Landslide monitoring by using ground-based SAR interferometry:

an example of application to the Tessina landslide in Italy

Dario Tarchi a, Nicola Casagli b,*, Riccardo Fanti b, David D. Leva a, Guido Luzi c,Alessandro Pasuto d, Massimiliano Pieraccini c, Sandro Silvano d

aInstitute for the Protection and Security of the Citizen (IPSC), Humanitarian Security Unit (HSU), Ispra, ItalybEarth Sciences Department, University of Firenze, Florence, Italy

cDepartment of Electronics and Telecommunications, University of Firenze, Florence, ItalydNational Research Council, Institute for Hydro-geological Protection, Padua, Italy

Received 7 January 2002; received in revised form 29 May 2002; accepted 8 July 2002

Abstract

An innovative technique, based on radar interferometry and implemented using ground-based instrumentation, has been

applied for monitoring the Tessina landslide (Italy, Belluno). The technique has allowed us to derive multitemporal surface

deformation maps of the entire depletion zone of the landslide with a high spatial resolution and accuracy. The portable device

used in this application is known as Linear SAR (LISA), and it is able to provide measurements at 17 GHz with a synthetic

aperture of up to 2.8 m. The results have been validated by comparing the recorded pixel displacements with independent

measurements carried out by a motorized theodolite and Electronic Distance Meter (EDM) on two benchmarks.

D 2002 Elsevier Science B.V. All rights reserved.

Keywords: Landslide; Remote sensing; Monitoring; Radar

1. Introduction

In many parts of the world, landslides affect urban

areas or anthropogenic activities and because of the

difficulties in putting into effect countermeasures in

terms of stabilization works, such situation frequently

determines a forced ‘‘cohabitation’’ of people with risk

conditions. In order to keep an adequate safety level in

those situations where human life or relevant property

and infrastructures are exposed, an optimal risk man-

agement requires warning systems based on the real-

time acquisition of reliable data resulting from perma-

nent monitoring instrumentation. Especially during

alarm events, in difficult operational conditions, the

real-time availability of data is fundamental to predict

the short-term evolution of movements and, conse-

quently, to define risk scenarios. Among the parameters

that can define the behaviour of a mass movement and

forecast its short-term evolution, the superficial mor-

phological changes of the detachment and accumula-

tion areas are particularly significant. Generally,

ground surface monitoring techniques provide infor-

mation on a determined number of points within the

landslide area, both in the cases of geotechnical mon-

itoring (clinometers, extensometers, distometers, etc.)

and of GPS or conventional topographic survey (Kea-

0013-7952/02/$ - see front matter D 2002 Elsevier Science B.V. All rights reserved.

PII: S0013 -7952 (02 )00196 -5

* Corresponding author. Fax: +39-55-275-6296.

E-mail address: nicola.casagli@unifi.it (N. Casagli).

www.elsevier.com/locate/enggeo

Engineering Geology 68 (2003) 15–30

ton and DeGraff, 1996; Mikkelsen, 1996; Allaway et

al., 1998; Coe et al., 2000; Gili et al., 2000; Angeli et al.,

2000).

Even if single-point data are accurate and taken

particularly in significant areas (landslide crown,

depletion zone, accumulation zone, etc.), they cannot

be considered inferable to the whole landslide area.

This is particularly important in large-size landslides

or complex slope movements, which are characterized

by different movement patterns. To get rid of such a

strongly limiting characteristic, the topographic and/or

instrumental measurements are usually carried out on

extensive and complex monitoring networks. Never-

theless, these conventional monitoring techniques

cannot give a detailed spatially extensive information

and cannot be employed for those landslide sectors

which are at high risk or not accessible.

The synthetic aperture radar (SAR) technology,

implemented through either spaceborne or ground-

based sensors, has demonstrated its capability in the

assessment of ground surface displacement fields over

wide areas (Gabriel et al., 1989;Massonnet et al., 1993,

1995; Zebker et al., 1994; Carnec et al., 1995). In

particular, it allows the detection, with high precision,

of the displacement components along the sensor–

target line of sight (LOS). The potentiality of ground-

based SAR interferometry for monitoring landslide

displacements has been explored by the authors in the

framework of a research program funded by the Italian

Space Agency (ASI) and the National Research Coun-

cil (CNR). In order to test the technique in the field, a

number of experimental campaigns have been carried

out on a variety of ground movements with different

kinematics and materials involved. A first application

on the Ruinon rock slide (Italy, Valtellina) has been

published by the authors (Atzeni et al., 2001, in press;

Tarchi et al., in preparation). This paper presents the

results of a ground-based radar campaign carried out

between the 25th of September and the 13th of October

2000 on the Tessina earth slide in the Italian Eastern

Alps.

2. Ground-based differential SAR interferometry

The proposed technique provides a remotely

sensed measurement of ground displacements. It is

able to supply a deformation field of the ground

portion in the field of view of the measurement tool,

without the necessity of positioning targets on the

ground and without any physical contact with the

slope (Tarchi et al., 1997). This technique is based on

SAR (Curlander and McDonough, 1991) and on

interferometric techniques (InSAR), originally devel-

oped for earth observation from satellites (Zebker and

Goldstein, 1986). InSAR is based on the quantitative

comparison of the phase information between two

radar acquisitions of the same scenario. Using a pair

of complex SAR images, where the former and the

latter are referred to as master (m) and slave (s)

images, respectively, an interferogram (I) is formed

according to the following relationship:

Iðk; lÞ ¼ mðk; lÞsðk; lÞ* ð1Þ

where * indicates the conjugate.

In the general case, which is the usual one for

satellite observations, the two acquisitions are taken

from slightly different positions and in different

moments of time, the phase of each pixel of the

interferogram, referred to as interferometric phase,

contains different contributions as follows:. Topographic effect. This contribution relates to

the height of the portion of terrain corresponding to a

pixel in the interferogram. The InSAR application

aimed to derive a Digital Elevation Model (DEM) of

the imaged area exploits this effect. Such an effect

originates from the slightly different position of

acquisition of the two images. Consequently, it dis-

appears for image pairs taken exactly from the same

position (zero baseline).. Dielectric effect. This contribution relates to the

phase shift induced both by the propagation through

the atmosphere and by the dielectric properties of the

reflecting targets. Usual assumption is that dielectric

characteristics are similar for both acquisitions and

have no impact on the interferometric phase. This

cannot be assumed to have general validity and

deserves a specific analysis taking into account the

relevant conditions during each acquisition and in the

time span between them.. Displacements of the mapped terrain. The phase of

each pixel of the single SAR image contains informa-

tion about the absolute distance along the line of sight

(LOS) of the system between the sensor and the portion

of terrain corresponding to the pixel. When terrain

displacements occur in the time span between the pair

D. Tarchi et al. / Engineering Geology 68 (2003) 15–3016

of SAR acquisitions, the interferometric phase will

vary accordingly. The InSAR application aimed at

retrieving displacements patterns on the imaged area

exploits this effect. Obviously, such an effect does not

appear if the pair of images is acquired at the same time.

Assuming a negligible or moderate impact of

dielectric effects on the interferometric phase, the

possibility to discriminate between the two remaining

contributions relies on an appropriate choice of the

acquisition parameters in order to cancel out one of

the effects and to retain the other one. The ideal set-up

for the derivation of DEM needs the acquisition of

both images from different positions but during the

same satellite pass, as recently done during the Shuttle

Radar Topography Mission (SRTM) NASA mission.

On the other hand, in order to derive displacement

patterns, the acquisitions need to be taken at different

moments of time but exactly repeating the same orbit

(zero baseline). In practice, this is hardly ever the case

and two different methods have been proposed in

order to obtain a ‘‘topography-free’’ interferogram

whose phase can be directly related to terrain move-

ments. The former, referred to as three-pass interfer-

ometry (Gabriel et al., 1989; Zebker et al., 1994) uses

a third image. The latter, referred to as DEM extrac-

tion method (Rosen et al., 2000), generates a synthetic

interferogram by using an existing DEM of the

observed area and the precise knowledge of the

trajectories (orbital parameters) of the sensor during

the acquisition of the paired images. This specific

application of InSAR is usually referred to as Differ-

ential InSAR (DInSAR).

On the other hand, with a ground-based platform,

the ideal condition of zero baseline can usually be

achieved and a couple of images are sufficient to

generate a topography-free interferogram and, finally,

to derive information on displacements. For the sake

of simplicity, we will refer to this specific application

of InSAR using ground-based systems as Ground-

Based Differential InSAR (GB-DInSAR).

Independently, both of the platform and of the

specific method, whenever the application of GB-

DInSAR is the monitoring of movement, the final

product can be referred to as a displacement map

having the following general characteristics:

� measured displacements refer to the component of

the real displacement along the line of sight of the

SAR system and to the time span between the

acquisitions of the SAR images;� spatial resolutions equal to those of the original

SAR images; the resolution could degrade if spatial

averaging is applied at some step of the processing

chain.

Although several examples of application of DIn-

SAR using spaceborne data to landslides are available

in the scientific literature (Achache et al., 1995; Prati

et al., 1995; Fruneau et al., 1996; Carnec et al., 1996;

Singhroy et al., 1998; Rott and Siegel, 1999; Rott et

al., 1999; Kimura and Yamaguchi, 2000; Singhroy

and Mattar, 2000; Refice et al., 2000; Ferretti et al.,

2001), the sensors actually available pose a number of

challenges for its operational use.

The main limits, due to both satellite parameters

and intrinsic constraints of the DInSAR technique, are

discussed by Wasowski and Gostelow (1999) and can

be summarized as follows:

(a) Acquisition geometry: the typical incidence angle

and the orbital trajectory allow an acceptable

sensitivity to vertical and across-azimuth (approx-

imately east–west) displacement components only;

(b) Geometrical distortions: SAR images are intrinsi-

cally affected by prospective deformations (fore-

shortening, layover, shadowing) strongly limiting

the observation of landslides on steep slopes or

into narrow valleys; these limitations can only be

partially removed by processing both ascending

and descending data acquisitions;

(c) Spatial resolution: the resolutions of available

satellites now range between 15 and 30 m;

RADARSAT is able to acquire 10� 9 m data

but only on demand; in any case, these resolutions

are suitable only for large-scale slope movements;

(d) Revisiting time: 35 days for ERS, 24 for

RADARSAT, 44 for JERS; in any case, the

temporal coverage is not suitable for monitoring

high deformation rates;

(e) Temporal decorrelation: changes in the observed

area usually degrade the quality of the interfero-

gram and can prevent the application of the

technique. This is usually the case of densely

vegetated areas where sliding phenomena often

occur; in general, the loss of coherence is related

to the time span between the acquisitions.

D. Tarchi et al. / Engineering Geology 68 (2003) 15–30 17

The use of a ground-based radar allows us to

overcome most of the limits linked to spaceborne

interferometry to overcome and provide the necessary

flexibility in order to accomplish the extreme varia-

bility, in terms of size, movement mechanism, dis-

placement rate, water content, state and distribution of

activity, which intrinsically characterizes slope pro-

cesses. In fact, such an approach makes possible to

change the observation parameters (such as the dis-

tance from the target, the frequency of observation,

the length of synthetic aperture, the angle of inci-

dence, the revisiting time) in order to adapt them to

every particular case.

On the other hand, a ground-based system suffers

from different limitations, such as the possibility to

cover only areas of limited extension (about 100,000

m2 from a mean distance of 1 km) and the necessity of

a location having a suitable visibility of the area under

test. In addition, due to the fact that the system should

be fixed in a stable position during the acquisition and

to the limited extension of the synthetic aperture, the

spatial resolution in azimuth depends both on the

distance from the sensor and on the lateral displace-

ment with respect to the sensor location. It should also

be noted that the obtained azimuth resolution is far

from being the optimum (i.e., the one obtained with a

synthetic aperture equals to the footprint of the anten-

nas at near range). However, although the obtained

azimuth resolution is typically a couple of order of

magnitude lower than the optimal one, it is usually

enough for monitoring landslide movements.

3. The Tessina landslide

The Tessina landslide, located in the NE Italian

Alps near the city of Belluno, was first triggered in

October 1960 (Pasuto et al., 1992; Angeli et al., 1994,

2000; Mantovani et al., 2000a,b). It is a complex

landslide with a source area affected by roto-transla-

tional slides which develop downhill into a mud flow

through a steep channel. The landslide developed in

the Tessina valley between altitudes of 1220 and 625

m a.s.l., with a total longitudinal extension of nearly 3

km, a maximum width of about 500 m and a total

volume of about 7 million m3. The mud flow

skimmed over the village of Funes and stretched

downhill as far as the village of Lamosano (Fig. 1).

The landslide involves the Flysch Formation

(Lower Eocene), which consists of alternated marly-

argillaceous and calcarenite layers, with a total thick-

ness ranging from about 1000 to 1200 m. This

formation makes up the impermeable bedrock of the

entire sliding area and crops out at the foot of Mt.

Teverone, which is mainly made up of Fadalto Lime-

stones (Upper Cretaceous).

During the 1960s, several reactivations involving

about 5 million m3 of material, caused the filling of

the Tessina valley. These movements seriously endan-

gered the village of Funes, which is situated on a steep

ridge originally quite high above the river bed, but

now nearly at the same level as the mud flow.

The April 1992 reactivation of the landslide posed

a high risk to the villages of Lamosano and Funes,

resulting in their temporary evacuation. The move-

ment initiated in the upper part of the depletion zone

as a rotational slide, with a 20- to 30-m-deep failure

surface, affecting also the flysch bedrock and involv-

ing about 1 million m3 of rock and earth. The land-

slide movement continued until June 1992, causing

the mobilization of a total volume of about 2 million

m3. The displaced material initially reached the upper

accumulation zone (Fig. 1) and then was channeled,

giving rise to a series of earth flows which converged

into the main mud flow in the lower part of the slope.

Following this major landslide reactivation, the

Italian Ministry for Civil Protection assigned funds

for works to be carried out on a short and medium-

term basis, in order to safeguard residential areas, as

well as for the installation of a permanent monitoring

and an early-warning system. The system, established

by the National Research Council (Angeli et al.,

1994), consists of an arrangement of sensors and

measuring instruments, including two multiple-base

wire extensometers, a topographic system with an

automatic landmark detector for measuring the surface

movements of 30 benchmarks (Figs. 1 and 2). Two

alarm units, one comprising three directional bars and

an ultrasonic echometer, the other with two directional

bars and an echometer, were installed on the body of

the mud flow, uphill the villages of Funes and

Lamosano. Three videocameras were also installed

aimed at recording the slide movements in the areas

considered as the most critical, i.e., the upper accu-

mulation and the two areas uphill from Funes and

Lamosano. The control centre, situated inside the

D. Tarchi et al. / Engineering Geology 68 (2003) 15–3018

Fig. 1. Plan of the Tessina landslide showing the installed monitoring systems and longitudinal geological section highlighting the main

geological units. Legend of the section: (1) main flow body; (2) rotational slides; (3) scree slope; (4) folded and fractured flysch; (5) Flysch

Formation (Lower Eocene); (6) Fadalto Limestone (Upper Cretaceous) (after Angeli et al., 2000).

D. Tarchi et al. / Engineering Geology 68 (2003) 15–30 19

Town Hall of Chies d’Alpago in Lamosano, received

data from the peripheral stations to which the sensors

are connected. The system is currently operating for

early-warning purposes, and it is associated to a Civil

Protection plan, which includes the evacuation of the

population from the residential areas in case of danger.

The depletion zone of the landslide was chosen as

target for radar observations. This area is constantly

active, and it is characterized by the presence of three

main scarps (Fig. 2). Global landslide reactivations in

the past have always been induced by mass move-

ments in this area; for this reason, its control is of

crucial importance in the framework of the early-

warning system. Fig. 2 shows, through different

symbols, the average displacement rates recorded at

30 benchmarks during the last year. The most active

sector, with displacements of over 1 m/year, is

located within the main scarp, where the material

slides intermittently towards the upper accumulation

zone (Fig. 1). The highest velocities (up to several

decimeters per hour) have been recorded in corre-

spondence of the superficial earth flows within this

sector.

4. Materials, methods and measurement campaign

The ground-based SAR apparatus used in this

application is a portable device, called Linear SAR

(LISA) designed and implemented by the Joint

Research Centre (Rudolf et al., 1999; Tarchi et al.,

1997, 1999, 2000a,b). The LISA system is composed

of the following main components (Fig. 3):

� a microwave system, constituted by a continuous-

wave stepped-frequency (CW-SF) radar, based on a

Fig. 2. Plan of the depletion zone showing the landslide main scarps, the location of the radar and of the topographic system, the position of the

benchmarks and their average rate of movement over the last year.

D. Tarchi et al. / Engineering Geology 68 (2003) 15–3020

network analyzer (NWA) with a signal source

between 30 kHz to 6 GHz; a coherent conversion

module makes it possible to extend the operating

frequencies up to 17 GHz;� a mechanical component formed by a straight rail

2.8 m long, with a motorized sled hosting the radar

antennas, whose movement is controlled via a

linear positioner.

The measurement campaign on the Tessina land-

slide was carried out between the 25th of September

and the 13th of October 2000. The instrumentation

was installed at an elevation of 997.3 m a.s.l., in a

stable area on the opposite slope in front of the

depletion zone, which was completely visible at an

average distance of 500 m (Fig. 2).

The arrangement of the instrumentation in the field

is shown in Fig. 4. The rail was mounted on a

concrete wall, and the electronic apparatuses for

acquisition and visualization were placed in an exist-

ing building hosting the topographic monitoring sys-

tem described in the previous section. The instrument

employed in these measurements has been designed in

order to make the installation as easy as possible,

taking into account the typical conditions of operation

for the proposed application. The installation of the

system, including preliminary calibration measure-

ments, typically requires few hours.

Fig. 5 shows the scenario observed by the radar

instrument, corresponding to the upper part of the

landslide (zone of depletion and part of the upper

accumulation zone). Each white dot in the figure

Fig. 4. Field set-up of the instrumentation in the test site and detail of the motorized sled with the antennas. The topographic station has been

used for validating radar measures on a number of selected benchmarks.

Fig. 3. Technical scheme of the LISA system. Network Analyzer

(NWA); transmitting antenna (Tx); receiving antenna (Rx).

D. Tarchi et al. / Engineering Geology 68 (2003) 15–30 21

indicates a benchmark, whose position is measured,

with millimetric accuracy, every 4 h, by the motorized

theodolite and the Electronic Distance Meter (EDM)

of the topographic system.

Radar observations were carried out in the fre-

quency band 16.70–16.78 GHz with steps of 100 kHz

and VV polarization, for a total of 801 frequency

points. The transmitted power was 25 dBm (approx-

imately 300 mW). The antenna synthesis was ob-

tained by moving the antenna’s sled, at azimuth steps

of 6 mm along a 2.4-m synthetic aperture, for a total

of 401 azimuth points (Table 1).

Under these operational conditions the spatial

resolution in range is approximately 2 m. Azimuth

resolution is not constant over the area imaged, as it

varies approximately between 0.5 and 3.75 m with a

value of about 2 m at the centre. The theoretical limit

for the system precision in LOS displacement detec-

tion is about 0.5 mm (corresponding to a phase shift

of 20j at the operating frequencies).

Data acquisitions were exactly repeated from the

same position, at intervals of about 14 min. In all, a

total of approximately 400 raw data sets, arranged in a

number of continuous sequences, were collected.

The data processing chain includes different steps.

First, each set of raw data is calibrated, using a

single reference calibration procedure derived from

measurements at a fixed point (Wiesbeck and Kahny,

1991). Then calibrated data are focused using a time

domain SAR processor specially tailored for such

application (Fortuny and Sieber, 1994). This algo-

rithm has been developed to approach efficiently the

special case where the azimuth extent of the desired

image is much larger than the synthetic aperture. In

this situation, memory requirements may become too

demanding, thus preventing the use of other SAR

Table 1

Summary of the main operational parameters of the radar measure-

ment campaign

Frequency band 16.70–16.78 GHz

Frequency step 100 kHz

Frequency points 801

Aperture 2.40 m

Azimuth step 6 mm

Azimuth points 401

Polarization VV

Transmitted power (approximate) 25 dBm

Target distance (average) 500 m

Spatial resolution (range) 2 m

Spatial resolution (cross range) 2 m

Measuring time per image ca. 14 min

Total time interval 15 days

Number of collected images ca. 400

Fig. 5. Photo of the target scene (depletion zone of the Tessina landslide) with the position of the optical benchmarks. The two benchmarks

labeled 610 and 611 are included in the zone affected by displacements during the radar campaign.

D. Tarchi et al. / Engineering Geology 68 (2003) 15–3022

focusing algorithms, such as range migration and

chirp scaling algorithms (Carrara et al., 1995). In

addition, the focusing can be performed on an

arbitrary set of points, with a negligible impact on

the computational time. Such a feature allows to

easily incorporate the information on the local top-

ography. Resulting images can be directly referred to

an existing DEM of the area under test facilitating

the analysis of the results. In this way also, the

comparison with ground truth data is simplified

because a defined point in the scenario can be easily

located in the image with a similar accuracy to that

of the available DEM. The grid of points has to be

chosen in order to guarantee an appropriate over-

sampling.

Finally, from each pair of images an interferogram

is generated according to Eq. (1). An additional step is

also applied in order to mask out pixels, where the

phase measurement cannot be considered reliable.

This has been accomplished through the complex

coherence, defined according to the following rela-

tionship:

c ¼ E½ms*�ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiE½AmA2�E½AsA2�

q ð2Þ

where m is the master image, s the slave image, * and

E[#] indicates the conjugate and the mathematical

expectation, respectively.

For a given set of images, the first one is identified

as the master and a sequence of coherence maps is

generated as the slave varies along the images se-

quence. The temporal evolution of the coherence is

then analysed in order to retain only the pixels whose

coherence is always above a specified threshold.

5. Discussion of results and validation

A radar power image of the target scene, projected

on the DEM, is shown in Fig. 6 and can be compared

with the photo of Fig. 5. It is possible to appreciate

how the highest reflectivity (light colors) comes from

the bare or scarcely vegetated soil (e.g., grass, low

shrubs). The boundaries of those zones with a high

reflectivity closely correspond to the vegetation limit.

Densely vegetated areas, with trees or dense shrubs,

have a low reflectivity and are represented with dark

colors in the image.

Due to the short time interval between acquisi-

tions (14 min), the variation of the ground dielectric

constants can be neglected and the phase difference,

Dw, is translated into ground displacements in the

LOS direction, Dr, according to the following rela-

tionship:

Dr ¼ k4p

Dw ð3Þ

When particular atmospheric events occur during this

interval, data are carefully checked and eventually

discarded when these effects are not negligible.

A sequence of eight interferograms, covering a

time span of 2 and 45 min (between 0000 and 0245

h GMT+1 of 05/10/2000) is shown in Figs. 7 and 8.

The interferograms refer to the same master image.

They have been processed on the DEM and areas of

low coherence masked out. In order to facilitate their

interpretation, the projection onto a horizontal plane is

displayed.

The color scale of the interferograms expresses the

phase difference converted to millimeters according to

Eq. (3), which in turn directly corresponds to ground

movements in the LOS direction. Negative values

indicate a distance reduction, i.e., a movement

towards the observer. The fact that only the compo-

nent of the displacement along the LOS can be

measured deserves additional comments. The geo-

metrical arrangement of the GB-InSAR is very differ-

ent from that of spaceborne observations, and the

orientation of the LOS is strongly dependent on the

local topography. On the other hand, when a detailed

DEM is available, the LOS orientation with respect to

a specified direction, for instance, the local slope

direction, can be precisely computed. The angles

between the LOS and the local slope direction have

been calculated for every pixel of the whole image.

Moreover, the topographic system provides an inde-

pendent assessment of the movement directions of the

benchmarks. The angles between these directions and

the local LOS direction have been assessed for every

benchmark; the results show that at least the 60% of

the movement is along the LOS.

It has to be pointed out that the phase values have

not been unwrapped. Deformation values are, there-

D. Tarchi et al. / Engineering Geology 68 (2003) 15–30 23

fore, affected by the intrinsic ambiguity of phase

measurements: if ground displacement towards the

observer exceeds the end of the scale, i.e., � 0.25k=� 4.5 mm, the successive values will restart from the

opposite scale end, i.e., + 0.25k = 4.5 mm. After a

ground displacement of 0.5k = 9 mm, the image pixels

are in phase (value = 0) again.

The typical effect of phase wrapping is evident just

from the first interferogram (Fig. 7), where a fringe

starts to form. Fringes are completely developed in the

last images showing the occurrence of several phase

cycles and their irregular pattern derives from the

complex landslide movement.

The circular concentric lines in the interferograms

are artifacts, probably the sidelobes of the direct

coupling between the transmitting and the receiving

antennas of the system.

A close inspection of the interferogram sequence of

Figs. 7 and 8 show a complex displacement field, with

two evident sectors in motion located beneath the

landslide main scarp. Both sectors have an elongated

shape, and the eastern one close to the left landslide

flank progressively expands upwards throughout the

sequence. This sequence allows the area of maximum

displacement to be identified within the western sector

(near the right landslide flank), showing a peak rate of

about 8.5 mm over 14 min and then of about 36 mm/h

approximately. This displacement pattern is clearly

related to the propagation and retrogression of super-

ficial earth flows caused by rainfall that occurred

during the measurement campaign (10.6 mm of rain

from 0900 h of 04/10/2000 to 0900 h of 05/10/2000,

after 99.6 mm fallen in the preceding 4 days). Com-

paring consecutive interferograms step by step, it is

Fig. 6. Radar power image of the target scene projected on the digital elevation model of the slope. Power P is expressed in decibels (dBm),

which are related to milliWatts (mW) through the equation P (dBm) = 10log10[ P (mW)/(1 mW)]. The image is georeferenced and represented in

a local coordinate system with the origin placed in the central point of the radar image.

D. Tarchi et al. / Engineering Geology 68 (2003) 15–3024

Fig. 7. Sequence of interferograms between the 00:00 and the 02:27 of the 05/10/2000. The time elapsed from the start of the sequence

(reference image) is shown on the topright of each interferogram.

D. Tarchi et al. / Engineering Geology 68 (2003) 15–30 25

possible to follow the landslide evolution in detail. The

distribution of activity of the landslide maintains the

same displacement pattern throughout the sequence,

showing constant displacement rates over the inves-

tigated time span.

Only two benchmarks, labeled 610 and 611 in

Figs. 2 and 5, were positioned inside the sectors

which moved during the radar measurements. The

comparison between the results of radar and optical

measurements on benchmarks 610 and 611 are plotted

in Figs. 9 and 10, respectively. In both cases, we

located the pixel containing the benchmark, and we

considered the same pixel in the series of successive

interferograms, extracting and unwrapping the dis-

placement history of what is hosted in an individual

sampling cell. Due to the presence of time spans with

missing SAR acquisitions, optical data have been

utilized to correctly unwrap radar measurements.

The curves in Fig. 9 refers to the benchmark 610

and show a nearly constant displacement rate of about

Fig. 8. Last interferogram after 2 h and 45 min from the start of the sequence (02:45 h of 05/10/2000).

D. Tarchi et al. / Engineering Geology 68 (2003) 15–3026

11.7 mm/h over a total time interval of 48 h. The plot

shows a very close agreement between the two

independent techniques with a maximum discrepancy

lower than 3.0 mm.

Benchmark 611 (Fig. 10) turned out to be not clear,

being located in an area of quite low coherence. In

addition, the optical measurements are affected by a

systematic error probably due to daily temperature

effects. For this reason, the optical data have been in-

terpolated in Fig. 10 in order to make a direct compar-

ison with radar observation possible. The interpolated

data show a total displacement of 9 mm over 48 h,

Fig. 10. Cumulated displacements measured by the EDM at benchmark 611 compared with radar displacements in the corresponding pixel

(from the 12:02 h of 04/10/2000 and the 12:02 h of 06/10/2000, GMT+ 1).

Fig. 9. Cumulated displacements measured by the EDM at benchmark 610 compared with radar displacements in the corresponding pixel (from

the 12:02 h of 04/10/2000 and the 12:02 h of 06/10/2000, GMT+ 1).

D. Tarchi et al. / Engineering Geology 68 (2003) 15–30 27

corresponding to a mean velocity of 0.35 mm/h. Des-

pite this low displacement rate and the low coherence,

in this case also, the radar observations show a very

similar trend, with discrepancies limited within 3 mm.

Data concerning benchmark 610 have been also

exploited to further assess the accuracy of the radar

method. In particular, the standard deviation of the

difference between optical and radar measurements

has been calculated, after resampling on an appropri-

ate finer grid. The resulting value of 1.7 mm can be

considered the accuracy of the radar interferometry

method in the detection of surface displacements

under the adopted operational conditions.

6. Conclusions

The application of the ground-based SAR interfer-

ometry to the Tessina landslide has been implemented

by using portable field instrumentation that can be

installed in a very short time (few hours). Derived data

have shown the evolution of ground movements

almost over the entire depletion zone of the landslide.

Displacement rates up to about 1 m/day have been

assessed with a millimetric accuracy and a pixel

resolution of approximately 2� 2 m.

Through the continuous monitoring of slope move-

ments, the proposed technique has allowed us to

derive real-time maps showing the deformation field

of those landslide sectors characterized by a good

radar reflectivity and coherence (i.e., scarcely vege-

tated areas). These deformation maps represent a tool

for the interpretation of landslide kinematics and

short-term evolution, providing data for an accurate

analysis of temporal and spatial displacement fields.

This aspect is the main element of scientific interest in

terms of pure research on landslide kinematics

because, compared to conventional monitoring meth-

ods, the collected information allows a more direct

interpretation of the movement mechanism to be

established. Besides this general scientific interest,

the technique has very promising perspectives for

operational applications. Thanks to its noninvasive

character it is well suited for monitoring ‘‘sensitive’’

areas such as unstable urban zones and cultural

heritage sites, and it is particularly useful for monitor-

ing emergency situations due to the ease of its

installation and maintenance.

In particular, the tests carried out on the Tessina

landslide provide an operational comparison between

the ground-based interferometry and a traditional topo-

graphic system, showing that the precision of both

techniques is almost the same. The proposed technique

presents, however, a series of major advantages:

(a) it is a completely remote sensing method and it

does not need benchmarks to be installed over the

target area;

(b) it is more robust because it does not seem to be

influenced by daily temperature disturbances

affecting the electronic distance meter;

(c) it provides a really distributed information over

large landslide sectors; and

(d) its cost and time of installation are comparable to

those of an automatic topographic system.

Further applications of ground-based radars, which

will be explored in the future, concern the possibility

of a remote sensing production of high-resolution

digital terrain models, as currently done by space-

borne SAR interferometry, and the determination of

the soil moisture, by combing information on SAR

reflectivity and coherence to obtain an interferometric

signature of the terrain.

Acknowledgements

Research on the applicability of ground-based SAR

for landslide monitoring is funded by the Italian Space

Agency (ASI) and by the National Research Council

Group for Hydro-Geological Disaster Prevention

(CNR–GNDCI) supported by the Department of

Civil Protection of the Italian Government. In

particular, this activity is part of the ASI Programme

‘‘Remote-sensing techniques for monitoring land-

slide’’, AMHARAL Project ‘‘Analytical methods for

the definition of hazard areas for rainfall induced

landslides’’. Part of the activity has been developed

within the GNDCI–MOGEM Project ‘‘Monitoring

high risk slope movements’’. Both projects are

coordinated by Prof. Paolo Canuti at the University

of Firenze. We would like to thank Dr. Gareth Lewis

for revising the manuscript, Mr. Marco Basso for the

LISA installation and maintenance, and Mr. Paolo

Farina for the help in data processing and editing. We

D. Tarchi et al. / Engineering Geology 68 (2003) 15–3028

would also like to thank the anonymous referees for

their fruitful comments.

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