GEO WEB SERVICES Spatial Data Infrastructure Infraestructura de datos espaciales

1. DESIGNING WEB-ENABLED SERVICES
TO PROVIDE DAMAGE ESTIMATIONTO PROVIDE DAMAGE ESTIMATION
MAPS CAUSED BY NATURAL HAZARDS
F. V. Gutierrez, M. A. Manso, M. A. Bernabe
D H Lang M Wachowicz W StrauchD. H. Lang, M. Wachowicz,, W. Strauch

2. CONTENTCONTENT
1 Introduction1. Introduction
2. Related work
3. Case of study
4. Methodology
5. Results
6. Conclusions and future work

3. 1. INTRODUCTION (2) The need for a map
? ? ?? ? ?
? ?
? ?
? ?
? ?? ?
A map for answering questions related to: location, casualties, damage zones

4. 1. INTRODUCTION (3) The answer can depend in
the level of detail of the base information.
A big granularity:
the level of detail of the base information.
A
(example)
Cities :
- The number of people
B
A - The number of people
- Amount of houses.
C
But when attempting to
predict and estimate losses
due to natural hazards
f- Demographic information
- Buildings stock inventory
- InfrastructuresInfrastructures

5. 1. INTRODUCTION (4) Problems when reaching
this kind of information:this kind of information:
- Information is related with protected information.Information is related with protected information.
- Created for taxes goal not thinking in Risk.
- There a large numbers of initiatives promoting SDI but only in a
few cases natural hazards domains is included into them (Schmitz
et al.), that's mean s that if the information is available it is no
often through out standardized way for software accessingoften through out standardized way for software accessing

6. 1. INTRODUCTION (5)
THE CHALLENGETHE CHALLENGE
- Analysis and design of a set of OWS using
the available resources, as promoted by SDI initiatives.
- Identification of services to reproduce the experience in other
places.
THE MOTIVATION
To propose a distributed and standardized vision
for providing data access and information processing for estimationfor providing data access and information processing for estimation
and presentation of the damage caused by natural hazards.

7. 2. RELATED WORK
Thi i h 't b h i
PAGER: Prompt Assessment of Global Earthquakes for Response
Developed by the USGS
This review hasn't been comprehensive
Evaluates the number of people, cities and regions exposed to a
powerful earthquake in all over the world.
Developed by the USGS.

8. 2. RELATED WORK (2)

9. 2. RELATED WORK (3)
Why doesn't PAGER estimate loss of life or property?
in order to estimate building damage or human casualties, it would be necessary
to use databases of building inventories...
No such database exists on a global scale
to use databases of building inventories...

10. 2. RELATED WORK (4)
GEM: Global Earthquake Model
Intends to be an independent, consistent standard of worldwide application for
calculation of risks, estimate of loss by an earthquake and communication of
hazards. (2013 the first complete global earthquake model).

11. 2. BACKGROUND (5)
CAPRA: Central America Probabilistic Risk Analysis
CAPRA is defined as an information platform to support risk management for
decision making in natural disasters.
i l t O G N d- implements OpenGeoNode
- Uploading of data and metadata in the GeoNode
- OGC standardized services WMS, WFS and CSW
- Lack of direct connection to the data sources.

12. 3. CASE OF STUDY
Hazards:
Earthquakes
LandslidesLandslides
Eruptions
Tsunamis
Hurricanes
Floods
NICARAGUA
hit by 3 powerful
Managua
hit by 3 powerful
Earthquakes In the
20th century, last one left
h lf f l tione half of population
Homeless.

13. 3. CASE OF STUDY (2) Agencies/Resources
Two studies of seismic risks and vulnerability of Managua had been
carry out in Managua since 2003. The last one in 2009 (RESIS-II).
Agencies Resources
M B ildi St k I tManagua
municipality
Building Stock Inventory.
INETER Hazard information in GIS formatINETER Hazard information in GIS format.
INETER Near-Real-Time earthquake information.
NORSAR Software for Risk and Loss estimation.
NORSAR/UPM Software for Risk and Loss representation.
UPM/NORSAR Software for assigning typology to the
b ildibuildings
UPM Geo-Web Services Chaining

14. 3. CASE OF STUDY (3) Resources for loss estimations
due to Earthquakes (DATA)
1. Seismicity database: Historical event database.
due to Earthquakes (DATA)
1. Seismicity database: Historical event database.

15. 3. CASE OF STUDY (4) Resources for loss estimations
due to Earthquakes (DATA)due to Earthquakes (DATA)
2. Soil classification : Created from the study of analysis and2. Soil classification : Created from the study of analysis and
response spectrum of the soil in different city areas.

16. 3. CASE OF STUDY (5) Resources for loss estimations
due to Earthquakes (DATA)due to Earthquakes (DATA)
3. Information of the event (Earthqueke): Detected, processed
and sent to the seismic station through the Earthworm and Seisanand sent to the seismic station through the Earthworm and Seisan
systems.

17. 3. CASE OF STUDY (6) Resources for loss estimations
due to Earthquakes (DATA)due to Earthquakes (DATA)
4. building stock inventory : Obtained from SISCAT, the municipal4. building stock inventory : Obtained from SISCAT, the municipal
cadastre system of Nicaragua. This database contains over 200,000
constructions.

18. 3. CASE OF STUDY (7) Resources for loss estimations
due to Earthquakes (Model)
5. SELENA: SEismic Loss EstimatioN using a logic tree Approach.
due to Earthquakes (Model)
5. SELENA: SEismic Loss EstimatioN using a logic tree Approach.
... allows calculating the damage as a function of the available information
sources and levels of uncertainty associated to input data ..

19. 3. CASE OF STUDY (8) Resources for loss estimations
due to Earthquakes (Softwares)due to Earthquakes (Softwares)

20. 4. METHODOLOGY
For designing the proposal a system architecture the following
steps were done.
1) Analysis - Earthworm and Seisan) y
for implementing services of warning and notifications.
2) S d B ildi l i Al i h /P2) Study - Building typologies Algorithms/Programmes
Resistance capacity curves / building of the inventory.
3) Study - SELENA API
for publishing their functionalities with OWS.
4) Analysis - SELENA Input/Ouput

21. 4. METHODOLOGY (2)
5) Analysis – RISeRISe API
for publication of its functionalities in a standardized way.
6) Analysis - RISe input /output
7) Data harmonization (building inventory ) for the cadastral
data base.
8) Modelling of the sequencing and arrangement of the execution8) Modelling of the sequencing and arrangement of the execution
of services published for processing and warning on the basis
of the available data.
9) Design of a system architecture connecting all standardized
resources through the Internetresources through the Internet.

22. 5. RESULTS
Resources OGC standards Relationship name
1. Soil classification
2 Construction inventory database
WFS, GML, WMS
WFS GML WMS
SC-WFS
CIDB WFS2.Construction inventory database WFS, GML, WMS CIDB-WFS
3. Building typology database WFS, GML BTDB-WFS
4. Assignment of structural
vulnerability information to
WPS, WFS, GML AV-WPS
AV-WFSvulnerability information to
building typologies
AV WFS
5. Seismicity database WFS, GML, WMS SDB-WFS
6. SELENA WPS SELENA-WPS. S
6.1 SELENA input data
6.2. SELENA output data
77.. RISeRISe
W S
WFS, GML
WFS, GML
WPS
S W S
SELIN-WFS
SELOUT-WFS
RISE-WPS
77..11 RISeRISe input data
77..22 RISeRISe output data
8. Earthworm
WFS, GML, KML
WFS, GML, KML
SAS, WNS
RIN-WFS
ROU-WFS
EW-SAS-WNS
9. Seisan SAS, WNS SS-SAS-WNS
10. Geoservices arrangement
(Orchestration engine)
BPEL (not an OGC
standard )
OREN-BPEL

23. 5. RESULTS (2)

24. 5. RESULTS (3)

25. 6. CONCLUSIONS AND FUTURE WORK
1. The main contribution of our work has been the proposal
standard geoservice architecture to generate damagestandard geoservice architecture to generate damage
estimation maps from seismic events.
For the design of these services we have tried to reuse to the
utmost existent resources..utmost existent resources..

26. 6. CONCLUSIONS AND FUTURE WORK (2)
2. The application of standardized technologies to interconnect
autonomous systems ensures their interoperability.y p y
3. The proposed architecture keeps the roles of actors/agencies
and people.and people.
4. An issue that will require a coordination effort is data model
specification to be offered by the municipalities with the
cadastral data.
5. The use of geo-referenced syndicated news (GeoRSS) for tu
publish the seismic events.

27. The end
Thank youThank you
vladimir@gmail.com
vladimir@topografia.upm.es