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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
However, recent strong seismic events have shown that the
seismological community is not able to collect a large amount
of data on damage distribution for a large destructive event,
especially if the situation is complicated for the hugeness of the
damaged area, for the presence of large towns.
Damag | Description Summary Example Damage to Masonry
e Grade Buildings
Grade 1 | Negligible to No Structural Hair-line cracks in very few
Slight Damage. Slight walls. Fall of small pieces of
Damage Non-Structural plaster only. Fall of loose stones
Damage. from upper parts of buildings in
very few cases.
Grade 2 Moderate Slight Structural Cracks in many walls. Fall of
Damage Damage. Moderate fairly large pieces of plaster.
Non-Structural Partial collapse of chimneys.
Damage.
Grade 3 | Substantial Moderate Large and extensive cracks in
to Heavy Structural Damage. | most walls. Roof tiles deta-ched.
Damage Heavy Non- Chimney fracture at the roof line.
Structural Damage. Failure of individual non-
structural elements (partitions,
gable walls).
Grade 4 | Very Heavy Heavy Structural Serious failure of walls. Partial
Damage Damage. Very structural failure of roofs and
Heavy Non- floors.
Structural Damage.
Grade 5 | Destruction Very Heavy
Structural Damage.
Total or near total collapse
Table 1 — EMS98 scale: summary of the damage grades.
1.2 Earth Observation technology for earthquake damage
assessment: operational and expected capabilities
The main topic of this paper concerns the possibility of using
optical remote sensing imagery for earthquake damage
assessment in urban areas, either in stand-alone techniques or in
support of the above mentioned methodologies adopted by
reconnaissance teams operating on the field.
The growing availability of satellite images, also at very high
resolution (VHR), could in fact permit today to have detailed
information about damage in a short time after earthquake and
for extended areas. It would be especially advantageous for data
collection in areas where access is difficult for political,
economic or technical reasons.
The main interest is related to the assessment of building
vulnerability and damage; about 75% of fatalities attributable to
earthquakes are on the other hand due to the collapse of
buildings (Weston et al., 2003).
Furthermore, these data could be useful for other purposes, not
directly related to this aim:
- in the emergency phase (search and rescue operations,
planning and emergency services, etc.), for instance making
available to the rescue teams the images as base maps in
handheld GPS-GIS systems;
- in a pre-event phase, for development of large GIS-based
databases related to exposure and vulnerability to earthquake of
buildings and other relevant structures, data that are often
incomplete or out of date, and to estimate potential losses. This
subject is moreover of great interest for the insurance and re-
insurance industry, by reducing both the cost and time
necessary for data acquisition.
The research run into some general questions that will be
briefly mentioned here, and in part discussed in deep in the next
paragraphs:
- different situations arise for highly developed or for
developing countries: in the last case there is frequently a lack
of updated maps or even of any sort of georeferenced
693
information, actually hampering the adoption of some
assessment strategies and techniques (on the other hand, direct
intervention on the field with high surveying capacity is in
certain cases quite impossible);
- using pre- and post-event images or just post-event images
could be a questionable option for this kind of analysis, but
sometimes pre-event images are not available or too far in time
from the event and then not reliable for this purpose;
- VHR images show certainly the highest level of detail related
to single buildings and small structures but the associated noise
can be an obstacle in some procedures;
- just some levels of damage can be detected with a good
faithfulness (collapsed and severely damaged buildings) also in
VHR imagery, and moreover some changes not imputable to
earthquake can be sometimes interpreted as damages;
- while nadir images are preferable for change detection
algorithms, the damage could be better observed by visual
interpretation using off-nadir imagery (building façades, ete…):
- the effects of shadows, in particular comparing pre- and post-
event images acquired at different day conditions, make really
hard to carry out automated change detection procedures lying
on the extraction of single buildings; they can furthermore hide
the rubble around buildings. These problems are particularly
evident for VHR imagery. On the other hand the presence or
absence of shadows, in a pre/post event pair, is a signal of a
building collapse;
- image-to-image or image-to-map registration are very critical
issues for this kind of images, sometimes constituting the major
problem in this application;
- data fusion must be exploited in support of damage
assessment, for its characteristic to integrate the high geometric
resolution of panchromatic images with the great information
content provided by multispectral bands; integration of low,
middle and high resolution data is also a promising approach;
- night-time images could be in certain cases useful and provide
valuable information about the real situation after an
earthquake;
- ground data (georeferenced photos, visual reality products,
reports, etc.) are in any case invaluable for a better damage
evaluation;
- issues of timing (temporal resolution) are finally crucial, in
particular if images are used in the emergency phase; some
problems however still exist for a quick availability of the
images and also about their price and their circulation.
The challenge is to integrate or even replace visual
interpretation of optical remote sensing images, accomplished
by expert photo-interpreters, with automatic or semi-automatic
classification techniques.
A choice could be between change detection analysis using pre-
and post-event images or interpretation of post-event images
only by means of specifically developed algorithms to
automatically individuate the areas subject to damage. This
paper will mainly concentrate on the first approach.
2. CASE STUDIES
The research concentrated on two recent, very destructive
earthquakes: the Marmara earthquake, Turkey, occurred in
1999, 17 August (Magnitude Richter 7.4, about 17,100 victims
and 25,000 injured people), and the Boumerdes earthquake,
Algeria, occurred in 2003, May 21 (Magnitude Richter 6.8,
about 2,300 victims and 11,000 injured people).
The data sets selected for the study pursue the progress in
imagery resolution due to VHR satellite constellation launch:
