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1. A spatial analysis of the December 26th, 2004 tsunami-induced damages:
Lessons learned for a better risk assessment integrating buildings vulnerability
Frédéric Leone a,*, Franck Lavigne b
, Raphaël Paris c
, Jean-Charles Denain a
, Freddy Vinet a
a
Laboratoire GESTER & Département de Géographie, Université Montpellier 3, 17 Rue Abbé de l’épée, 34 199, France
b
Laboratoire de Géographie Physique UMR 8591 CNRS & Université Paris 1 Pantheon-Sorbonne, Paris, France
c
Laboratoire Géolab UMR 6042 CNRS, Clermont-Ferrand, France
Keywords:
Tsunami
Damage
Vulnerability
Fragility curves
GIS
Indonesia
a b s t r a c t
The December 26th tsunami of 2004 caused an unprecedented disaster in the Indian Ocean. In Sumatra,
a third of the Banda Aceh area was destroyed and 70,000 people died. The Tsunarisque Program e
a FrencheIndonesian research project e brings new considerations to tsunami dynamics and damage
intensity in this urban area: An original method of damage spatial analysis is based on field surveys,
photo interpretations and GIS. The first result is a very accurate cartography of the tsunami breaking zone
that is shown by a steep drop in the damaging gradient around 2.7 km from the coast. The second is
a new “macro-tsunamic” intensity scale based on special typologies of buildings and damages. This
analysis is complemented by fragility curves that give the statistical relationships between mean damage
intensities and wave heights. These results will allow developing application in tsunami potential losses
modelling.
Ó 2010 Elsevier Ltd. All rights reserved.
Introduction
With approximately 70,000 dead (JICA, 2005) and thousands of
damaged buildings, Banda Aceh area (Sumatra, Indonesia) was the
most affected region by the tsunami of the December 26th 2004.
With an exceptional moment magnitude (Mw) of 9.15 (Chlieh et al.,
2007), the triggering earthquake occurred at 7:58 am (local time)
and was located 255 kmwest of the city coast (Fig.1). With a 600 kph
velocity, the tsunami reached the Banda Aceh area only 25 min later
(Borrero, 2005a). At least three main waves and several smaller
waves spread over the city and inland destructions can be seen up to
5 km from the coast (Lavigne et al., 2009). The first main wave was
quite small (1e1.5 m high), very fast (more than 50 kph) and very
turbulent with a sliding type progressive breaking. It was followed
by a bigger second main wave up to 14.1 m 3 min later at Uleelheue,
a western suburb of Banda Aceh. With an inland average of 30 kph,
this wave was not as fast as the first wave, and had a diving or spiral
type breaking. In Banda Aceh, the waves penetration followed the
topographical setting according to sub-perpendicular directions: A
main flow came from the NW, whereas, a secondary flow came from
the SW (Lhok Nga), and they joined at Lampisang. In Kajhu (east of
Banda Aceh), backwash hit a third main wave and the resulting
submersion lasted several hours.
First satellite imageries produced the day following the event
clearly show the destroyed area: Two-third of the urban territory was
affected by varying degrees of destruction (SERTIT, 2004). This remote
sensing analysis was followed by first field recognitions of the
damage, particularly in Thailand (Ghosh et al., 2005; Rossetto et al.,
2007; Ruangrassamee et al., 2006; Srivichai, Chidtong, Supratid, &
Shuto, 2005; Thanawood, Yongchalermchai, Densrisereekul, 2006)
and inIndonesia(Yalcineretal.,2005;Borrero,2005a,2005b;Borrero,
Synolakis, & Fritz, 2006; Ghobarah, Saatcioglu, & Nistor, 2006, Tsuji
et al., 2006). The first complete territorial diagnostic of buildings
and power and transport networks were made by Japanese scientists
in March 2005. Statistics and cartography (1:50,000 maps) were
produced for planning reconstruction (JICA, 2005). No other damage
surveys or mappings at a local scale (less than 1:10,000) have been
made further to make a reconstruction of the tsunami and its related
effects.
This research fills a gap in understanding damage processes
associated with tsunami intensity, location of breaking zone, and
destruction. It first defines an original and reproducible method-
ology and then makes a spatial and quantitative analysis on the
buildings damages. These will be very helpful for producing future
scenarios of tsunami risk and loss quantification.
* Corresponding author. Tel./fax: þ33 4 67 14 58 33.
E-mail addresses: Frederic.Leone@univ-montp3.fr (F. Leone), lavigne@univ-
paris1.fr (F. Lavigne), raparis@univ-bpclermont.fr (R. Paris), Jean-Charles.Denain@
univ-montp3.fr (J.-C. Denain), Freddy.Vinet@univ-montp3.fr (F. Vinet).
Contents lists available at ScienceDirect
Applied Geography
journal homepage: www.elsevier.com/locate/apgeog
0143-6228/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved.
doi:10.1016/j.apgeog.2010.07.009
Applied Geography 31 (2011) 363e375

2. Material and methods
Field surveys and GIS database
A 7 km2
area from coast (Uleelheue) to city center (“Plane
Terrace” in Kampung Baru) was selected for its diversity of buildings
architecture, its high density (885 buildings per km2
) and various
levels of destruction (Fig. 1). Prior to the tsunami, this area was
composed from coast to heart of the city by a barrier beach
(Uleelheue), prawn and fish ponds (“tambak”), a low density resi-
dential zone with paddy fields, and a high density residential zone
very close to the city center. After the tsunami, all these areas were
still linked from the NW to the SE by a main road, with a canal
crossing the eastern zone from south to north. We developed
a comprehensive database on this strongly affected area covered
by: A decreasing gradient for water heights from 14.1 to 0 m
(Lavigne et al., 2006); a Quick Bird satellite view from 2004-06-23
(60-cm resolution); aerial photographs from January and June 2005
(30-cm resolution), a Quick Bird satellite imagery from 2004-12-28
(60-cm resolution) and a Ikonos satellite imagery from 2005-03-01
(1-m resolution).
No cadastral maps were available on this study area. As a result,
GIS maps were constructed using the aerial photographs dating
from January 2005. The selected area was divided into squares
measuring 500 m on each side for field study. During the recon-
struction phase, a systematic recognition was carried out on every
building from the 16th to the 25th of January 2006. Damages were
still significant one year after the disaster despite some rehabili-
tated buildings and some new construction.
Spottings were made in the selected area and also throughout
the city and two simplified typologies were built. One for the
different types of existing buildings; and another based on
damaging modes and levels visible on buildings, attempting to
establish connections between observations from field and Aerial
views. Erased completely destroyed and non-affected buildings
were identified with post-disaster aerial photographs (4970 units).
The buildings totally erased or rebuilt were identified with ante-
disaster Quick Bird imageries (http://www.digitalglobe.com). Finally,
field surveys mainly focused on partly-damaged buildings (1230
units).
Each building was photographed for further complementary
damage analysis. This field diagnosis was a quick and visual
assessment that did not need thorough knowledge on structural
engineering. The primary analysis was on structural damages,
structure linkages and building materials. Every building was given
a code for its vulnerability (building class) and another one for its
level of damage. Lastly, GIS data base counts 6200 units (Fig. 2).
Damage process and magnitude criteria
Despite the outstanding magnitude (9.15) of the earthquake, our
field diagnosis, other scientific works (Boen, 2006, p. S807) and
videos recorded during the immediate aftermath confirmed that
the earthquake caused limited destruction compared to the
tsunami.
A tsunami is a hydraulic phenomenon of marine submersion
characterized inland by a non-Newtonian flow with a heavy sedi-
ment charge (Chanson, 2005). Its impacts on land result in several
Fig. 1. Location of the selected area in Banda Aceh city.
F. Leone et al. / Applied Geography 31 (2011) 363e375
364

3. processes that can follow one another or be simultaneous. Each
process produces distinct damage mechanisms which give infor-
mation on the magnitude of the phenomenon. Seven main
processes from tsunami impact have been emphasised during field
surveys (Fig. 3). Each one of them can be described by one or several
physical parameters (magnitude criteria) that can be theoretically
measured and used for modelling. Concerning the energy of the
second wave with a plunging type breaking, it is possible to
Fig. 2. Map of studied buildings.
Fig. 3. The three different dynamics zones of a tsunami inland. Processes and main associated damage modes on buildings (second wave).
F. Leone et al. / Applied Geography 31 (2011) 363e375 365

4. Table 1
Building classification by decreasing vulnerability.
Vulnerability class of buildings (tsunami e Banda Aceh)
A B C D E
Identification
criteria on the field
Individual building
with wood structure,
completion of wood
or bricks, roof of red
tiles or raw sheet
steels, no floor,
sometimes on piles
Individual building
with concrete structure
hardly strengthened (20 cm
posts * 20 cm), masonry of bricks
or rubble stones, 0 in 1 floor,
roof of raw or painted sheet
steel, or red or grey panels-tiles
Individual building with
structure strengthened by concrete,
masonry of bricks, rubble
stones or concrete, 1 floor, roof of
red, blue, grey or green
panels-tiles or red tiles
Collective building
with concrete structure
not strengthened, 1 in 3
floors, cover of sheet
steels or panels-tiles
Collective building with concrete
structure strengthened. 1 in 3 or more
floors, various roofs
Field view
Identification
criterion by aerial
photographs
Geometry in simple plan
(rectangle or square). Flat,
rusty roofs. Small
dimension
Geometry in simple plan
(rectangle or square). Flat roofs
rarely rusty and more often of
grey or red uniform color.
Small or mean dimension
Geometry in more complex plan.
Several levels of roofs. Oblique
roofs with lively colors. Mean
or big dimension
Geometry in simple
plan (rectangle). Flat or
oblique, rusty roofs mostly.
Big dimension
Geometry in more or less
simple plan. Various
terraces or roofs.
Great dimension.
Mosques present a simple
geometry (square)
with a flat or four
sides roof surmounted
by a dome
Aerial view
(different scales)
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5. Table 2
Classification of building damage modes and levels by increasing severity.
Damage modes and levels of buildings (tsunami e Banda Aceh)
D0 D1 D2 D3 D4 D5
Identification
criteria on
the field
No damage: invisible
damage a year later
Negligible or light
damages: furniture
and roofs have been
damaged, debris have
been laid down in the
house’s surroundings.
Structures are not affected.
Important damages: walls
have been punched, windows
and doors have been pulled away,
roofs have been partly pulled away.
Structures are not affected
Damages to structure’s:
pillars have been broken
floorboards are partly
felt down. Construction
stability can be affected
Heavy damages to
structures: building is
partly felt down
Complete destruction
of building with or
without levelling
Field photo.
Building class illustrated A C C B C B
Aerial recognition Not visible Hardly visible Hardly visible for roofs.
Not visible for the rest. NB:
some roofs were removed
during the reconstruction
Not visible, or hardly if
roofs were removed
Visible Highly visible
Aerial photo.
Level of recovery Livable buildings Buildings to be evacuated
but reparable
Irremediable buildings
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6. distinguish these basic processes from upstream (transit zone) to
downstream (flood zone), and at the core breaking of the wave
(breaking zone) (Fig. 3). Transit and breaking zones are character-
ized by turbulent flows with very high energy; whereas flood zone
is characterized by laminar flows that are less turbulent.
These hydrodynamic processes involve water pressure and
impact forces that are a function of velocity, flow depth and debris
load. Other effects are associated with erosion (abrasion, excava-
tion) and accumulation of different debris that are pulled up,
carried along and laid down by the tsunami. Large floating objects
such as boats and cars can cause impact and obstruction effects that
are able to strongly damage various infrastructures, even a few
kilometres from the coast: For example, a 63-m long and a 20-m
large boat (PLN) was moved 2.6 km inland, to Banda Aceh city.
Backwash flow did not cause a lot of damage to infrastructures. At
the end of the process, some zones can remain flooded for a long
time causing moisture damage. A year later, some building foun-
dations were still flooded in some subsided or eroded areas,
especially in past marshy zones.
To produce damage matrices or functions, damage processes
have to be quantified with simple physical parameters leading to
magnitude scales. On the Phuket seafront in Thailand (Kamala
Beach), Srivichai et al. (2005) deducted that pressures were around
6.8 metric ton/m2
for a 3 m flow depth. Pressure forces are a func-
tion of water mass in motion, and especially various moved debris
that can produce random deformation on buildings. Furthermore,
a pressure model is very difficult to generate because of many
blockages produced by debris and because of protection effects
Fig. 4. Map of interpolated damage levels with B and U vulnerability classes of buildings.
Fig. 5. Example of a protection effect on a building (B type) by a mosque (E type) in Uleelheue bridge area (field picture by F. Leone, January 2006, and aerial photo of June 2005).
F. Leone et al. / Applied Geography 31 (2011) 363e375
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7. created by some buildings. As it is not possible to easily obtain the
pressure field and its direct effects on infrastructures, two relevant
and measurable physical parameters e velocity and flow depth e
are commonly used to generate tsunami magnitude scales and
propagation models. In Banda Aceh, flow velocity was locally
determined with videos (http://www.asiantsunamivideos.com). One
was shot in the City Center close to the Grand Mosque (2.5 km from
coast) and shows a debris flow 1.5 m high with a velocity from 1.5 to
1.7 m/s (Chanson, 2005; Fritz, Borrero, Synolakis & Yoo, 2006). From
Lavigne et al. (2006) this video shows the very end of the first wave.
The other video was shot in an SW suburb (2.4 km from coast) at
8:50am, 36 min after the second wave. It shows a 3-m deep flow,
smoother and more loaded and over twice the speed of the first
wave.
Flow depth can also be used to characterize tsunami magnitude.
Tsunami depth is in theory proportional to the square root of its
velocity. Flow depths were measured and mapped by US, Japanese
and French teams: The Tsunarisque Program researchers notably
showed a second wave height gradient from 15 m to 0 m in the
studied area (Lavigne and Paris, in press). As the tsunami
approached the coast, its velocity decreased while its amplitude
increased in relation to the energy conservation equation.
Magnitude scales of Imamura (1949), Lida (1970), Soloviev (1970),
Abe (1981), Hatori (1986) and Murty and Loomis (1980), were
based on maximal wave heights (Hmax in meter) on coast
(Papadopoulos & Imamura, 2001). The highest wave measured on
Uleelheue (14 m) corresponded to a level 3 on the Imamura and Iida
scale (M ¼ log2Hmax) and a 9.1 in Abe classification (1981).
The diversity of tsunami processes caused various damages to
buildings from minor deterioration to total destruction (levelling)
with clearing. The first wave e probably pushed by the second e
seemed to damage mainly semi-permanent and light buildings
(“sederhana”), according to the “Grand Mosque” which shows
various types of debris in motion. Considering that main damage
effects resulted from the second wave, every process can be related
to the most frequently observed damage modes on the field (Fig. 3).
These main damages are due to front impacts and lateral push
along the tsunami transit. Buildings seem to have exploded when
the wave arrived, and tsunami progression on land sounded like
a bombing, as some interviewees mentioned. Where flow depths
were between 6 and 14 m, up to 2.5 km from coast with an NE-SW
direction, only building slabs and bathroom water tank (“mandi”)
vestiges remained. However, for many of them, these buildings had
a reinforced concrete structure and one or two storeys. Pillars were
pulling away from the buildings or had fallen in the flow direction
and debris was scattered for many kilometres. With water depths
between 3 and 6 m, from 2.5 to 3.4 km from the coast, damage
intensity in this intermediate submersion area is variable, mainly
due to debris impact. The external walls were often perforated and
buildings partially collapsed when pillars broke or fell. Beyond the
tsunami’s breaking zone (southeast direction), the area was flooded
only and thus, less damaged: Submersion was slower and had less
impact effects (between 0 and 3 m). Damages are barely visible
a year later; whereas, debris accumulation was observable by
spatial imageries and pictures just after the tsunami. On the
remaining buildings, seismic damages can be distinguished from
the ones caused by the tsunami. A report by Canadian Civil
Fig. 6. Grounded ships close or inside the studied area (pictures by F. Leone and F. Vinet, January 2006). See Fig. 4 for locating ships N3, 4 and 5.
Table 3
Macro-tsunamic intensity scale based on buildings damages (intensity from I to VI
degrees). This scale combines the class of vulnerability of the building and its level of
damage. It is equivalent to a building macroseismic scale in its development and use.
Buildings vulnerability classes Damage levels on buildings
D0eD1 D1eD2 D2eD3 D3eD5 D5eD6
A I II III IV V
B I II III IV VI
C II III IV V VI
D II III IV V VI
E II IV V VI VI
F. Leone et al. / Applied Geography 31 (2011) 363e375 369

8. Engineering researchers was very useful for marking these differ-
ences in the source of building damages (Ghobarah et al., 2006).
Earthquakes generate soil oscillations that cause damages to
structures by balancing, shearing and bending efforts. In addition,
in areas that have been submerged between 6 and 14 m, it seems
logical that buildings weakened by the earthquake were less
resisted to the tsunami.
Buildings and damage typologies
After several field validations, a spatial and quantitative analysis
of building damages has been done, using two simple and reusable
typologies: One for building type, and another for types and levels
of damage. Five decreasing classes have been defined for charac-
terizing building vulnerability: A, B, C, D, E. They are recognizable in
the field and also in the aerial pictures according to roof shape,
dimension and type. This classification (Table 1) is based on
construction type and building fragility observations made by
Ghobarah et al. (2006) and Boen (2006). “A” is the least resistant
class: Buildings are made of wood and sheet iron, sometimes built
on piles as illustrated on the Uleelheue lagoons borders. “B” type
buildings are made of bricks and have columns of 20 20 cm width
reinforced by 8 mm smooth steel stems. This type is the most
representative of the study area. It often corresponds to self-
constructions and belongs to the local middle class. The C types are
detached and large houses (sometimes a luxury house) with a more
complex design, a reinforced and calculated structure and always
a floor. The D types are an apartment, office (public services) or
commercial block with one or two floors and a basic design.
Structure has several pillars and is usually partially reinforced.
Many of them are present in the Banda Aceh city center. “E” type is
the same kind of building as D type, but it is very well constructed
with calculated and reinforced concrete structures (public services,
mosques, hotels). The 16 mosques located in the studied area
belong to this class because of their high quality construction and of
their specific open-shaped architecture (many pillars and court-
yards). Sometimes it is difficult to distinguish A, B and C types in
aerial photographs when roofs are similar: A field validation is
required. Many buildings have been levelled e especially the ones
close to the coast e and it is impossible to know their initial type
a posteriori. As a result 4095 buildings have been marked in the U
(unknown) class. This typology is quite well-adapted to building
classification for tropical developing countries, and also for French
overseas departments and territories exposed to tsunamis
(Martinique, Guadeloupe, Guyane, La Réunion, Mayotte and Tahiti).
The damage typology is specific to tsunami and is different from
seismic (Grünthal, 2001) and landslide (Leone, Aste, Leroi, 1996,
pp. 263e269) typologies because of the nature of the damage. Six
Fig. 7. Map of interpolated damage intensity for all building types (application of the macro-tsunamic scale).
Table 4
Correspondence between macro-tsunamic intensities (I) and flow depth (H).
Intensity H (m) Intensity from
Papadopoulos
and Imamura (2001)
I 1.5 IeV
II 2 VI
III 3 VIIeX
IV 5
V 8
VI 11 XIeXII
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370

9. classes with an increasing damage level have been defined from D0
to D5 (Table 2). The transition from D2 to D3 classes marks the
damage limit of building stability and its potential reoccupation:
That corresponds to the water’s interaction with the structures
rigidifying the building (vertical and transverse pillars, floor-
boards). Partial or total destruction (D4, D5) can be seen by photo-
interpretation; whereas, lower damages can only be observed from
the field. D3 level needs a little more detailed observation to
superstructures. Taking into account the density of observations on
damage, water depth and direction of movement, and chronology,
a spatial analysis of the damage by a test of interpolation under GIS
was done.
The interpolation supposes that damage follows a continuous
evolution in space for a same class of building. It’s based on U
(entirely destroyed, D5) and B buildings classes. This choice was
determined by the search for a homogeneous average behavior of
the structures for the levels of damage lower than D5. As a result,
the observable space variations in the damage between D0 and D4
Fig. 8. Mean damage curve for B type buildings.
Fig. 9. Curve of total destruction rate (D5 level) for all type buildings (in %).
F. Leone et al. / Applied Geography 31 (2011) 363e375 371

10. will be logically and mainly related to the magnitude of the
phenomenon rather than to the resistance of the building frame
(class B with homogeneous behavior). Interpolation was made with
Vertical MapperÒ
by krigeage (Gratton, 2002) from 5693 units. A
raster file (grid format) was generated and 5 damage level contours
were created.
Results
Tsunami breaking zone reconstruction
On the produced map, it is possible to clearly note the
decreasing gradient of damage from West to East, and up to the
most urbanised areas (Southeast) (Fig. 4). From the Uleelheue
ancient shoreline to nearly 2 km inland, this coastal fringe was
highly destroyed by waves 6e14 m high and most of buildings were
levelled (D5, destruction peak). Some less damaged enclaves
appear in an easterly direction (D4eD2). These enclaves are prob-
ably due to protection effects by other buildings or well-made
constructions. For example, a protection effect occurred for a B type
building that was partially protected by the Uleelheue Grand
Mosque, although waves were up to 14 m high (Fig. 5). At 2.7 km
from the Uleelheue coastline, a significant and NE-SW oriented
discontinuity in the damage gradient appears. Along this one, in
a 100 m wide fringe, water depths fell from 6 to 2 m and damage
gradient sharply decreases from D5 to D1. This seems to result from
the surge of the second wave, and corresponds to a spatial mark of
the dynamics and energy change of the wave. D2 level is easily
identifiable on the field and characteristic of this zone of surge
where the flow smashed the external walls and sometimes the
internal partitions. This assumption is confirmed by location of boat
n4 (PLN) and boat n5 that have been driven ashore on this
probable breaking zone (Fig. 6). The position of the boats n2 and
n3 can be explained by an earlier surge; it is not demonstrated by
the interpolation, but just indicated. Some interviewees mentioned
that a breaking occurred around ship n4. Thus, the wave breaking
zone was charted between the D5 and D2 limits. Its width is vari-
able according to the sectors, which gives a lobed layout which can
be explained by differences in wave height. It seems to be the case
for B7 sector where waves were a little higher (around 6 m high).
The presence of a transverse road in this sector also could spread
out the surge by reducing ground roughness. It is also similar 500 m
upstream for the C6 and C7 sectors where waves were around 9 m
high. In addition, a good spatial correlation exists between the
breaking zone front and the second wave orientations, collected on
the field by Lavigne et al. (2006). Flows split in two distinctive
directions (N 130 and N 150) in the B5 sector, which could be
explained by a division of the wave. This hypothesis could then
explain the location of a possible breaking zone westward, also
indicated by small isolated areas that are less damaged (C5 sector)
and by the boat n2 and boat n3 locations. Beyond this or these
breaking zones, damages are lower (D0eD1) in correlation with
a low-height submersion (less than 2 m high) and a water
stagnation.
Validation of a “macro-tsunamic” intensity scale
Observations on other building classes were not taken into
account in the previous analysis. To integrate this additional
information, we have created a damage intensity scale with
a crossing of two variables: Damage levels (D0eD5) and building
vulnerability classes (A, B, C, D, E), resulting in a “macro-tsunamic”
intensity scale with six degrees, comparable to a macro seismic
scale (Table 3).
Four results are obtained by using this scale for a new damage
interpolation (Fig. 7). First, it makes it possible to find again the
previous damage gradient mapped with the class B. Second, it
confirms the breaking zone location that had been previously
revealed (damage intensity decreases suddenly from VI to I)
making it possible to know the precise location of the Northeast
part of the breaking zone. This limit was previously supposed
because of a few type B building-samples. Third, it makes it possible
Fig. 10. Loss of life curve for 16 districts (“Desa”).
F. Leone et al. / Applied Geography 31 (2011) 363e375
372

11. to better locate areas where site effects were more important.
Fourth, it confirms a more western location of the breaking zone
(and earlier breaking); it is precisely on this area where boats n 2
and 3 were grounded.
As a result, this damage intensity scale presents an opportunity
to locate a tsunami breaking zone basing on a detailed and localised
analysis of damage to buildings that have diverse fragilities. It is
similar to a macro seismic scale (EMS98 for example) that makes it
possible to find the earthquake epicentre, and local geological or
topographical effects. This scale is different from the other ones
available in the scientific literature (Ambraseys, 1962;
Papadopoulos Imamura, 2001; Sieberg, 1927; Soloviev, 1970).
These are based more on multiple qualitative and subjective
criterions (damages, perceptions, environmental effects) and are
not adapted for a detailed and spatial analysis. Lastly, damage
intensity (DI) of all building types was correlated with the flow
depths (Table 4).
Fragility curves implementation
Tsunami-induced damage and loss scenarios theoretically
integrate damage matrices or fragility curves. Associated functions
generally state the probability for a building with an indicated
vulnerability class to be affected by an average damage level
(DMean, named Damage Probability Matrix). It is also possible to
express these functions by the probability to reach a certain
percentage of a particular damage level (D) for a stock of same-
category buildings with a same vulnerability class. In these two
cases (at the building scale or for a stock of buildings), these
functions are used to quantify economic losses when the building
(or stock of buildings) reconstruction value is known (Leone,
2004; Leone et al., 1996). But due to unusualness of detailed
and multi-disciplinary field learning about tsunami damages, such
functions and curves related to tsunami are still very rare in
scientific literature (Koshimura, 2007; Peiris, 2006; Peiris
Pomonis, 2005; Reese et al., 2007; Shuto, 1993), whereas, many
references exist for earthquakes (AFPS, 2005; FEMA 310, 1998;
Giovinazzi Lagomarsino, 2003; RISK-UE, 2003; Schmidtlein,
Shafer, Berry Cutter, in press), for strong winds (Khanduri
Morrow, 2003; Murlidharan, Durgaprasad, Appa Rao, 1997;
Stewart, 2003), or for floods (Dutta, Herath, Musiake, 2003;
MOC, 1996).
Fragility functions and curves were proposed for both
approaches (at the building scale and for a stock of buildings) by
using our large database. For buildings sampling, a 100-m diameter
buffer was created around each point where flow depth was
measured. So, 892 buildings were selected to implement the
fragility curves.
For the first approach (building scale), B type buildings class was
used because of their large numbers in the study area. The resulting
scatter plot gives a logarithmic-type relation and a good correlation
(R2
¼ 0.58). We considered Dmean growth as a continuous function
of flow depth between points D0 and D5 (Fig. 8). We did the same
with the average damage intensity (DImean) and correlation was
better (R2
¼ 0.66).
The same method was applied to a group of buildings
(R2
¼ 0.59). The obtained curve expresses the percentage of total
destruction (D5 level) (between 0 and 100%) as a function of
submersion flow depth (H) (Fig. 9). It is just an indicative value
because building types are not known for the D5 level: the distri-
bution will be certainly different with more resistant and bigger
buildings (2 floors for example), notably with flow depth below
6 m.
In both approaches, other correlations are not significant, except
for D1 level that is simply the opposite of D5. For an operational use
(loss scenario for example), functions have to be defined for each
buildings class: So more learning and modelling on tsunami-
induced damage on structures have to be done to complete these
curves in the future.
Furthermore, there is a very good linear correlation between
people losses (stated in % of dead and missing people) and
percentage of total destruction (D5 level). This correlation was
made with JICA data (2005) on 16 districts (“Desa”), which are
totally or partly located in the selected area (Fig. 10).
In addition, we noticed from our field observation that moder-
ately damaged buildings (D2 and D3) must be renovated and lead-
time is between a few days and a year. Strongly damaged buildings
(D4 and D5) are abandoned or must be reconstructed. Many factors
must be considered about reconstruction and renovation: Organi-
zational, institutional, political and administrative, socio-economic,
cultural, psychological.
Discussion
This study is based on systematic damage analysis on buildings
from in situ observations with an original and reproducible meth-
odology. Typologies were produced to make a quick field survey
and for photo interpretation analysis. The density of collected
information made it possible to produce a very precise mapping of
the damage gradient. This mapping also reveals a tsunami breaking
zone that was only mentioned by visual testimonies. This breaking
zone location was refined using a macro-tsunamic intensity scale
based on all damaged buildings. The correspondences between the
6 degrees of this scale and the average depth of immersion were
also deduced. This analysis shows all the interest of a geographical
reading of the damage in complement of the traditional surveys on
tsunami runups to reconstitute the dynamics and the extension of
the phenomenon. It underlines the determining role of this
dynamics on the mechanisms of destruction and the importance of
the breaking zone as a line of major discontinuity in the gradient of
damage. Until now, no study based on post-tsunami damages
recognition by remote sensing was able to give this degree of
accuracy to inform the dynamics of a tsunami (Greidanus, Dekker,
Caliz, Rodriguez, 2005; Gruhier, 2005; JICA, 2005, Vol. III;
SERTIT, 2004).
The relevance of the future tsunami risks scenarios will largely
depend on the capacity to simulate heights and flow velocity
inland, and the zone of surge of the main wave. These scenarios
will require in the second time to integrate functions of damage
adapted to different stakes (buildings, roads, people, activities,
etc).
The spatial models of tsunami risk assessment are still rare in
the scientific literature. Except the recent work of Marchand,
Buurman, Pribadi, and Kurniawan (2009), they are based on
multi-criteria approach of vulnerabilities and do not introduce
functions and curves of damage (Dall’Osso, Gonella, Gabbianelli
Withycombe, 2009; Dominey-Howes, Dunbar, Varner,
Papathoma-Kohle, 2009; Dominey-Howes Papathoma, 2006;
GNS Science, 2008, 19 pp.; Omira et al., 2009; Papathoma, 2003;
Wood, 2008). In addition and in useful complement, Sugimoto,
Murakami, Kozuki, and Nishikawa (2003) proposed a simulation
of the evacuation times for littoral populations in Japan in the event
of tsunami.
In the future, new scenarios that integrate multi-disciplinary
steps, tools, and data deserve development in this and other socio-
geographical contexts. That supposes to work in the light of expe-
rience feedbacks as rich as that undertaken in Indonesia within the
framework of the international project “Tsunarisque” (Lavigne
Paris, in press http://www.tsunarisque.cnrs.fr).
F. Leone et al. / Applied Geography 31 (2011) 363e375 373

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