elementary objects at a lower level; e.g. at a municipality
level a GIS may contain houses, streets and parks, while at a
national level a GIS may contain towns and urban areas.
Another aspect is how the data will be used: is it for
monitoring the terrain situation, or is it for the analysis of
the situation, or will the data be used for planning purposes
etc. Each field of activities puts its own requirements the
type of terrain description, although there are often overlaps
between these requirements. A fourth important aspect that
in many disciplines the relevance of data changes with time.
In agriculture for example, the requirement for soil
information has changed during the last decades. Originally
the main interest was to analyze the suitability of soils for
sustaining different crops. At present the interest changes to
e.g. the capacity of the soil to store chemical elements which
could do harm to the environment.
These observations show that the decision of what data are
relevant is always context dependent, i.e. the elementary
objects with their classes at the different hierarchical levels
and linked to these classes the attributes with their value
domains. For these elementary objects it should be decided
also to which geometric type they belong. This will depend
on the geometric role they play in the terrain description,
this role should not be confused with the appearance of these
objects in reality. It may be that a river is treated as a line
object in a data base for hydrological purposes, whereas the
same river is treated as an area object in the data base of the
authority responsible for its maintenance. Similarly a town
may appear as an area object in a data base for demographic
purposes, whereas the same town appears as a point object
in a data bases containing air traffic routes. The decision
which geometric aspects of an object are important is always
made in a particular context and that implies the decision
whether it should be treated as a point-, line- or area object.
Within such a context one should also decide what are the
relevant object aggregates and associations that should be
constructed from the elementary objects.
Data modelling should be done with care, the discussion of
the structural and semantic aspects and the context
dependency of the data explains why. Therefore tools should
be developed to assist us in the process of spatial data
modelling, to find out what can be modelled and what not.
The Modul-R Formalism of [Bedard e.a. 1992] is one
example of such tools.
In the explanation of some of the concepts that play a role in
a geo-information theory reference was made to elementary
and aggregated terrain objects. These are high-level
concepts, very close to the conceptual level a GIS user
would like to think at. Operational GISystems and
DBMSystems require that these high-level objects are broken
down into low-level data types that match the logical data
structures of these systems. The data management in these
systems has in most cases been organised so that the user is
forced to think and operate at this low level. This often
frustrates the use of these systems, because the user may
have great problems analyzing his complex high-level
problems when he forced to work at such a low level. Data
management tools should be developed that bridge the cap
between these two levels, [Lee e.a. 1992] discus this
problem and propose a solution.
752
UNCERTAINTY
Data models are prescriptions how objects should be
represented in an information system. Once these models
have been defined we are faced with the problem of data
acquisition to fill the database. This means that terrain
objects should be identified, they should be classified and
their geometry should be measured and their attributes
evaluated. This should be done by measuring operations and
it is through these operations that uncertainties of different
types are introduced in the data. Three major types of
uncertainty will be described shortly here (see for a general
treatise [Klir e.a. 1989].
The criteria for assigning terrain objects to a certain class
might be fuzzy: e.g. the definition of nature districts is not
always clear. Does it mean that people do not interfere with
the development of flora and fauna? If it means that there is
only a limited interference of people, then how little should
that be. No sharp criteria can be formulated.
The geometry and the attributes of the terrain objects should
be evaluated through measuring procedures or through the
processing of measuring data. Measuring operations
introduce in general stochastic components in the observed
data. These stochastic components propagate through the
processing steps applied to these data. This type of
uncertainty is generally expressed in accuracy models in
terms of variances and probabilities.
The third type of uncertainty is related to evidence theory. It
may be that the object classes are clearly defined and the
object data are accurate, but still the data do not contain
sufficient information to decide whether a particular object
belongs to a certain class or not. This case is well known in
remote sensing image classification. If a classification is
made to determine the landcover of an area, then the
landcover classes might be well defined. Still the spectral
information in the image might not give sufficient evidence
to assign the parcels with certainty to those classes.
In [Brimicombe 1992] the problem of uncertainty in GIS is
treated and proposals are formulated how to deal with it.
CONCLUSION
The introduction of information technology does not only
confront organisations with technical problems, but it does
have a significant organisational impact. Consequently it
requires a redefinition of the organisational structure and of
staff expertise and responsibilities. More direct is the effect
on the information flow through the organisation. This
concerns the technical and structural aspects of the
information flow, but also (and not the least) the definition
of the data and data processing models.
Tools should be made available to experts involved in this
task. For organisations dealing with Geo-Information these
tools should be embedded within the framework of a theory
dealing with the structure or syntaxis and semantics of GEO-
information and the structure of its processing models.
Several structural and sematic aspects of data modelling have
been explained in the previous sections. [Bedard e.a. 1992]
[Lee e.a. 1992] and [Brimicombe 1992] explain how tools
for some of these modelling tasks can be developed.
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