Space remote sensing for urban damage detection mapping and mitigation

1
Space remote sensing for urban damage detection
mapping and mitigation
Salvatore Stramondo1, Nazzareno Pierdicca2, Marco
Chini3, Christian Bignami1
1 Istituto Nazionale di Geofisica e
Vulcanologia,Via di Vigna Murata 605, 00143,
Rome, Italy. stramondo_at_ingv.it, bignami_at_ingv.it 2
Dept. of Electronic Engineering, Sapienza Univ.
of Rome, Via Eudossiana 18, Rome, Italy.
pierdicca_at_mail.die.uniroma1.it 3 Dept. of
Physics, Univ. Alma Mater Studiorum of Bologna,
Viale C. Berti Pichat 8, Bologna, Italy.
chini_at_ingv.it
Introduction In the last years the remote sensing
techniques have been demonstrated a suitable
monitoring tool for providing data useful for
disaster mitigation. In particular, in case of
strong earthquake, the rapid detection of damaged
buildings and infrastructures has assumed an
important role for the civil protection rescue
activities. Moreover, the damage assessment can
help the redevelopment process of the hit area.
SAR has been revealed a powerful instrument for
change detection and damage evaluation purpose.
In particular, interferometric features like the
InSAR phase coherence and the intensity
correlation of multi-look images collected before
and after an earthquake can be used to detect and
quantify changes in built-up area. On the other
side, optical sensors have also been successfully
used for damage estimation. In fact, the new
optical sensors are reliable systems for
detecting changes of single buildings. However,
the presence of clouds, shadows, variation in Sun
illumination and geometric distortions are
critical for this type of sensors and prevent a
fully automatic change detection approach. When
both optical and SAR are available, a damage
classification can also be obtained by combining
the two data types, leading to a more reliable
result. This work proposes an effective procedure
oriented to the damage mapping. From data
requirements (satellite images and auxiliary
data) to product delivery the chain for damage
mapping is described. This latter in order to
provide new instruments useful to Civil
Protection Departments and Administrations for
disaster management.
Data requirements

• The minimum configuration to perform a damage
  level estimation can be summarised as follow
• SAR data
• Two pre-seismic acquisition
• One post-seismic acquisition
• OPICAL data
• One pre-seismic and one post-seismic
• Auxiliary data
• local cartography
• DEM
• The damage evaluation products can be also
  generated by SAR data alone or by optical data
  alone

Optical Processing

• Two images taken one pre- and one post-seismic
  event.
• Co-registration of the images.
• Extraction of the other information from the
  image before the earthquake in order to have
  more input for the building classification,
  especially when we deal with panchromatic images,
  just one band.
• Building classification of the image before the
  earthquake for limiting the analysis of changes
  just at this feature in order to reduce the
  possible false alarms caused by temporary objects
  (e.g. shadows, cars, vegetation).
• Change detection procedure using both images on
  the building map which is based on the
  pre-seismic image.

Data acquisition strategy
Data collection has to be done as frequently as
possible. In particular a systematic approach of
the acquisition over high risk seismic area is
preferable This approach is intended to create a
catalogue, of both SAR and optical data, composed
by images as current as possible, in order to
avoid false alarm in the damage detection caused
by urban development between pre-seismic and
post-seismic acquisitions
SAR processing
SAR images are processed in order to obtain two
main SAR features the complex coherence and the
intensity correlation. The first one is
calculated from the single look complex data by
means of The second one is evaluated from
multi look data as follows where s1 and s2
are the corresponding complex pixel values, I1
and I2 are corresponding pixel values of the
intensity, and E() indicates the expected
value. Pre-seismic features are obtained
combining two pre-seismic acquisitions whereas
the co-seismic ones are derived using one pre-
and one post-event acquisition
Damage evaluation approaches

• The possible approaches for damage evaluation can
  be separated in
• Optical when only optical data are available
  change detection procedure give the map of
  damages at different scale, depending on the
  ground resolution of the sensors.
• SAR when only SAR data are available, the
  difference between SAR features (complex
  coherence and intensity correlation) is analysed
• SAR Optical data fusion by classification
  algorithms both parametric and non-parametric.

Product delivery
Product Description Tools Scale
Potential damage snapshot Prompt overview of potentially damaged area (only qualitative) Medium/high res. OPT SAR Medium, tens to hundreds meters
Damage level at district scale Damage level (i.e., collapse ratio) estimated on homogeneous urban areas medium/high res. OPT very-high res. OPT SAR District, block of buildings
Collapsed/heavy damaged buildings Identification of single buildings collapsed or heavily damaged Very-high res. OPT Single building