What are collaborative maps and how are they used in disaster management?
Oct 24th, 2014 by j0p
By Bianca Kappl
Natural and anthropogenic disasters have occurred in history and will occur in future, because of global climate change, population growth or the spread of infectious diseases (ZOOK ET AL. 2010, 10). The Haiti Earthquake occurred in January 2010 could be regarded as a good example for a natural disaster in the context of “Volunteered Geographic Information” (VGI). After this disaster, fast and extensive help was needed. The two major questions that immediately had to be answered then were who actually was in need of help and where these people were located. Comprehensive databases of assets, infrastructure, population and location were limited, which is why it was difficult for the responders to help in the disaster region (ZOOK ET AL. 2010, 14). The catastrophe in Haiti shows the necessity of geo-spatial information of a certain region in order to help people in need. Since geo-spatial information from that region was missing and this lack was corrected from volunteering mappers who organized themselves via internet. The information distributed through social media and Web 2.0 technology. Web 2.0 describes websites that allow users to collaborate with other users to work on projects like disaster response (NEIS ET AL. 2010, 6).
A popular example of Web 2.0-style mapping is the OpenStreetMap (OSM) project. Volunteers can create a free street map for the entire world by using Global Positioning System (GPS) trails and digitized street patterns from aerial imagery. In case of the earthquake in January 2010 the OSM project was an important source of Web 2.0 mapping, because people from developed countries enjoy better access to geodata than people from poor countries and with that knowledge they collected a lot of information for the responders (ZOOK ET AL. 2010, 11). This example illustrate that information technologies (IT) are an important part of disaster response. With the development of OSM and a variety of other web- based mapping services such as Google, the opportunity for volunteers to help in disaster response situations via mapping and other spatial analysis has grown significantly (ZOOK ET AL. 2010, 12). IT ́s were a key, because individuals can support relief work and aid agencies without actually being physically present in Haiti or other disaster areas. It can empower people from every place to work for the public good (ZOOK ET AL. 2010, 10).
The crowdsourced geo-spatial data and the collaborative maps have many benefits. Most importantly, this form of mapping allows to produce many maps in a short period of time (ZOOK ET AL. 2010, 12). The ability to leverage IT ́s to allow individuals to report on local and specific conditions is another important benefit of Web 2.0 and disaster mapping, too. When many people work together on a project without knowing each other, it is quite likely that because errors occur. However, a good thing about collaborative maps and crowdsourced geo-spatial data is, that “with enough people working together, any errors by one individual can be easily corrected by another” (ZOOK ET AL. 2010, 13).
Figure 1: Maps from OSM data showing Port-Au-Prince before the earthquake, two days after the earthquake and how it looks now (NEIS ET AL. 2010, 5)
Figure 1 shows three maps from the capital of Haiti Port-Au-Prince. The map on the left-hand side shows the situation before, the second one the situation two days after the earthquake. These are good examples of “Volunteered Geographic Information” (VGI), within a few days volunteers have organized user-generated datasets via Web 2.0. With maps like these and other spatial information the disaster management can be improved.
Nevertheless, collaborative maps do also have disadvantages. Since they are mostly created by nonprofessional people, the quality of the geo-spatial data is worse than the data from professional mappers, but it is more important to get immediate help, first of all during crises. Another attraction of volunteer mappers are to fill the blank spaces on the map, not alone during crises (ZOOK ET AL. 2010, 11f).
References:
ZOOK, M., GRAHAM, M., SHELTON, T., GORMAN, S. (2010): Volunteered Geographic Information and Crowdsourcing Disaster Relief: A Case Study of the Haitian Earthquake. World Medical & Health Policy, 2(2). doi: 10.2202/1948-4682.1069
NEIS, P., SINGLER, P., ZIPF, A. (2010): Collaborative mapping and Emergency Routing for Disaster Logistics – Case studies from the Haiti earthquake and the UN portal for Afrika. In Geospatial Crossroad s@ GI_Forum 2010. Proceedings of the Geoinformatics Forum Salzburg (pp. 239-248). Salzburg, Austria.
Further reading:
HEIPKE, C. (2010): Crowdsourcing geospatial data. ISPRS Journal of Photogrammetry and Remote Sensing, 65 (6), 550–557. doi:10.1016/j.isprsjprs.2010.06.005
RAMM, J. T. F. (2010): OpenStreetMap. Lehmanns Media GmbH.
SCHELHORN, S. J., HERFORT, B., LEINER, R., ZIPF, A., & ALBUQUERQUE, J. P. de. (2014): Identifying Elements at Risk from OpenStreetMap: The Case of Flooding. In Proceedings of the 11th International ISCRAM Conference (pp. 1 – 5).
GOODCHILD, M. F. (2007): Citizens as sensors: the world of volunteered geography. In GeoJournal 69:211–221. doi 10.1007/s10708-007-9111-y
Hey everyone,
Great example with the map from Port-au-Prince. This really shows how useful collaborative maps are in total! I just have one problem with these maps that I would like to point out.
In Fig. 1 we can see that the maps evolve to a very precise street map of Port-au-Prince in a short period of time. I guess pretty much every road is mapped which is a big advantage for the people helping there. Still there is no precise information about the status of the people living in this area. First helpers do need information where severe injured people, injured people or people who need just a “little” help are located. I can imagine that it is not easy to get these special information and it is not the resonsibility of a collaborative map to give such information. Yet these maps would be much more helpful for first helpers if they show these information.
Maybe information provided by social media is the answer…?
Have a good one!
David Max
Thank you for the great summary.
I’m impressed by the Haiti-Example and the map of Port-Au-Prince and how fast a map can be adapted and developed. Still I have some questions or some things I’m wondering about:
What about already available maps? Of course they are often outdated and not for free but couldn’t they be used as a basis? In many cases after the occurrence of a disaster commercial data (mainly high resolution remote sensing data) was provided for free by the companies (Kawasaki et al. 2010) to support relief, response and recovery. This could be possible with maps as well.
Yet another thought arises for me from the topic of collaborative maps. So far in all the papers and articles I read they were mainly used for post-disaster-management. But what about pre-disaster management? Couldn’t collaborative maps also be used for preparation in some ways? So people can (for example) evaluate themselves whether the realty they’re planning to build their house on is threatened by flooding events?
And last but not least I keep wondering about the organizational part behind the whole crowdsourcing thing. Because after all at least a little bit of organization and structure is needed like: who coordinates which parts of the map are already getting tracked or drawn? Is there anyone who sets priorities?
After all I think that collaborative maps are very useful especially for disaster management because psycho-social research has shown that collaborative intelligence is sometimes better than the intelligence of one person alone as errors are compensated by the amount of information input. This is a great example of Aristoteles’ saying “The whole is more than the sum of its parts”.
Goog job, I think the lector can make itself a good idea of the topic in a few lines. Concrete and explicit.
I agree with Charlotte’s question concerning the fact whether there are already existent maps. Of course in poor countries does not exist as good open information (e.g. Open street) as in developed countries and they often do not have access to the newest technologies. But in case of emergency it would be important that volunteer mappers can quickly access information that normally wouldn’t be available. Society should aks for the open access of this information in case of a disaster.
In the whole area of Central America every year small natural emergencies happen, but not only in these areas it is well known that there exist risk of repeating natural disasters. Therefore, it is not only important to act after a disaster has happened but to establish a data base that can help volunteer mappers to create maps in a more efficient and effective way after a disaster has occured. Groups at different univerities could help in establishing such data bases of geographical data which after a diaster are used by volunteer mappers to create the maps.
Nico.