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n or
accuracy of the captured landscape objects (differences in
the scale of the DLM's). Also, there exists a difference
between the data representation of the different informa-
tion systems. The data can be made available in a graphic
format (e.g. DXF), in a layer format (e.g. ALK) or in
an object oriented format (e.g. SAIF). Therefore, we have
to convert the corresponding data models into a uniform
model. We have chosen an object oriented data model to
represent spatial objects because of the natural representa-
tion of real world objects in contrast to their representation
in relational databases [Riekert 1993, L.Raynal, B.David
& G.Schorter 1995, Fritsch & Anders 1996].
DINER
GeoObjectComplex
Thematic
Q
RNC
| Geometry | |ReferenceSystem |
Figure 7: Description of the spatial object class
/\ ; Attribut
Thematic
Name : String
Value : String
Figure 8: Thematic class
Our object oriented data model used is derived from
the data model of the Canadian standard SAIF (Spa-
tial Archive and Interchange Format) described in [Spatial
Archive and Interchange Format: Formal Definition Re-
lease 3.2 1995]. In the following figures we use the
OMT-Notation (Object Modeling Technique) described
in detail in [Rumbaugh, Blaha, Premerlani, Eddy &
Lorensen 1991]. In the OMT-Notation the rhomb symbol
represents the object oriented feature aggregation (has.a
relation) and the triangle symbol represents the feature
inheritance (is.a relation). Our developed data model
uses container classes provided by the used object oriented
database system. Geographic objects are modelled by the
class GeoObject (figure 7). Parts of the class GeoObject
are the classes Thematic and SpatialRelation. The class
Thematic (figure 8) is implemented as a associative map
and represents the non-spatial attributes of a geographic
object. The class SpatialRelation is used to represent the
spatial attributes and describes the kind of geometry and
reference system which belongs to the geographic object.
The class Geometry shown in figure 9 provides the ba-
sic geometric objects described by the classes Point, Line,
Area and GeometryComplez. The class GeometryComplez
93
is used to build geometries, which are composed of the
classes Point, Line and Area. Every object from the class
Line is defined by two objects of the class Point (start
point and end point of the line) and any number of addi-
tional points depending on the type of line interpolation
(e.g. polygon, spline). An object of the class Area is de-
scribed by at least one border line of the area (areas with
holes includes two or more border lines), which is modelled
by the class Line.
Area
Point (abstract)
2+
size_of_area
Figure 9: Geometry class (point, line, area)
5 METHODS
We can distinguish the following methods which every spa-
tial object in the database has to provide :
e relational operators (figure 10) for
> semantic relations (e.g. typeof, is_a)
The interpretation process has to be able de-
termining the kind of object it is looking at.
For example, with this method we are able
to determine the semantics of a spatial object
(e.g. road or building).
> structural relations (e.g. part_of, has.a)
In order to get information about the compo-
sition of an object it provides methods to get
all objects, which are a part of this spatial ob-
ject, or all objects to which the spatial object
belongs.
> topological relations (e.g. inside, disjoint,
asically we need information about the topo-
logical relations of a spatial object because we
have implemented methods to test all topo-
logical relations as described in [Egenhofer &
Herring 1990].
> neighbourhood relations (e.g. lies beside,
near_to)
The methods for the neighbourhood relations
are not implemented at the moment. They
will be used to deduce relations which cannot
be determined only by topological relations.
For example, the database query Retrieve all
buildings which lie beside road A. This can only
be solved using geometrical relations. Another
problem is, that there exists no mathematical
definition of this kind of relation.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996