“Broadly speaking, qualitative-reasoning research aims to develop representation and reasoning techniques that will enable a program to reason about the behavior of physical systems, without the kind of precise quantitative information needed by conventional analysis techniques such as numerical simulators. … Observing pouring rain and a river’s steadily rising water level is sufficient to make a prudent person take measures against possible flooding – without knowing the exact water level, the rate of change, or the time the river might flood.” (Y. Iwasaki, Real-World Applications of Qualitative Reasoning)
Human-being, indeed, are used to reason with qualitative information rather than numbers. On the other hand, big part of actual artificial systems implements mathematic/numerical theories and calculi. This makes “tricky” for humans to interact with machines, as they cannot use them natural expressivity. Development of qualitative reasonings and their application to automatic systems, can facilitate the communication among humans and machines. This is one of the reasons Qualitative Reasonings have been quickly developing during the last decades. Nevertheless, although qualitative reasoning methods are rapidly emerging and developing in several areas, they are still relatively unknown in the Geographic Information field, indeed, up to now, just the topological aspect has been taken into consideration and integrated in the major part of GISs. Again, even if GISs comprise the topology, they are not optimized to answer to topological queries as processing the query will always go down to the geometric level. It is evident that, whether topological relationships would be directly stored within a GIS, topological queries execution performance would be highly improved. Finally, other qualitative relations, direction and orientation, relative position, as well as what we can name “target-oriented” qualitative models, are completely unconsidered within nowadays GISs. This means for example that whether one would like to query a GIS on a qualitative requirement will have to translate the query into some geometric constraints.
If a GIS would explicitly include the storage of qualitative relations, it would provide a powerful instrument for operations and searches based on them. Indeed it would be possible to reduce efforts that today are needed to translate from qualitative representations (typically human) to mathematic/geometric representations (standard GIS). Furthermore, qualitative queries would also allow for using Geographic Information Systems in a completely new way. Indeed it would be possible to satisfy a big range of requirements that today cannot be accomplished. The users would be furnished with a high power system, able to satisfy more human-like requests. The system would become much more user-friendly leading to a range of novel kinds of spatial analyses that are impossible to imagine nowadays. The intrinsic properties of the system would also lead to the possibility to directly collect and store qualitative data avoiding a specific geometric description. Nevertheless it would be possible to reconstruct a geometric approximation directly from qualitative relations if sufficient qualitative information is available in the system.
If a hybrid GIS stores dataset regarding a specific location, a city, a forest and so forth, it would provide the basis for a fast dataset update when a catastrophic natural event occurs. Such a system would allow a rapid recontruction because it will be able to directly manipulate and store qualitative information as well quantitative ones. Furthermore, when the system is queried through qualitative requirements, it will be possible to immediatly access and retrieve the right information, providing quicker answers to qualitative queries. Finally, Qualitative Reasonings will provide further information by inferences that will be possible to do on already stored qualitative data.