Presented at NZ ESRI User Group Regional Conference - Christchurch 6 April 2016

1. Volunteered Geographic Information
(VGI) for Disaster Management (DM)
A Case Study for Floods in Jakarta
Emir Hartato | emir.hartato@pg.canterbury.ac.nz
Masters of Geographic Information Science (MGIS) Candidate
University of Canterbury
6 April 2016
NZEUG Christchurch Regional Conference

2. Humans cannot prevent natural disasters, but their
risks can be reduced by understanding their differing
characteristics.
The use of Geographic Information Systems (GIS) is
considered as one of the important information and
communication technology (ICT) tools for disaster
management (DM).
The required data are difficult to acquire or may be
obsolete or not exist.
(Abbas et al., 2009)
(Reinhardt, 2014)
(Cutter, 2003; ESRI, 2000)
Tsunami in Aceh, Indonesia, 2004 (Liputan 6)
Merapi eruption, Indonesia, 2010 (BBC)
EQ Padang, Indonesia, 2009 (Reuters)
BACKGROUND

3. EQ Haiti, 2010
Typhoon Haiyan, Philippines 2013
Calgary Floods, Canada, 2013
Examples of Volunteered Geographic Information (VGI) use in Disaster Management (DM)
Disasters create a time-critical need
for geographic information and VGI
can fill this need with near real-time
information.
(Goodchild & Glennon, 2009)

4. There is a lack of research in the application of VGI for the other stages.
VGI has major credibility issues as data can be contributed by anyone
regardless of their expertise.
A framework to improve VGI’s credibility to enhance its
data quality and accessibility is required.
(Haworth & Bruce, 2015)
(Foody et al., 2013; Goodchild, 2007; Schnebele et al., 2014; Severinsen, 2015)
(Fazeli et al., 2015)
DM Cycle (Khan et al., 2008)
Authoritative vs Non-Authoritative (Schenebele et al., 2014)
Identified Problems

5. What is an appropriate framework to improve VGI’s credibility for DM using
Jakarta flood risk mapping as a case study?
• What is the current practice of the VGI use at each of the DM phases?
• What are the issues with use of VGI across the stages of disaster management?
• What are the advantages and limitations of the collection and use of VGI in each stage?
Research Questions

6. STUDY AREA
Jakarta, Indonesia
Flood events in Jakarta are
expected to become more
frequent in coming years,
with a shift from previously
slow natural processes with
low frequency to a high
frequency process resulting in
severe socio-economic
damage.
(The World Bank, 2013)

7. Population (2014)
• 15 million people (Daytime)
• 10 million people (Night)
Why flooding become a routine
in Jakarta?
• Low topography
• High precipitation intensity
• Sea level rise
• Land subsidence
• Rapid urban growth
(Marfai et al., 2014)
(Jakarta Open Data, 2014)

8. Mapping Jakarta, 2012
• Multi-stakeholders program
• Over 6,000 structures digitized in
OSM
• 2,668 village boundaries in OSM
• Printed map for every village
• Data has been used for flood risk
modelling to support
contingency planning

10. The project has
demonstrated the social
media value within the
disaster management system
as an operational tool to
provide decision support in
the event of disaster.
Real-Time Flood Mapping in Jakarta, 2014
(Holderness & Turpin, 2015)
PetaJakarta.org

11. METHODOLOGY
Literature
review
In-depth
interview
Focus group
• Government
• Non-Government/Private
• Academic
• Flood-affected community
Data Collection

12. • Respondents
• Complicated Indonesian
bureaucracy
• Ethics
• Language
Limitations
Kite Mapping by Ekuatorial showing
inundated area in Kampung Melayu, Jakarta
(2014)

13. CONCLUSIONS
• Jakarta has shown evidences where the government is expanding the application of
VGI at each DM cycle.
• The VGI credibility issue makes the need of appropriate framework crucial in order to
take the full advantages of VGI at each of DM cycle.
• By completing this research, it is hoped that the disaster manager in Jakarta would
learn more about VGI’s nature in DM and take the developed framework as an input
to improve the flood management in Jakarta.
• Other disaster managers also expected to learn from this case study and being
encouraged conduct a similar research in other locations with other disaster types.

14. Thank You
Emir Hartato (University of Canterbury) | emir.hartato@pg.canterbury.ac.nz
Supervisors:
Dr. Ioannis Delikostidis (University of Canterbury) | ioannis.delikostidis@canterbury.ac.nz
Dr. Mairead de Roiste (Victoria University Wellington) | mairead.deroiste@vuw.ac.nz

15. Abbas, S. H., Srivastava, R. K., Tiwari, R. P., & Bala Ramudu, P. (2009). GIS-based disaster management. Management of Environmental Quality: An International Journal, 20(1), 33-51. doi:
10.1108/14777830910922433
Cutter, S. L. (2003). GI Science, Disasters, and Emergency Management. Transactions in GIS, 7(4), 439-446. doi: 10.1111/1467-9671.00157
ESRI, Radke, J., Cova, T., Sheridan, M. F., Troy, A., Mu, L., & Johnson, R. (2000). Challenges for GIS in emergency preparedness and response. Redlands, Calif.: Environmental Systems Research Institute.
Fazeli, H. R., Amerudin, S., Abd Rahman, M. Z., & Said, M. N. (2015). A study of volunteered geographic information (VGI) assessment methods for flood hazard mapping: A review. J. Teknol. Jurnal
Teknologi, 75(10), 127-134.
Foody, G. M., See, L., Fritz, S., Van der Velde, M., Perger, C., Schill, C., & Boyd, D. S. (2013). Assessing the Accuracy of Volunteered Geographic Information arising from Multiple Contributors to an
Internet Based Collaborative Project. Transactions in GIS, 17(6), 847-860. doi:10.1111/tgis.12033
Haworth, B., & Bruce, E. (2015). A Review of Volunteered Geographic Information for Disaster Management. Geography Compass, 9(5), 237-250. doi:10.1111/gec3.12213
Holderness, T., & Turpin, E. (2015). Assessing the Role of Social Media for Civic Co-Management During Monsoon Flooding in Jakarta, Indonesia. Retrieved from
https://petajakarta.org/banjir/en/research/
Goodchild, M., & Glennon, J. A. (2010). Crowdsourcing geographic information for disaster response: a research frontier. International Journal of Digital Earth, 3(3), 231-241.
doi:10.1080/17538941003759255
Jakarta, D. K. d. C. S. P. P. D. (2014). Data Jumlah Penduduk DKI Jakarta. from Jakarta Open Data http://data.jakarta.go.id/dataset/data-jumlah-penduduk-dki-jakarta
Khan, A., Khan, H., & Vasilescu, L. (2008). DISASTER MANAGEMENT CYCLE – A THEORETICAL APPROACH. Management & Marketing - Craiova, 43-50.
Reinhardt, W. P. (2014). Geographic Information for Disaster Management - An Overview.
Schnebele, E., Cervone, G., Kumar, S., & Waters, N. (2014). Real Time Estimation of the Calgary Floods Using Limited Remote Sensing Data. Water, 6(2), 381.
Severinsen, J. J. (2015). Measuring Trust for Crowdsourced Geographic Information.
References