MULTITEMPORAL SAR COHERENCE ANALYSIS:

LAVA FLOW MONITORING CASE STUDY

Piero Boccardo1, Vittorio Gentile

2, Fabio Giulio Tonolo

3, Domenico Grandoni

2, Magdalena Vassileva

1

1

Politecnico di Torino – DIST – Torino, Italy 2

e-GEOS – Rome, Italy 3

ITHACA – Torino, Italy

ABSTRACT

This paper is focused on an operational case study

related to the adoption of a Multi-Temporal Coherence

(MTC) color composite approach to support monitoring

activities of volcanic eruption events. A specific case study

related to the volcanic eruption in Fogo Island (Cape

Verde), which started on late November 2014 will be

presented and discussed. A MTC analysis based on data

acquired by the COSMO-SkyMed SAR satellite constellation

of the Italian Space Agency is describe in details. The

thematic accuracy of the MTC based analysis is assessed

exploiting as comparison data lava extents derived by very

high resolution satellite imagery acquired in the same

period.

Index Terms— SAR, Multi-Temporal Coherence,

Volcanic eruption, Lava Extent

1. INTRODUCTION

Emergency Mapping can be defined as “creation of maps,

geo-information products and spatial analyses dedicated to

providing situational awareness emergency management

and immediate crisis information for response by means of

extraction of reference (pre-event) and crisis (post-event)

geographic information/data from satellite or aerial

imagery” [1]. Satellite remote sensing is nowadays a

common data source in the framework of emergency

mapping, since it allows to monitor large areas with limited

or no accessibility. Different type of remote sensing sensors,

platforms and techniques can be considered in this context:

the choice is mainly based on the event details and the end-

user requirements, e.g. the type of disaster to be mapped, the

approximate extent of the affected areas, the required level

of detail of the analysis and the need for monitoring the

event [2].

As far as volcanic eruption events are concerned, one of the

end users main requirement is to map the extent of the lava

flow on the ground as well as to monitor its evolution. Both

optical and SAR sensors can be exploited to fulfill the

aforementioned requirement, but the advantages offered by

optical imagery (mainly in terms of spatial/thematic

accuracies and of spectral resolution, including the

availability of thermal bands) is often limited by the

persistence of clouds or volcanic plumes over the area of

interest, making the whole or part of the scenes unusable for

mapping purposes. To cope with the aforementioned issues,

alternatives approaches based on radar SAR data can be

adopted, exploiting the well-known “all-weather” and “all-

light” capabilities of SAR sensors, which also allow to

increase the monitoring frequency exploiting satellite passes

during both the local morning and evening.

2. MULTITEMPORAL SAR COHERENCE FOR

LAVA FLOW MONITORING

As mentioned in the introduction section, one of the main

end user requirement related to volcanic eruption events is to

timely map the extent of the lava on the ground, to rapidly

assess the magnitude of the event, the potential damages to

infrastructures as well as to monitor the flow evolution.

Satellite-based emergency mapping generally exploits

optical imagery to map the lava extent, exploiting the

spectral (including thermal), spatial (up to 0.3m) and

temporal resolution of recent optical sensors. Unfortunately,

the possible presence of cloud coverage and the probable

persistence of volcanic plumes limit the suitability of optical

imagery, especially in terms of possibility to monitor the

event with as frequently as possible.

To cope with the aforementioned limitations, active

sensors can be successfully adopted, also leveraging on the

possibility to exploit acquisitions during the local afternoon,

increasing the revisit time (and the monitoring rate)

consequently.

A Multi-Temporal and Coherence (MTC) color

composite approach is here presented and discussed. MTC is

based on the combined SAR amplitude and coherence

analysis, being its general goal the detection of changes

between two (or more) multi-temporal datasets. SAR

interferometric coherence (InSAR coherence) is a cross-

correlation product derived from two SAR co-registered

2699978-1-4799-7929-5/15/$31.00 ©2015 IEEE IGARSS 2015

complex-valued (both intensity and phase components)

images, and it depicts changes in backscattering

characteristics at the spectrum of the radar wavelength [3].

In simple terms, the coherence map can be seen as the

comparison in amplitude and phase between the two signals

received during two consecutive acquisitions with the same

orbit pass, look direction, incidence angle and polarization

(i.e. interferometric acquisitions) over the same area. As a

result, the more the illuminated target is stable in time the

more the two signals will be similar (i.e. coherent).

Otherwise, if the target changes position, shape or

dimension, the two signals will not be coherent. The InSAR

coherence is also referred to as decorrelation and it estimates

the statistical differences between the signals in the two

interferometric SAR images.

Despite InSAR coherence analysis is mainly used to

assess the interferometric analysis feasibility, it can be

indirectly used as an independent layer to extract thematic

information relevant to ground features properties and their

temporal changes. In the context of lava flow mapping, areas

of low coherence values based on a suitable interferometric

pair (i.e. with a temporal baseline as low as possible) are

therefore potentially related to the presence of new areas

covered by lava. Unfortunately several additional

mechanisms can lead to decorrelation between two multi-

temporal scenes, such as systemic spatial decorrelation,

additive noise, temporal decorrelation and atmospheric

effects.

With the goal to better identify the decorrelation areas

related to the lava flow, the InSAR coherence image is

combined with the master (pre event) and slave (post event)

SAR detected amplitude images to create an ad-hoc color

composite, also referred to as Multi-Temporal Coherent

(MTC) color composite. Accordingly, MTC product is

generated combining into a single RGB image a) the SAR

detected amplitude of the master SAR acquisition (Red

channel), b) the SAR detected amplitude of the slave SAR

acquisition (Green channel) and c) the SAR interferometric

coherence (Blue channel). Therefore, it is possible to define

specific image interpretation keys depending on the relative

balance of the three different MTC components.

• changes in soil roughness

• changes in soil humidity

• harvesting of cultures

RedLowLowHigh/medium

• natural vegetation (e.g. grass)

• trees (identified with texture)YellowLowHighHigh

• water bodiesDark grey/blackLowLowLow

• fast growing vegetation (agriculture)

• changes in soil roughness

• changes in soil humidity

GreenLowHighLow

• flat/rough bare soil

• Sealed flat surfaces (roads, flat rooftop,

airport runway)

Dark/light blueHighLow/mediumLow/medium

• buildings (corners)

• Railways / power lines

• infrastructures

WhiteHighHighHigh

InterpretationExampleResulting

colorCoherence

2nd image

amplitude

1st image

amplitude

• changes in soil roughness

• changes in soil humidity

• harvesting of cultures

RedLowLowHigh/medium

• natural vegetation (e.g. grass)

• trees (identified with texture)YellowLowHighHigh

• water bodiesDark grey/blackLowLowLow

• fast growing vegetation (agriculture)

• changes in soil roughness

• changes in soil humidity

GreenLowHighLow

• flat/rough bare soil

• Sealed flat surfaces (roads, flat rooftop,

airport runway)

Dark/light blueHighLow/mediumLow/medium

• buildings (corners)

• Railways / power lines

• infrastructures

WhiteHighHighHigh

InterpretationExampleResulting

colorCoherence

2nd image

amplitude

1st image

amplitude

Figure 1 – General MTC interpretation guidelines [5]

A synthesis of the MTC interpretation guidelines is provided

in Figure 1, taking the following considerations into account: a short time interval between the two acquisitions is

required (1-16 days);

the roughness of bare soil influences the MTC

brightness;

texture and shapes of the targets have to be taken

into account.

3. FOGO ISLAND VOLCANO CASE STUDY

3.1. MTC Generation

The active volcano Pico do Fogo located in Fogo Island

in Cape Verde, lastly erupted on November, 23rd

2014. The

MCT technique described in section 2 was applied during

the monitoring activities related to the aforementioned

eruption, exploiting the availability of several pre and post

event COSMO-SkyMed interferometric acquisitions over the

area.

Figure 2 shows an example of MTC product generated

over Fogo Island combining a COSMO-SkyMed image post

event pair acquired in Spotlight-2 mode (Ground Sampling

Distance: 1m) in the date 26/11/2014 (master) and

04/12/2014 (slave) at 19:20 UTC. The relevant acquisition

parameters are:

Incidence angle: 32.75°;

Polarization: HH;

Side looking: Right;

Orbit pass: Descending.

The MTC image was produced using SARMAP

SARscape COTS software.

The main new areas covered by lava are located inside

the red box in Figure 3 and, as expected, those areas are

characterized by reddish and greenish tones, i.e. very low

values in the coherence image due to the occurred changes

on the ground caused by the lava flow as well as medium

values in either pre or post event SAR amplitude data, due to

the roughness of the lava surface compared to the terrain

surface conditions before the lava flow.

On the contrary, bright yellow pixels highlight areas with

low coherence but very high backscattering values both

before and after the event, presumably due to the presence of

vegetation or SAR artifacts (layover), while blueish areas

are related to low backscattering surfaces unchanged over

the considered time period.

Several tests have been conducted exploiting different

interferometric pair combinations among more than 10

images acquired in this time series, highlighting the need to

keep both the temporal and the orbital baseline as short as

possible to achieve meaningful results. As a consequence,

the interpretation of the MTC analysis results should

carefully take into account the temporal baseline of the

interferometric pair, with the goal to clearly inform the end

users if the identified areas are related to the whole extent of

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the lava flow since the beginning of the event or to new

areas covered by lava since the last monitoring activity.

Figure 2 – MTC product generated over Fogo Island

Figure 3 – Areas covered by lava (inside the red box)

Based on these observations and taking into account the

keys for MTC interpretation described above, two datasets

were extracted by means of photo-interpretation techniques,

specifically:

lava extent in the range from 2014/11/26 to

2014/12/04;

the lava extent as of present only in 2014/12/04.

The lava detected in the MTC time interval appears

yellowish, because of the increasing of the backscattering

from both the SAR images and the loss of the

interferometric coherence (low values in the blue channel).

The increase of the backscattering is due to the lava

solidification process that increases the surface roughness

(X-Band SAR sensor is very sensitive to the roughness)

while the loss of the interferometric coherence is caused by

the new lava flow occurred between 2014/11/26 and

2014/12/04 modifying the elementary scatterers and their

positions on the ground. Indeed the lava flow present only

on 2014/12/04 appears greenish because of the increase in

the backscattering coming from the SAR image acquired on

that date.

Despite the MTC analysis generally requires both a pre

and a post event image, in the specific case study it was

possible to exploit two post event images, due to the peculiar

morphology of the affected area that direct the lava flow

always in the same areas.

3.2. MTC approach validation using Optical data

The accuracy of the lava extent extracted from the MTC

approach was assessed by computing the confusion matrix

with respect to reference data. As reference data the post-

event crisis vector dataset produced by visual interpretation

of optical imagery (Pléiades © CNES 2014, acquired on

29/11/2014 12:27 UTC, GSD 0.5 m) in the framework of

the Copernicus Emergency Management Service - Mapping

activation (related to the same event and available on the

related portal) were exploited [4].

Figure 4 – The lava extent extracted by the MTC approach

(red outline) compared with the reference data (green

outline). Details of the areas with main differences (1 and 2).

As shown in Figure 4, the MTC polygons (in red) fits the

overall shape of the reference data (in green), excluding two

areas (black squares) with clear differences. The main

differences between the two polygons and the related

probable causes are:

the MTC polygon is slightly larger than the

reference data due to the temporal differences

between the acquisition dates of the imagery used

for the generation of the two lava extent polygons:

considering the ongoing lava flow, it was expected

that the most recent dataset would have lead to the

identification of larger affected areas;

the north-west region of the MTC (Figure 4, Area

1) is influenced by strong geometrical deformations

1

2

1

2

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due to SAR foreshortening effects, affecting the

outcomes of the coherence analysis;

the differences over the area near the main fissure

(Figure 4, Area 2) are mainly due to geometrical

distortions;

User and producer accuracies (and the complementary

commission and omission errors) are reported in Table 1,

with values in the range from 80% to 85%.

The analysis highlight the differences between the two

polygons, specifically:

79,72% of the lava extent extracted from the MTC

corresponds to the available reference data;

14,87% of the ground truth areas were omitted in

the MTC analysis (mainly due to the

aforementioned issues).

MTC 4/12 - 26/11 vs Pleaides 29/11

(%) Lava extent

commission error 20,28

user accuracy 79,72

omission error 14,87

producer accuracy 85,13 Table 1 – MTC-based lava extent accuracy assessment

4. CONCLUSION

The Fogo Island case study demonstrated that the MTC is a

suitable approach for monitoring the evolution of volcanic

eruptions. The usage of X-band SAR sensor has the great

advantage to be almost completely not influenced by the

eruption plume coverage, allowing a continuous event

monitoring.

The thematic accuracy of the identification of the lava extent

is mainly limited by the well-known geometrical issued of

SAR acquisitions, limiting the possibility to perform a

reliable MTC analysis over areas affected by foreshortening

and layover effects. The integration of the results derived by

the analysis of additional interferometric pairs characterized

by different acquisition geometries is a possible solution to

cope with the aforementioned issue.

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