?’ (Barla et al. 2006).
Thus, monitoring represents a fundamental tool for obtaining deep knowledge of the
*Corresponding author. Present address: IREA-CNR, Naples, Italy.
Email: calo.f@irea.cnr.it
International Journal of Remote Sensing
ISSN 0143-1161 print/ISSN 1366-5901 online © 2012 Taylor & Francis
http://www.tandf.co.uk/journals
http://dx.doi.org/10.1080/01431161.2011.630331
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

Assessing the activity of a large landslide, southern Italy 3513
phenomenon under investigation, prevention of the associated risk and, consequently,
protection of the potentially affected environment.
Several monitoring techniques are generally used (Mikkelsen 1996, Turner and
McGuffey 1996, Barla et al. 2006, Wieczorek and Snyder 2009) for measuring the
slope deformation, starting from surface and subsurface ground investigations.
The long-term sustainability of an effective monitoring network based on ground
instrumentation is often hampered by financial and technical limitations, such as dif-
ficult accessibility of the site, availability of expert operators, extension of the area
under investigation and consequent high management costs over time. Monitoring
should ideally last for a very long period in order to detect changes in the landslide
behaviour and to relate them to possible environmental factors (Turner and McGuffey
1996).
In the last decades, many researches have emphasized the role of remote-sensing
techniques in landslide investigations and analysis. Particularly, for monitoring pur-
poses, differential synthetic aperture radar (SAR) interferometry (DInSAR) tech-
niques may help to overcome most of the above limitations related to ground
monitoring, going from a ‘point-wise’ to a ‘wide area’ analysis of the investigated
phenomenon. Further, they produce highly accurate final results, which is a funda-
mental requisite, particularly in the case of landslides moving with rates of velocity in
the order of centimetres per year or millimetres per year.
DInSAR techniques exploit the phase information of the SAR electromagnetic
signal: by computing the phase differences between SAR images (Franceschetti and
Lanari 1999) of the same area acquired at different times, it is possible to retrieve
the surface displacements that occurred in the meantime and, thus, produce a defor-
mation map of that area (Burgmann et al. 2000a, Hanssen 2001). Several successful
interferometric applications are reported in the scientific literature, pointing out the
potentialities of this remote-sensing tool in detecting and monitoring surface deforma-
tion. They include monitoring of ice-sheet motion (Goldstein et al. 1993) and volcanic
areas (Massonnet et al. 1995, Lanari et al. 2004a, Bonforte et al. 2007), co-seismic dis-
placements (Massonnet et al. 1993, Burgmann et al. 2000b), subsidence connected to
groundwater systems (Amelung et al. 1999, Bell et al. 2002) and terrain deformation
caused by mining (Raucoules et al. 2003, Colesanti et al. 2005). Even in more difficult
situations, DInSAR has been successfully applied to landslide areas in several geolog-
ical contexts worldwide (Fruneau et al. 1996, Nagler et al. 2002, Antonello et al. 2004,
Hilley et al. 2004, Singhroy and Molch 2004, Rott and Nagler 2006, Cascini et al. 2009,
2010).
In the following, the results coming from a monitoring system based on the use
of field and Earth observation data are reported, in order to analyse how such an
integrated approach can improve landslide studies. The monitored landslide site is
Calitri in southern Italy. Historical data sets of inclinometer readings related to differ-
ent time intervals (1981–1984; 1992–1994) allowed investigation into the activity of the
large Calitri landslide since its seismic reactivation in late 1980. Further, we integrated
the information coming from the ground instrumentation with that derived by SAR
interferometric products, whether already available (in the case of permanent scat-
terers (PS)-InSAR analysis conducted by Telerilevamento Europa (TRE)–Politecnico
di Milano (PoliMi)) or generated by our processing of Earth Resource Satellite 1/2
(ERS-1/2) SAR images. Finally, preliminary results of inclinometric measurements,
carried out since 2008 in the context of an integrated monitoring system based on
ground instrumentation and SAR interferometric techniques, will be reported.
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

3514 F. Calò et al.
2. Geologic and geomorphologic setting
The study area is located along the left valley side of the Ofanto River (Campania
region; see figure 1(a)), geologically characterized by the presence of a regressive suc-
cession of clay and grey–blue siltites, sandstones, sands and conglomerates of Pliocene
age (Budetta et al. 1990). In particular, the town of Calitri is built on top of a
hill (figure 1(b)), where also pre-Pliocene varicoloured clays, called hereafter Argille
Varicolori, crop out; they are made up of a chaotic mass of scaly clays of various
colours (grey, red and green), including more competent terms of marly carbonate and
calcilutites (Parise and Wasowski 1996). This material, highly tectonized and locally
sheared, can be described as a ‘structurally complex formation’ (Esu 1977, A.G.I.
1979) and, due to its geotechnical and structural characteristics, it is very susceptible
to mass movements (Hutchinson and Del Prete 1985).
The town of Calitri and its surroundings have been historically affected by large
gravitational phenomena, induced or reactivated by meteoric or seismic events, such
as in the case of the large Calitri landslide remobilized by the 23 November 1980
earthquake.
Due to the active tectonism of the southern Apennines, the Irpinia region, where
Calitri is located, is characterized by very high seismic hazard (Slejko et al. 1998). On
many occasions, earthquakes have caused loss of property, severe damage to historical
buildings and a large number of deaths.
The last catastrophic earthquake recorded in Irpinia occurred at 19 h 34 min 54 s
local time on 23 November 1980; it was characterized by a 6.5 magnitude main shock
that lasted for about 50 s (Hutchinson and Del Prete 1985) and was recorded up to
hundreds of kilometres from the epicentre. The 1980 earthquake represented one of
the most destructive events to have affected southern Italy, in terms of human life
(about 3000 deaths) and economic damage deriving directly from the seismic shaking
Figure 1. Location of the study area (a) and view of the Calitri hill (Campania region,
southern Italy) (b).
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

and indirectly from the numerous landslides induced and/or reactivated in a large area
around the epicentre (Cotecchia and Del Prete 1984, Carrara et al. 1986, Cotecchia
1986, Cotecchia et al. 1986). Estimates (in terms of areal frequency) reported that 35%
of pre-existing landslides were triggered by the 1980 earthquake, in an area already
heavily affected by landsliding (Agnesi et al.1983, Parise and Wasowski 1996, 1999).
In Calitri, almost all the damage resulted from the movement of the landslide, and
only the eastern part of the old town, outside the slide area, suffered direct earthquake
damage of low severity.
The large landslide occurred at about the same time of the main shock and led to
vertical surface displacements of some metres in the top area (Hutchinson and Del
Prete 1985).
The geology of the slide area that involved the slope facing approximately south-
west towards the Ofanto River, with average inclination of 10◦
, mainly consists of
sand lenses within Pliocene blue siltites, in which also olistostromic lenses of Argille
Varicolori are present. The landslide is a complex phenomenon, in which four main
elements have been identified (Hutchinson and Del Prete 1985): (1) a large deep-seated
slide that mobilized a volume of around 20 × 106
m3
of material, with the main scarp
of the slide intersecting the old part of the town; (2) secondary slides at the head of
the main slide; (3) shallow slides close to the toe of the main slide; and (4) shallow
mudslides that reached and dammed the Ofanto River.
In addition to the large Calitri landslide, the main instability phenomena in the
area are represented by shallow slope movements, often as soil slips–debris flows, or
earthflows, which are present mainly in the clay slopes.
Analysis of the current spatial distribution of landslides and evaluation of their state
of activity have been performed through field surveys carried out in 2009 in Calitri
and its surroundings, and an updated landslide inventory map has been produced, in
which a distinction between the active and dormant landslides and erosion areas is
shown (figure 2).
Figure 2. Extract of the landslide inventory map of the Calitri area (field surveys carried out
in 2009). Blue, active landslide; black, dormant landslide; violet, active erosion area; green,
dormant erosion area.
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

3. Data processing, analysis and interpretation
3.1 Ground monitoring
Following the 1980 earthquake and its destructive effect on the territory, the Calitri
landslide has been monitored during two campaigns of subsurface investigations,
aimed at analysing the stability of the area affected by the seismically reactivated land-
slide: the first was carried out during 1981–1984, in order to analyse the stability of the
area in the immediate aftermaths of the earthquake, and the second during 1992–1994
in the context of an engineering project addressing landslide remedial works (table 1;
figure 3). Finally, it is worth pointing out that an ongoing monitoring campaign, which
consists of monitoring seven inclinometer boreholes, selected among those drilled dur-
ing the 1981–1984 and 1992–1994 campaigns, has been carried out since July 2008, in
order to collect further updated data on ground movements (table 1; figure 3).
3.1.1 1981–1984 monitoring campaign. The 1980s’ monitoring campaign consists
of inclinometer measurements performed in 13 boreholes located at variable depths,
between 10 and 100 m, within the landsliding area (table 1; figure 3). Five of them,
related to shallower boreholes (depth 10–17 m), were first monitored in February 1981
in order to eventually detect movements caused by aftershocks.
Subsequently, since 1982, the other boreholes, distributed along the main slide,
have been monitored, allowing exploration of the behaviour of the main landslide
at greater depths (in the range 31–100 m). It has to be noted that these inclinometers
had already been monitored during three occasions between June and October 1981
by Hutchinson and Del Prete (1985), bringing the authors to suppose the existence of
a main slip surface at a depth greater than 100 m.
Significant cumulated displacements at the surface are registered in the main deep-
seated slide affecting the old town, in particular in its middle–lower portion monitored
by the I1, I5 and I7 inclinometer boreholes detecting, from March 1982 to November
1984, the highest values of cumulated displacements of, respectively, 7.7, 7.4 and
6.9 cm. Regarding the mudslide (as termed by Hutchinson and Del Prete (1985))
extending down to the Ofanto River, the inclinometer measurements carried out in
the I4 borehole were recorded monthly from March to December 1982 and registered
a cumulated displacement of 6.4 cm in less than 1 year, highlighting a significant state
of activity of the shallower mudslide, whose thickness is around 8 m.
3.1.2 1992–1994 monitoring campaign. In the early 1990s, during the works aimed
at stabilizing the landslide, 12 further boreholes, characterized by depths between 18
and 29 m, were installed on the main landslide body in order to monitor the slope
after the realization of the project (table 1; figure 3).
Table 1. Ground-based data sets and their characteristics.
Time interval
Type of
measurements
Number of
boreholes
Number of
readings
Depth of
boreholes (m)
1981–1984 Probe inclinometer 13 8–33 10–100
1992–1994 Probe inclinometer 12 11–20 18–29
2008 to present Probe inclinometer 7 4 27–31.5
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

1980 landslide
1981–1984
1992–1994
2008 to present
Figure 3. Location of the inclinometer boreholes, I (monitoring campaign: 1981–1984) and
S (monitoring campaigns: 1992–1994; 2008 to present). In addition, the main landslide body
reactivated by the 1980 earthquake is reported; the dashed line represents a secondary slide
localized at the northwestern corner of the main slide (after Hutchinson and Del Prete (1985)).
Inclinometer measurements conducted monthly over 2 years (July 1992–June 1994)
registered an overall significant decrease of the slope displacements. Indeed, the mea-
sured displacements are of an order of magnitude lower than those recorded during
the 1981–1984 campaign, with cumulated values ranging from 0.2 to 1.9 cm. In par-
ticular, the highest values of cumulated displacements were registered in boreholes S5
and S12, confirming the major activity of the middle-lower portion of the depletion
zone (WP/WLI 1993), as was also the case during the monitoring campaign carried
out in the 1980s.
Despite the limited depth as well as the low values of displacements recorded by
these inclinometers, they allowed retieval of valid information on the existence of
multiple slip surfaces. In particular, the displacement–depth graph related to S12
demonstrates the existence of multiple shear surfaces, the deepest of which is local-
ized at about 27 m from the ground surface, that occurred between January and
March 1993 (figure 4(c)). Analogously, in the same period, a slip surface at about
16 m depth can be deduced from the measurements carried out in the S6 borehole
(figure 4(b)). Shallow movements, with a shear zone at about 5 m depth, are recorded
by the S4 inclinometer, leading to a cumulated displacement of about 1 cm in 2 years
(figure 4(a)).
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

30.0
25.0
20.0
15.0
10.0
5.0
Depth
(m)
0.0
0 1
Displacement (cm)
(e)
30.0
25.0
20.0
15.0
10.0
5.0
Depth
(m)
0.0
0 1 2
Displacement (cm)
(d)
30.0
25.0
20.0
15.0
10.0
5.0
Depth
(m)
0.0
1
0 2 3
Displacement (cm)
( f )
Depth
(m)
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
20.00
0.0 5.0 10.0 15.0
Displacement (mm)
(b)
Depth
(m)
35.00
30.00
25.00
20.00
15.00
10.00
5.00
0.00
0.0 5.0 10.0 15.0 20.0 25.0
Displacement (mm)
(c)
Depth
(m)
2 Jul 1992
28 Jul 2008 28 Jul 2008
27 Nov 2008
28 Jul 2008
27 Nov 2008
9 Oct 2008
22 May 2008
9 Oct 2008
22 May 2008
9 Oct 2008
22 May 2008
27 Nov 2008
5 Aug 1992 9 Sep 1992
2 Jul 1992 2 Jul 1992 5 Aug 1992 9 Sep 1992 13 Oct 1992
4 Mar 1993
25 Oct 1993
18 Feb 1994
15 Jun 1994
20 Jan 1993
20 Sep 1993
27 Jan 1994
12 May 1994
17 Dec 1992
27 May 1993
15 Dec 1993
21 Apr 1994
16 Nov 1992
20 Apr 1993
22 Nov 1993
16 Mar 1994
5 Aug 1992 9 Nov 1992
17 Dec 1992
20 Apr 1993
25 Oct 1993
27 Jan 1994
21 Apr 1994
6 Nov 1992
4 Mar 1993
20 Nov 1993
15 Dec 1993
16 Mar 1994
15 Jun 1994
13 Oct 1992
20 Jan 1993
27 May 1993
22 Nov 1993
18 Feb 1994
12 May 1994
17 Dec 1992
20 Apr 1993
6 Nov 1992
4 Mar 1993
13 Oct 1992
20 Jan 1993
35.00
30.00
25.00
20.00
15.00
10.00
5.00
0.00
0.0
(a)
5.0 10.0 15.0 20.0
Displacement (mm)
Figure 4. Inclinometer readings related to S4 (a), S6 (b), S12 (c) boreholes (monitoring cam-
paign: 1992–1994; reference measure: 29 May 1992) and to S10 (d), S14 (e) and S162 (f )
boreholes (monitoring campaign: 2008 to present; reference measure: 12 June 2008).
3.1.3 Ongoing monitoring campaign (2008 to present). Starting from June 2008, sev-
eral field surveys have been carried out in order to identify, among the old inclinometer
boreholes, those that were still able to be currently monitored. Most of the boreholes
were not found, due to new construction or being covered by man-made activities,
while some of them were identified but were not suitable to be monitored because
of complete or partial filling. Among the boreholes installed in the two campaigns
discussed above, only seven, still found in good condition, have still been measured
since July 2008 (table 1; figure 3), and their data, the first of which are shown in figure
4(d)–(f ), will be integrated within an ongoing research project based upon the use of
DInSAR techniques and will contribute to validate the interferometric results.
3.2 DInSAR monitoring
Landslide monitoring probably represents the most difficult DInSAR application,
compared with other deformation phenomena, for example subsidence. This is mainly
due to the characteristics of the landslide areas, including aspect and gradient of
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

the slopes (Colesanti and Wasowski 2006), failure mechanisms, vegetation cover and
deformation rate. Furthermore, the characteristics of SAR systems, such as incidence
angle, spatial resolution, wavelength and revisiting time, have to be taken into account
when studying a landslide area with DInSAR (Poncos 2008).
Many advanced techniques have been proposed for landslide analysis, such as the
PS (Ferretti et al. 2000, 2001) and Small Baseline Subsets (SBASs; Berardino et al.
2002). They are based on a database approach: exploiting stacks of SAR images, these
interferometric techniques allow us to mitigate the possible errors and obtain very
accurate results and, at the same time, analyse the temporal evolution of the landslide
under investigation.
The PS technique is based on the detection of dominant radar targets, the so-called
permanent scatterers, smaller than the resolution cell, that remain coherent over long
time intervals (Ferretti et al. 2000, 2001); further, they are unaffected by spatial decor-
relation, preserving high coherence even with very large baselines and thus allowing
the exploitation of all the archives of SAR images available for a certain area.
The detection of PS is basically performed by analysing the behaviour in time of
the image pixels. To this end several methods were developed: a comparison among
them, pointing out the relative advantages and drawbacks, can be found, for example,
in Poncos (2008). Therefore, over the detected point scatterers, deformation measure-
ments with an accuracy in the order of millimetres can be obtained (Ferretti et al.
2001).
It is evident that interferometric techniques based on measurements over electro-
magnetic stable scatterers can be successfully applied in fast decorrelating areas also
where some anthropogenic features are present, thus allowing their monitoring over
large time intervals. On the other hand, the PS techniques lose one of the main
advantages that make DInSAR so attractive with respect to the traditional ground
techniques: the ability to monitor wide areas and not just a limited number of points.
The SBAS technique, based on a different approach, allows us to obtain deforma-
tion maps over large areas, even if with lower accuracy, that is, in the order of half a
centimetre in coherent zones (Berardino et al. 2003).
SBAS uses only small baseline interferograms, thus allowing us to release the point
target condition. It is particularly suitable for application in urbanized areas (Usai
2003), where the coherence is preserved over a long time and, thus, many interferomet-
ric combinations with low baseline values can be found, while its application in areas
characterized by quick decorrelation is strongly limited. The technique is substantially
based on a least square (LS) approach: since multiple combinations of interferograms
are performed and different values of phase are found for each acquisition date, an LS
solution is applied. In this way, from all the generated interferograms, it is possible to
obtain the time series of displacements and, at the same time, mitigate the effect of pro-
cessing and decorrelation errors, by exploiting the redundancy of phase information
for each date (Usai 2003). The algorithm based on the singular value decomposition
(SVD) approach, presented by Berardino et al. (2002), allowed improvement of the
‘temporal sampling rate’. It basically extends the LS approach to the case of sepa-
rate SBAS that will be subsequently combined on the basis of a selected criterion
(i.e. the minimum norm criterion of the velocity deformation), in order to use all the
acquisitions belonging to the different subsets (Berardino et al. 2002, Lanari et al.
2004b, 2007).
The Calitri area has been analysed through both the aforementioned SAR interfero-
metric techniques (see table 2) in order to observe the activity of a portion of territory
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

Table 2. DInSAR data sets and their characteristics.
Time interval Type of analysis Satellite Orbit Number of SAR images
1992–2001 PS ERS-1/2 Descending 81
Ascending 44
1992–1995 SBAS ERS-1/2 Descending 16
2008 to present SBAS Cosmo-SkyMed Descending Ongoing acquisition
Note: PS, Permanent Scatterers; SBAS, Small BAseline Subset.
wider than that covered by inclinometer measurements and to eventually detect and
map areas affected by ground displacements not revealed by ground monitoring.
3.2.1 PS-InSAR analysis. The PS-InSAR analysis (performed by T.R.E–PoliMi)
consisted of processing 81 descending-orbit and 44 ascending-orbit ERS images
acquired during 1992–2001 (table 2), which allowed identification of respectively,
around 2300 and 1400 PS over all of Calitri town, including its historical and recently
built parts located on the slope, as well as its industrial area in the Ofanto River valley
(figure 5).
The PS data, and the temporal evolution of their displacements, have been extracted
by the regional interferometric analysis performed over the Campania territory in the
context of the Telelerilevamento Laboratori Unità di Supporto (TELLUS) project
Corner reflector
>2
>2
–2 to 2
–4 to –2
–6 to –4
–5.8 to –4
–4 to –2
–2 to 2
< –6
Displacement rate (mm year
–1
)
Displacement rate (mm year–1
)
1980 landslide
Figure 5. Map showing the location of the permanent scatterers and their average displace-
ment rate along the radar line of sight (LOS) direction. In addition, the landslide body
reactivated by the 1980 earthquake and the radar corner reflectors installed in 2008 along its
longitudinal profile are reported.
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

(TRE 2006). In particular, a standard PS analysis (SPSA) has been conducted, allow-
ing us to extract information on the yearly average velocity of the PS along the line
of sight (LOS) direction and to produce the time series of the displacements for
about 31% of PS that are characterized by a minimum coherence of 0.82 and 0.75,
respectively, for the ascending and descending data sets.
The map in figure 5 reports the PS divided into different velocity classes, accord-
ing to their average displacement rate (mm year−1
), pointing out the high spatial
density of the radar targets in the Calitri area. The accuracy of PS positioning is
around ±5 m in the easting direction and around ±2 m in the northing direction
(for PS located within 2 km from the reference point). The velocity class delimited
by the ±2 mm year−1
threshold indicates stable PS, according to the precision achiev-
able with the PS technique that depends on several factors, such as climatic conditions
during the radar acquisition, number of available SAR images and distance from the
reference point supposed motionless (Meisina et al. 2008). In terms of percentages, the
majority of the identified PS falls in this class, and it is possible to consider them as not
affected by movements. With the exception of ascending PS moving with an average
displacement rate between −4 and −2 mm year−1
, the percentages of PS belonging
to the other velocity classes are significantly low, reaching 0.1% and 0.8%, respec-
tively, for the descending and ascending PS moving with a velocity V between −11.4
and −6 mm year−1
and between −5.8 and −4 mm year−1
that represent the highest
observed values.
By examining the spatial distribution of the PS (figure 5), it can be observed that, as
a whole, the urban centre of Calitri appears stable during the analysed time interval.
Isolated PS show movements that could be related to other causes, such as settlement
of buildings due to soil foundations or to structural problems.
It is worth pointing out that the PS analysis brought very limited results on the
unstable slope affected by the large phenomenon reactivated by the 1980 earthquake:
here, the presence of few anthropogenic features and, due to its mostly clay nature, the
absence of outcropping rocks made it feasible to detect only a small number of radar
dominant targets. However, a ‘homogeneous area’ with PS moving with a maximum
average displacement rate of 5.8 mm year−1
can be observed in the middle portion of
the slope, where some active erosional areas were mapped during the field survey (see
figure 2).
3.2.2 SBAS analysis. The Calitri site has been interferometrically analysed by
processing 15 single look complex (SLC) images (descending passes) acquired in
the period 1992–1995 (table 2); further, an external digital elevation model (DEM)
obtained by digitizing the 5 m contours of the 1:5000 ‘CTR Campania 1998’ topo-
graphic map has been used. The DEM was characterized by a spatial resolution of 5 m
× 5 m and an accuracy of 5 m, and allowed us to estimate and subtract the topographic
component, in order to isolate the information related to the deformation of the area.
First, all the SAR images have been co-registered. The co-registration usually con-
sists of matching all the SLC images on a unique master. In our implementation of
the SBAS technique, an alternative procedure has been used, allowing us to easily per-
form a good co-registration: the images have been matched using some tens of ground
control points (GCPs) spatially distributed over the whole area of interest.
Subsequently, a database of interferograms (table 3) has been produced, by taking
pairs of images with relatively short perpendicular baselines, in order to make the
topographic phase suppression easier and reduce the effects of spatial decorrelation.
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

Particularly, three subsets of 12, 6 and 7 interferograms (table 3; figure 6) have been
used for producing displacement maps with a resolution of about 50 m × 50 m, by
applying an LS approach without a priori hypothesis on the temporal behaviour of
deformation.
Figure 7 shows examples of cumulated displacement maps related to the first subset.
Furthermore, in order to extend the monitoring period (1992–1995), 25 interferograms
(see table 3) have been combined for generating a velocity map based on a linear tem-
poral model (figure 7(f )). The geocoding accuracy of the results is around ±5 m in the
easting direction and ±2.5 m in the northing direction.
All the final maps reported in figure 7 show that no relevant surface movements
have been detected by DInSAR analysis, and therefore the investigated area can be
considered stable overall. However, it is worth pointing out that, from an interfero-
metric standpoint, the Calitri area resulted in a fast decorrelating zone because of the
intense vegetation cover. The weather conditions of the area – quite rainy – added
further decorrelation effects and made the retrieval of low deformation rates, such
as those estimated by ground monitoring, very difficult. As a result, even in the less
noisy interferogram, only a few coherent patches corresponding to urban zones are
present, while the pixels imaging most of the landslide body (see inset representing the
study area in figure 7) have been masked because they are characterized by a coherence
lower than the used coherence’s threshold that was set equal to 0.2 for a compromise
between the degree of phase noise and the number of selected pixels.
4. Conclusions and discussion
Due to uncontrolled urbanization and non-sustainable planning and management of
the territory, in Campania region (southern Italy), many urban centres and much
infrastructure have been developed on unstable slopes in structurally complex for-
mations affected by slow-moving landslides. The control of the interaction between
mass movements and anthropogenic features represents one of the main issues for
local and regional authorities worldwide (Van Westen et al. 2008), in order to pre-
vent slope instabilities or at least to mitigate the resulting damage. It is evident that,
in this context, efforts in Campania should be addressed to develop new monitoring
methodologies aimed at controlling the evolution of slope instability phenomena at
the regional scale. The use of remote-sensing techniques, and in particular of SAR
interferometric techniques providing information on ground displacements, can help
in identifying, over a regional territory, areas at high risk on which further analysis and
investigations should be carried out. An integrated approach, based on coupling tra-
ditional methods of landslide analysis with such interferometric techniques, has been
applied to the case study of Calitri, well known to the scientific community working
on landslides for the large slope movement reactivated by the 1980 Irpinia earthquake
that severely affected most of the urban centre.
The analysis of the seismically induced landslide at Calitri has been for many years
a matter of debate, due to the complexity of the phenomenon and the difficulties in its
interpretation. The Calitri landslide is a complex slope movement, mainly composed
of two elements: a large deep-seated slide whose main scarp was developed in the old
town and a shallow mudslide, involving the middle-lower portion of the slope going
down to the Ofanto River.
Accurate research into the available data derived from surface and subsurface inves-
tigations carried out after the 1980 earthquake has been performed at the archives of
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

Table
3.
Interferometric
pairs
used
in
the
DInSAR
analysis
and
values
of
temporal
(T)
and
perpendicular
(B
perp
)
baselines.
First
subset
(I)
Second
subset
(II)
Third
subset
(III)
Number
Image
pair
T
(day)
B
perp
(m)
Number
Image
pair
T
(day)
B
perp
(m)
Number
Image
pair
T
(day)
B
perp
(m)
1
920710_921023
105
74
13
920918_921127
70
133
19
951001_951105
35
216
2
921023_930521
210
80
14
921127_930416
140
65
20
951001_951106
36
37
3
930521_931008
140
76
15
930416_930730
105
433
21
951001_951211
70
96
4
931008_931112
35
31
16
920918_930416
210
198
22
951105_951106
1
179
5
930521_930730
70
385
17
920918_930730
315
235
23
951105_951211
35
312
6
930730_931008
70
309
18
921127_930730
245
368
24
951106_951211
34
133
7
930521_931112
175
107
25
950827_950828
1
54
8
920710_930521
315
6
9
920710_931008
455
82
10
920710_931112
490
113
11
921023_931008
350
156
12
921023_931112
385
187
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

1000
800
600
400
200
Perpendicular
baseline
(m)
0
–200
0 200 400 600
Days after July 1992
800 1000 1200 1400
Figure 6. Spatial versus temporal baseline, with SAR acquisition dates (nodes) and inter-
ferograms (lines) for the three subsets. Triangles: subset I; squares: subset II; diamonds:
subset III.
cm
–1.7 0.0 0.0 5.1
–5.2
mm year–1
2.9
(a)
(d)
(b)
(e)
(c)
( f )
Figure 7. Maps of the evolutionary trend of cumulated displacements ((a) 23 October 1992;
(b) 21 May 1993; (c) 30 July 1993; (d) 8 October 1993; (e) 12 November 1993; reference date:
7 July 1992). Map of the average displacement rate along the LOS direction ((f ) 10 July 1992 to
11 December 1995). The red inset represents the large landslide under investigation; the white
arrow indicates the satellite LOS (descending orbit).
private companies and public administrations. As a result, data relating to two mon-
itoring campaigns consisting of inclinometer measurements have been collected. The
first monitoring data covering the 1981–1984 period were aimed at checking the sta-
bility of the landslide area during the years immediately after the 1980 main seismic
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

shock; the second monitoring data covering the 1992–1994 period were acquired in
order to check the efficiency of an engineering project aimed at landslide control. Both
the data sets have been processed and critically analysed: although related to different
boreholes, they gave information on the overall behaviour of the phenomenon and
pointed out that its activity decreased over time, significantly after the completion of
engineering control works.
In addition, a detailed geomorphologic study has been performed, and an updated
landslide inventory map has been produced, showing the spatial distribution of
slope movements in the Calitri territory. The geomorphologic and historical analy-
sis, together with the inclinometer measurements, pointed out that the activity of the
whole landslide body is mainly related to the major seismic events, while only shal-
lower phenomena involving its limited portions showed activity linked with rainfall.
The application of interferometric techniques to Calitri confirmed that no sig-
nificant movements affected the area during the analysed period and, at the same
time, highlighted some of the main drawbacks encountered when studying landslides
with DInSAR. These drawbacks are mainly related to the direction of the measured
displacement vector and to the low radar coherence in vegetated areas.
Employed ground instrumentation and SAR sensors actually measure different
components of the displacement. As a matter of fact, in situ data are obtained by using
inclinometers that are able to measure the horizontal components of the displacement.
Conversely, the DInSAR technique is only able to measure the displacement compo-
nent along the satellite’s LOS. In particular, due to the ERS acquisition geometry,
DInSAR systems are not sensitive to the north–south component of movement, and
the retrieved displacement value is a combination of the east–west and vertical com-
ponents, with a higher weight for the latter, due to the 23◦
look angle. For the landslide
site investigated in this work, the slope aspect is along the north–south direction and
the horizontal component of the displacement is mostly along this direction; therefore,
DInSAR measures a displacement only if a significant vertical component is present.
Indeed, the highest values of displacement measured by PS-InSAR are relative to
scatterers located in the northeast sector of the landslide crown where the rotational
movement, and thus the vertical displacement component, is expected to be dominant,
and furthermore, the local aspect of the slope is mainly northeast/southwest.
Even if the main scarp is developed in the urban centre, a large portion of the land-
slide phenomenon, particularly the active mudslide going down to the Ofanto River,
involves a vegetated slope where only few anthropogenic features are present. As a
consequence, the PS technique gave a good density of stable scatterers over the whole
urban centre located on the top of the hill but resulted in only a few of them over
the middle portion of the slope. The limited PS information that related to the slope
affected by the large seismically induced landslide led us to carry out SBAS processing,
by using ERS-1/2 SLC images acquired during 1992–1995.
The results provided by the two presented techniques, that is PS-InSAR and SBAS,
are different. PS-InSAR measures displacements of single scattering targets, thus
relative to individual ground objects. Conversely, SBAS measures the average dis-
placements over resolution cells of about 50 m × 50 m (in this case study). In
addition, PS monitoring was based on a wider temporal interval (1992–2001) than
SBAS (1992–1995). Finally, both ascending and descending data sets were used in
PS-InSAR analysis, whereas only descending images were processed by the SBAS
technique. Accordingly, it is worth pointing out that one must be very careful when
comparing results from the two approaches. Nevertheless, a good agreement between
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

the two techniques is obtained: no moving areas have been detected by applying the
SBAS technique, confirming the overall stability of the urban centre of Calitri that
resulted from the PS-InSAR analysis.
However, even by choosing a relatively low coherence threshold as a trade-off
between the quality of phase and the number of resulting pixels, it was not possible to
retrieve, by SBAS, information on the deformation of most of the landslide body, due
to the kind of land cover affected by heavy temporal decorrelation.
In order to monitor and analyse the activity of the whole landslide, including its
most active portion extending from the middle slope to the Ofanto River, in late 2008,
eight corner reflectors have been installed close to the inclinometer boreholes. These
trihedral reflectors are distributed along the longitudinal profile of the mass movement
(see figure 5) and represent high coherent radar points in the decorrelated landslide
area. The interferometric processing of high-resolution SAR images acquired since
2008 over the study area by Cosmo-SkyMed satellites is ongoing by our team, in order
to analyse the behaviour of the whole slope thanks to ad hoc located corner reflectors.
At the same time, inclinometer measurements have been carried out since late 2008, in
order to update by ground truth the information on landslide movements.
The results of the presented work suggest that the relatively recent advanced
DInSAR techniques show a high potential in the field of slope movements, but the
feasibility of a landslide monitoring system based only on their use needs to be care-
fully evaluated. If the possible advantages are relevant and allow us to overcome some
limitations of the ground-monitoring techniques (e.g. inaccessibility of the unstable
sites, problems of installation and maintenance of the instrumentation, large extent of
the areas to be monitored and high management costs), it should be noted that they
currently cannot replace, overall, in situ measurements.
The reliability of interferometric results strongly depends on the characteristics of
the study area. The first concern regards the gradient and the aspect of the slopes,
which strongly limit the use of SAR images and thus of DInSAR techniques in
landslide monitoring. By assuming that the landslide area under investigation is
not affected by significant SAR geometric distortions, the choice of ascending and
descending orbits depends on the specific orientation of the slope. Second, the main
drawback of DInSAR monitoring results from the temporal decorrelation effects,
which can be particularly heavy in many settings of the southern Apennines, where
landslides involve vegetated slopes. The use of thematic maps such as land-cover maps,
as well as the analysis of the climatic data during and immediately before the acquisi-
tions, particularly in environments often affected by bad weather conditions, can help
in preliminarily evaluating the amount of the expected decorrelation. The problems
coming from the temporal decorrelation can be overcome by installing corner reflec-
tors, as in the case study presented here. However, in such a case, the opportunity to
exploit historical data sets in order to perform a temporal analysis of the deformation,
which is a great advantage particularly when the research aim is the detection of the
phenomena precursors, is lost.
Finally, it should be noted that a quantitative exploitation of the interferometric
results in slope movement studies is still difficult, due both to the SAR system capa-
bility to record only the LOS projection of a 3D deformation and to the complexity
of the landslide kinematics. Such an aspect represents the main limitation of DInSAR
techniques when compared with the global positioning system (GPS) and topographic
measurements that provide 3D data, and may be overcome only if both the ascending
and descending data sets are exploited.
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

Currently, compared with ground monitoring, the main attractive capability of
DInSAR is to provide information on the (in)stability of wide areas affected by
slow-moving landslides, and therefore it represents a useful tool in the fields of
urban/regional planning and civil protection.
Acknowledgements
We are grateful to Studio di Ingegneria by Ing. Sabini (Naples) and especially to
Dr Antonio Di Meglio, for kindly providing the historical inclinometer data and to
Dr Italo Giulivo (Soil Defense Department – Campania Region) and the Progetto
Operativo Difesa Suolo (PODIS) working group for allowing access to PS data, within
the framework of a cooperation programme between the University of Naples and
Campania Region.
References
A.G.I., 1979, Some Italian experiences on the mechanical characterization of structurally
complex formations. In 4th International Congress I.S.R.M., 2–8 September 1979,
Montreux, Switzerland, pp. 827–846.
AGNESI, V., CARRARA, A., MACALUSO, T., MONTELEONE, S., PIPITONE, G. and SORRISO
VALVO, M., 1983, Elementi tipologici e morfologici dei fenomeni di instabilità dei ver-
santi indotti dal sisma 1980 nell’alta valle del Sele. Geologia Applicata e Idrogeologia,
18, pp. 309–341.
AMELUNG, F., GALLOWAY, D.L., BELL, J.W., ZEBKER, H.A. and LACZNIAK, R.J., 1999, Sensing
the ups and downs of Las Vegas: InSAR reveals structural control of land subsidence
and aquifer-system deformation. Geology, 27, pp. 483–486.
ANTONELLO, G., CASAGLI, N., FARINA, P., LEVA, D., NICO, G., SIEBER, A.J. and TARCHI, D.,
2004, Ground-based SAR interferometry for monitoring mass movements. Landslides,
1, pp. 21–28.
BARLA, G., CHIAPPANE, A. and VAI, L., 2006, Slope monitoring systems. In XI Ciclo di
Conferenze di Meccanica e Ingegneria delle Rocce. Instabilità di versante. Interazioni con
le Infrastrutture, i Centri Abitati e L’Ambiente, 28–29 November 2006, Torino, Italy
(Bologna: Patron Editore), pp. 177–202.
BELL, J.W., AMELUNG, F., RAMELLI, A. and BLEWITT, G., 2002, Land subsidence in Las Vegas,
Nevada, 1935–2000: new geodetic data show evolution, revised spatial patterns, and
reduced rates. Environmental Engineering Geoscience, 8, pp. 155–174.
BERARDINO, P., CONSTANTINI, G., FRANCESCHETTI, G., IODICE, L., PIETRANERA, L. and
RIZZO, V., 2003, Use of differential SAR interferometry in monitoring and modelling
large slope instability at Matera (Basilicata, Italy). Engineering Geology, 68, pp. 31–51.
BERARDINO, P., FORNARO, G., LANARI, R. and SANSOSTI, E., 2002, A new algorithm for surface
deformation monitoring based on small baseline differential SAR interferograms. IEEE
Transactions on Geoscience and Remote Sensing, 40, pp. 2375–2383.
BONFORTE, A., GAMBINO, S., GUGLIELMINO, F., OBRIZZO, F., PALANO, M. and PUGLISI, G.,
2007, Ground deformation modeling of flank dynamics prior to the 2002 eruption of
Mt. Etna. Bulletin of Volcanology, 69, pp. 757–768.
BUDETTA, P., CALCATERRA, D., DE RISO, R. and SANTO, A., 1990, Geologia e fenomeni fra-
nosi dell’Alta Valle del fiume Ofanto (Appennino Meridionale). Memorie Della Società
Geologica Italiana, 45, pp. 309–324.
BURGMANN, R., ROSEN, P.A. and FIELDING, E.J., 2000a, Synthetic aperture radar interferome-
try to measure Earth’s surface topography and its deformation. Annual Review of Earth
and Planetary Science, 28, pp. 169–209.
BURGMANN, R., SCHMIDT, D., NADEAU, R.M., D’ALESSIO, M., FIELDING, E., MANAKER, D.,
MCEVILLY, T.V. and MURRAY, M.H., 2000b, Earthquake potential along the northern
Hayward fault, California. Science, 289, pp. 1178–1182.
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

CARRARA, A., AGNESI, V., MACALUSO, T., MONTELEONE, S. and PIPITONE, G., 1986, Slope
movements induced by the southern Italy earthquake of November 1980. Geologia
Applicata e Idrogeologia, 21, pp. 237–250.
CASCINI, L., FORNARO, G. and PEDUTO, D., 2009, Analysis at medium scale of low-
resolution DInSAR data in slow-moving landslide-affected areas. ISPRS Journal of
Photogrammetry and Remote Sensing, 64, pp. 598–611.
CASCINI, L., FORNARO, G. and PEDUTO, D., 2010, Advanced low- and full-resolution DInSAR
map generation for slow-moving landslide analysis at different scales. Engineering
Geology, 112, pp. 29–42.
COLESANTI, C., LE MOUELIC, S., BENNANI, M., RAUCOULES, D., CARNEC, C. and FERRETTI,
A., 2005, Detection of mining related ground instabilities using the permanent scatterers
technique – a case study in the east of France. International Journal of Remote Sensing,
26, pp. 201–207.
COLESANTI, C. and WASOWSKI, J., 2006, Investigating landslides with space-borne Synthetic
Aperture Radar (SAR) interferometry. Engineering Geology, 88, pp. 173–199.
COTECCHIA, V., 1986, Earthquake-prone environments. In Slope Stability, M.G. Anderson and
K.S. Richards (Eds.), pp. 287–329 (Chichester: John Wiley Sons).
COTECCHIA, V. and DEL PRETE, M., 1984, The reactivation of large flows in the parts of
Southern Italy affected by the earthquake of November 1980, with reference to the
evolutive mechanism. In IV International Symposium on Landslides, September 1984,
Toronto, ON, Canada (Rotterdam: Baalkema), pp. 33–38.
COTECCHIA, V., LENTI, V., SALVEMINI, A. and SPILOTRO, G., 1986, Reactivation of the
large “Buoninventre” slide by the Irpinia earthquake of 23 November 1980. Geologia
Applicata e Idrogeologia, 21, pp. 217–253.
ESU, F., 1977, Behaviour of slopes in structurally complex formations. In International
Symposium on the Geotechnics of Structurally Complex Formations, Capri, Italy (Rome:
Associazione Geotecnica Italiana), pp. 292–304.
FERRETTI, A., PRATI, C. and ROCCA, F., 2000, Nonlinear subsidence rate estimation using per-
manent scatterers in differential SAR interferometry. IEEE Transactions on Geoscience
and Remote Sensing, 38, pp. 2202–2212.
FERRETTI, A., PRATI, C. and ROCCA, F., 2001, Permanent scatterers in SAR interferometry.
IEEE Transactions on Geoscience and Remote Sensing, 39, pp. 8–20.
FRANCESCHETTI, G. and LANARI, R., 1999, Synthetic Aperture Radar Processing (New York:
CRC Press).
FRUNEAU, B., ACHACHE, J. and DELACOURT, C., 1996, Observation and modelling of
the Saint-Etienne-de-Tinée landslide using SAR interferometry. Tectonophysics, 265,
pp. 181–190.
GOLDSTEIN, R.M., ENGELHARDT, H., KAMB, B. and FROLICH, R.M., 1993, Satellite radar
interferometry for monitoring ice sheet motion – application to an Antarctic ice stream.
Science, 262, pp. 1525–1530.
HANSSEN, R., 2001, Radar Interferometry: Data Interpretation and Error Analysis (Dordrecht:
Kluwer Academic Publishers).
HILLEY, G.E., BURGMANN, R., FERRETTI, A., NOVALI, F. and ROCCA, F., 2004,
Dynamics of slow-moving landslides from permanent scatterer analysis. Science, 304,
pp. 1952–1955.
HUTCHINSON, J.N., 1983, Methods of locating slip surfaces in landslides. Bulletin of the
Association of Engineering Geologists, 20, pp. 235–252.
HUTCHINSON, J.N. and DEL PRETE, M., 1985, Landslides at Calitri, Southern Appennines,
re-activated by the earthquake of 23 November 1980. Geologia Applicata e Idrogeologia,
20, pp. 9–38.
LANARI, R., BERARDINO, P., BORGSTRÖMB, S., DEL GAUDIO, C., DE MARTINO, P., FORNARO,
G., GUARINO, S., RICCIARDI, G.P., SANSOSTI, E. and LUNDGREN, P., 2004a, The use of
IFSAR and classical geodetic techniques for caldera unrest episodes: application to the
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

Campi Flegrei uplift event of 2000. Journal of Volcanology and Geothermal Research,
133, pp. 247–260.
LANARI, R., CASU, F., MANZO, M., ZENI, G., BERARDINO, P., MANUNTA, M. and PEPE, A.,
2007, An overview of the Small BAseline Subset algorithm: a DInSAR technique for
surface deformation analysis. Pure Applied Geophysics, 164, pp. 637–661.
LANARI, R., MORA, O., MANUNTA, M., MALLORQUI, J.J., BERARDINO, P. and SANSOSTI, E.,
2004b, A small baseline approach for investigating deformations on full resolution dif-
ferential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing,
42, pp. 1377–1386.
MASSONNET, D., BRIOLE, P. and ARNAUD, A., 1995, Deflation of Mount Etna monitored by
space borne radar interferometry. Nature, 375, pp. 567–570.
MASSONNET, D., ROSSI, M., CARMONA, C., ADRAGNA, F., PELTZER, G., FEIGL, K. and
RABAUTE, T., 1993, The displacement field of the Landers earthquake mapped by radar
interferometry. Nature, 364, pp. 138–142.
MEISINA, C., ZUCCA, F., NOTTI, D., COLOMBO, A., CUCCHI, A., SAVIO, G., GIANNICO, C.
and BIANCHI, M., 2008, Geological interpretation of PSInSAR data at regional scale.
Sensors, 8, pp. 7469–7492.
MIKKELSEN, P.E., 1996, Field instrumentation. In Landslides. Investigation and Mitigation.
Transportation Research Board, Special Report Series, A.K. Turner and R.L. Schuster
(Eds.), pp. 279–316 (Washington, DC: National Research Council).
NAGLER, T., ROTT, H. and KAMELGER, A., 2002, Analysis of landslides in Alpine areas by
means of SAR interferometry. In IEEE International Geoscience and Remote Sensing
Symposium, 24–28 June 2002, Toronto, ON, Canada, pp. 198–200.
PARISE, M. and WASOWSKI, J., 1996, Aspetti evolutivi e stato attuale della franosità nei din-
torni dell’abitato di Calitri. In International Conference on Prevention of Hydrogeological
Hazards: The Role of Scientific Research, 5–7 November 1996, Alba, Italy (Turin:
CNR-Turin), pp. 135–144.
PARISE, M. and WASOWSKI, J., 1999, Landslide activity maps for landslide hazard evaluation:
three case studies from Southern Italy. Natural Hazards, 20, pp. 159–183.
PONCOS, V., 2008, InSAR Processing: Processing Methodology, Analysis Procedures and Results.
The Permanent Scatterers Techniques Applied to Corner Reflectors. InSAR Monitoring
of Active Geohazards Sites in Canada GRIP Annual Report, Canadian Centre for
Remote Sensing, Ottawa, ON, Canada, pp. 19–37.
RAUCOULES, D., MAISONS, C., CARNEC, C., LE MOUELIC, S., KING, C. and HOSFORD, S., 2003,
Monitoring of slow ground deformation by ERS radar interferometry on the Vauvert
salt mine (France). Comparison with ground-based measurement. Remote Sensing of
Environment, 88, pp. 468–478.
ROTT, H. and NAGLER, T., 2006, The contribution of radar interferometry to the assessment of
landslide hazards. Advances in Space Research, 37, pp. 710–719.
SINGHROY, V. and MOLCH, K., 2004, Geological case studies related to RADARSAT-2.
Canadian Journal of Remote Sensing, 30, pp. 893–902.
SLEJKO, D., PERUZZA, L. and REBEZ, A., 1998, Seismic hazard maps of Italy. Annali di
Geofisica, 41, pp. 183–214.
TRE (TELERILEVAMENTO EUROPA), 2006, Progetto Di Elaborazione Dati SAR Con Tecnica PS,
Rapporto finale, Regione Campania.
TURNER, A.K. and MCGUFFEY, V.C., 1996, Organization of investigation process. In
Landslides–Investigation and Mitigation: Transportation Research Board, Special Report
Series, A.K. Turner and R.L. Schuster (Eds.), pp. 121–128 (Washington, DC: National
Research Council).
USAI, S., 2003, A least squares database approach for SAR interferometric data. IEEE
Transactions on Geoscience and Remote Sensing, 41, pp. 753–760.
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

VAN WESTEN, C.J., CASTELLANOS, E. and KURIAKOSE, S.L., 2008, Spatial data for landslide
susceptibility, hazard, and vulnerability assessment: an overview. Engineering Geology,
102, pp. 112–131.
WIECZOREK, G.F. and SNYDER, J.B., 2009, Monitoring slope movements. In Geological
Monitoring, R. Young and L. Norby (Eds.), pp. 245–271 (Boulder, CO: Geological
Society of America).
WP/WLI, 1993, A suggested method for describing the activity of a landslide. Bulletin of the
International Association of Engineering Geology, 47, pp. 53–57.
Downloaded
by
[Northeastern
University]
at
19:55
05
January
2015

10.1080@01431161.2011.630331.pdf

Recommended

Recommended

More Related Content

Similar to 10.1080@01431161.2011.630331.pdf

Similar to 10.1080@01431161.2011.630331.pdf (20)

Recently uploaded

Recently uploaded (20)

10.1080@01431161.2011.630331.pdf