8
Using Qualitative Information in Query Processing
over Multiresolution Maps
Paola Podest` a
1 , Barbara Catania
1 , and Alberto Belussi
2
1 University of Genoa, Genoa (Italy)
2 University of Verona, Verona (Italy)
8.1 Introduction
Recently, the availability of huge amounts of spatial data representing geographical
information has significantly increased. This is essentially due to both the increasing
number of different devices collecting such data (i.e. remote sensing systems, environmental monitoring devices and, in general, all devices linked to location-aware
technologies) and to the amazing development of distributed computing infrastructures (e.g. the Web) as platforms to share and access any type of information.
Geographical data usually correspond to data sets collected and integrated from
different sources (private or public institutions), produced by different processes
(e.g. social, ecological, economical) over a geographical area, at different times
(e.g. every 10 years), possibly using different devices. Such geographical data sets
are sets of geographical features spatially described as geometric objects embedded
in a reference space and/or spatial relationships existing among them. Information
concerning spatial relationships can be derived from geometric data but it can also be
directly provided and related to features for which no geometric information is available. In this chapter, using a quite common terminology in geographical database
systems, we call such data sets maps.
In a distributed environment, depending on the application context, it is often
possible to find different, that is, multiresolution, representations of the same or overlapping maps. Multiresolution may have different meanings in different contexts. It
may correspond to a different pixel size in raster data sets, to the number of points
used to visualize a line in vector data sets, or to the different dimensions assigned
to the same geographical feature in distinct maps. For example, a road can be represented as a region for an ecological process whereas it can be represented as a
line for a traffic analysis process. In this chapter, we consider multiresolution maps
according to this last meaning.
Managing multiresolution data sets in a distributed environment is an interesting
but complex problem that can be addressed under two different points of view. From
a system point of view, multiresolution may lead to query processing and integration
problems, as the same concept can be represented in different ways and at different
Using Qualitative Information in Query Processing
over Multiresolution Maps
Paola Podest` a
1 , Barbara Catania
1 , and Alberto Belussi
2
1 University of Genoa, Genoa (Italy)
2 University of Verona, Verona (Italy)
8.1 Introduction
Recently, the availability of huge amounts of spatial data representing geographical
information has significantly increased. This is essentially due to both the increasing
number of different devices collecting such data (i.e. remote sensing systems, environmental monitoring devices and, in general, all devices linked to location-aware
technologies) and to the amazing development of distributed computing infrastructures (e.g. the Web) as platforms to share and access any type of information.
Geographical data usually correspond to data sets collected and integrated from
different sources (private or public institutions), produced by different processes
(e.g. social, ecological, economical) over a geographical area, at different times
(e.g. every 10 years), possibly using different devices. Such geographical data sets
are sets of geographical features spatially described as geometric objects embedded
in a reference space and/or spatial relationships existing among them. Information
concerning spatial relationships can be derived from geometric data but it can also be
directly provided and related to features for which no geometric information is available. In this chapter, using a quite common terminology in geographical database
systems, we call such data sets maps.
In a distributed environment, depending on the application context, it is often
possible to find different, that is, multiresolution, representations of the same or overlapping maps. Multiresolution may have different meanings in different contexts. It
may correspond to a different pixel size in raster data sets, to the number of points
used to visualize a line in vector data sets, or to the different dimensions assigned
to the same geographical feature in distinct maps. For example, a road can be represented as a region for an ecological process whereas it can be represented as a
line for a traffic analysis process. In this chapter, we consider multiresolution maps
according to this last meaning.
Managing multiresolution data sets in a distributed environment is an interesting
but complex problem that can be addressed under two different points of view. From
a system point of view, multiresolution may lead to query processing and integration
problems, as the same concept can be represented in different ways and at different