Common Scenario

The following common scenario on disaster management in the case of an earthquake gives a research direction for the International Research Training Group on Semantic Integration of Geospatial Information.

Disaster Management (Earthquake)

In the early morning hours of 6 April 2009 a severe earthquake hit the city of L’Aquila and its surroundings, in the Abruzzo region of Italy, causing the death of 307 people and more than 1’500 injured. Between 3’000 and 11’000 buildings were damaged solely in the city of L’Aquila.

Typically, urban and wild environments are represented in GIS application developed by national or local administrations, industries, military forces, etc. Each of them stores in a GIS system all the geographical informations useful for their kind of target: a local administration could have a good description of roads, buildings, natural zones belonging to the environment; an industry enterprise wants to manage, in most cases, information useful for their kind of business; military forces, indeed, would like to store and manage information related to strategic points or risk zones within an urban environment. Obviously the cited application are only a small part of the global GIS purposes and applications.

With full access to all the datasets stored by the different administrations or industries GIS, it is possible to say that one can solve almost all kind of problems and can develop all kind of geographical applications using the informations stored in existing GIS.

Data changes are often slow processes and changes affect only a minimal part of the whole data stored in a GIS; let us imagine the process of construction of a new road or building that requires a long time to be completed and that affects only the neighbor of the new entity.

In this case it is quite easy to update GIS information: the only mandatory operation is to make accurate measure of the new entity and add it to the system, and eventually update information related to objects that was affected by the changes.

But what happens when an unexpected natural event, like an earthquake or a tornado, changes in few seconds the typical “static” environment? This kind of event can cause a lot of changes in the environment: a bridge can fall down, a landslide can occlude a road, etc.

In this case, different from the typical situation described before, data changes are no more slow processes and can affect a big part of the whole data managed by GIS.

Obviously these kind of changes make the environment description stored in a GIS system unusable; at the same time, after a natural catastrophe GIS data is particularly important as it is needed to coordinate the different aid operations. In particular, considering the example of an earthquake hits a city, it is possible to find a lot of tasks that need to start in the minutes after the natural event and need to be completed in the shortest possible time. Let’s consider, for example, crucial operations like victims rescue, aid dispatch to survivors, organization of gather points and of management points for people who have to manage the catastrophic situation.

The requirement of first aid makes an efficient infrastructure necessary. The firefighters and rescuers rely on a flow of latest information. The operational command has to update its information to avoid losing time by having emergency vehicles reaching deadlocks.

With a good description of the environment, it is possible to take care of these kind of tasks reducing the risk for rescue missions and for survivors; in contrast, using information stored in a non-updated GIS, e.g. to find the shortest way to reach a zone where there is necessity of aid, there are intrinsic risks to obtain a path that can not be used anymore, because of collapses or landslide; this eventuality increase hazard for rescue missions and also increase the time to take aid to people.

The challenge is then to try to update informations on GIS systems in a fast way, using when possible automatic agents instead of humans and take advantage from the power of modern automatic calculators.

Modern observation systems make a quick surveillance possible. Remote sensing, unmanned aerial vehicles, but also reports by helpers and victims provide valuable information. Different groups, like the military, local administrations, the Red Cross and other aid organizations, universities or single persons can contribute valuable information. Most of these contributions can be grouped as sensory information: observations and measurements. An efficient integration of various sensory information sources across communities and different data models is crucial in this situation. The red cross does not only need to know how many people are injured, but they need to decide on where to set up their camps and mobile hospitals to achieve the best accessibility. Blocked roads have to be removed from the route planning. Helicopter landing fields have to be scouted. Medical supply has to be delivered. In such case medical information, demographic information, military information and personal information have to be integrated and made available to the institutions that need them. In time critical applications it is not only important to make all information available to all parties, but to support the retrieval of precisely the required information.

The International Research Training Group “Semantic Integration of Geospatial Information” addresses problems arising when integrating geospatial information across different communities and data sources to reason and support decision about the human environment.

Personal research within the scenario: