International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
By comparison of these different layers, an enriched layer 
allowing identification of the evolutions of buildings, houses 
and settlements can be created. An excerpt of this vector layer 
showing the status of buildings and houses in a small area of 
Jacmel is shown in figure 2. Buildings existing before the 
earthquake are shown as grey boxes, either opaque if they still 
exist or empty if they have been removed. Buildings built in the 
emergency period are displayed as orange boxes, either opaque 
if they still exist or empty if they have been removed since then. 
Finally red boxes correspond to new buildings or shelters built 
since the emergency period. One must be aware that a dark 
grey box does not always correspond to a safe building, because 
this layer does not take into account the safety status of the 
building (available in another layer). However this information 
can be very useful for the Jacmel authorities in their effort to 
plan the city reconstruction. 
4.2 Analysis of water runoff in urban area 
Water runoff is a major risk in several districts of Port-au- 
Prince and its impact may be higher than usual, given the 
habitat conditions in this area after the disaster. Assessing this 
risk and associated vulnerability is thus a major challenge for 
Haiti. 
Information extracted from satellite imagery like buildings, 
roads and paths, together with a DEM (possibly derived from 
the same imagery) can be used to compute the water paths. Each 
building vulnerability can also be derived by merging these 
water paths and the building locations, geometry and status. 
This is shown in fig 3 for Martissant district. Furthermore, the 
same spatial description of the scene can be fed into 
hydrological models to estimate the water runoff at each 
location; improving the fitting of such models could become the 
subject of subsequent research activities. 
  
X. 
Figure 3 — Water runoff risk assessment showing the water 
paths and the building vulnerability. 
4.3 Automated reconstruction monitoring 
Vector layers described in section 4.1 can also be used, together 
with the high resolution images they come from, as a test case 
for developing new (semi-)automated methods aiming at 
identifying buildings evolutions in high resolution images, 
taking into account the buildings layers when they already exist. 
In situations where housings are rapidly evolving, such methods 
could be very effective because they could help reducing the 
delay for such information production. 
5. PERSPECTIVES 
Besides the applications given as examples in the previous 
section, KAL-Haiti steadily promotes the proposal of new 
applications and research activities in the field of global risk 
management and sustainable reconstruction, from geophysical 
and societal modelling to image analysis, data processing and 
information management. 
From another perspective, the CNES KALIDEOS programme, 
in which KAL-Haiti is inscribed, is committed to support such 
databases and surrounding activities on the long term, thus 
providing a stable environment for contributors willing to be 
involved. 
The KAL-Haiti database will also be proposed as a contribution 
to the Global Earth Observation System of Systems (GEOSS) « 
Supersites » activity which has begun to bring together relevant 
data for scientific study of this event 
Considered together, these three arguments shall strengthen the 
potentialities of the database on the long term.. 
Last but not least, Haiti will of course benefit directly from the 
KAL-Haiti project. A mirror database will be transferred to 
Haiti during the course of the project and assistance in 
exploiting this resource will be proposed with the aim of 
developing a regularly updated GIS, operated by academic or 
institutional Haitian bodies. 
6. CONCLUSION 
The availability of comprehensive and consistent datasets 
corresponding to real use cases is a key issue for the 
development of new methods and algorithms able to solve 
increasingly complex problems. In line with this assumption, 
the KAL-Haiti database is a promising initiative which strives 
to strengthen the global risk management domain which has 
emerged as an important one, given its societal importance. 
7. REFERENCES 
ANR CFP:  www.agence-nationale-recherche.fr/AAP-310- 
Flash-Haiti.html (16/04/2012) 
KAL-Haiti website: http://kal-haiti.kalimsat.fr, (16/04/2012) 
8. ACKNOWLEDGEMENTS 
The KAL-Haiti project is funded by the French Agence 
Nationale de la Recherche (ANR) under grant number 2010 
HAIT 008 01. Contributions of data providers to the database, 
whose list is available on the Kal-Haiti website, are 
acknowledged by the KAL-Haiti project team. 
Inter 
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