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In geography, a geographic object refers to an object that used to exist on earth or was actually present today, which can be clearly referenced using geodata . In the stricter sense of geography it is an identifiable part, in the broader sense of geoinformatics it is an identifiable feature of the earth's surface , as it is relevant for the cartographic representation on general geographic and thus also topographic maps or in geographic information systems .


A geographic object is a location localized on the earth's surface to which material or immaterial properties are assigned by user definition. This definition takes place in the subject-specific - geoscientific - context.

According to the terminology of the United Nations Expert Group on Geographical Names ( UNGEGN ), the term specifically refers to locations on the earth's surface, while this restriction does not apply to a topographical object .

Geoinformatics defines the spatial object as "a user-defined spatial phenomenon that can be modeled or represented."

In contrast to general definitions or descriptions ( phenomenology ) of structures in geography, these are specific individual locations that can be verified by their position ( geographical coordinates ). Collective terms such as mountain , island or bay describe a large number of similar objects. Single structure of these families of objects (object classes) such as the mountain Zugspitze , the island of Corsica or the Gulf of Gdansk are by their wording - their individual names , a Toponym  - identified and can easily through their unique earthly coordinates mapped detected and thus in world maps and atlases entered become.

Objects and facts

Geo-objects can be divided into two categories

  • Objects in the narrower sense are the concrete, inanimate and animate structures of our environment. These are sensually perceptible and in most cases visible. They can therefore be referred to as appearances or phenomena.
  • Facts describe the intrinsic characteristics of an object or its relationship to other objects. The facts of an object are about certain complex properties that are often not immediately perceptible. So there can be a soil object in an object model and the soil climate as an attribute of this object. This fact can be described as an independent object class. The spatial reference of facts is represented by the set of objects to which the facts are assigned.

Relationships between objects can also be shown in more detail with a specially created object. In this context, one speaks of an association class in object-oriented design .

Example: A central place that is connected to places of a lower order through commuters. This relationship between commuters can be specified in more detail in many ways: How many day and week commuters are there? How is the age structure of the commuters characterized? Which modes of transport are primarily used?

Dimensional classification

A distinction is made between

  • extensive geographical objects,
  • linear geographic objects
  • and point-like geographic objects.

An important factor when deciding which object is to be classified and how is the map scale , the representability and the recognizability.

Cartographic representation

Example: An extensive, square piece of forest in the natural dimensions of 10 m × 10 m has the following map dimensions in the following scales :

scale Card dimensions
1: 1,000 10 mm × 10 mm
1: 10,000 1 mm × 1 mm
1: 100,000 0.1mm x 0.1mm
1: 1,000,000 0.01mm x 0.01mm

With a drawing accuracy of usually 0.1 mm to 0.2 mm, it becomes clear that the wooded area is barely perceptible as a surface from a scale of 1:10 000. For this reason, only a punctiform representation is conceivable for these cases (if the forest is of such importance that it has to be represented). The selection of the objects that are represented at all, or their simplification, is called generalization .

Modeling of spatial objects

Geo-objects form elements for modeling the real world in geographic information systems ( GIS ). In general, a spatial object has four information technology dimensions - also known as components :

  1. geometry
  2. topology
  3. semantics
  4. dynamics

The object can be composed of elementary or arbitrarily complex. Geo- objects are described by geo-information .

Each object is unique, but is also part of an object class . The general appearance of an object is defined in the object class (e.g. whether it is point-shaped, linear or planar, which attributes describe it in more detail, which relationships are possible or necessary). Each object must be provided with a unique key or identifier for identification .

The ISO 191xx series of standards was created by ISO to standardize geographic information . In this context, the ISO 19109 standard regulates the rules for modeling spatial objects. The term general feature model is introduced for this.

Object modeling creates a structure by bringing the individual objects into context, linking them to a certain extent according to the laws of the real world. This ultimately results in the digital object model (DOM).

The modeling process and its documentation represent an important phase in the planning of a GIS. The digital object model ultimately has a decisive influence on the analysis and visualization options of the system.

The modeling in a GIS is done using different techniques. If the model is stored in a relational geodatabase , one speaks of data or structure-oriented modeling. Objects are mapped in the form of relations. During the runtime of the GIS application, a method-enriched and therefore more powerful virtual object model (based on a class hierarchy) can arise that only exists in the main memory and is responsible for the actual dynamics in the information system.


The geometry describes the spatial position of an object in 2 or 3-dimensional space. It includes all information on the absolute spatial position and extent of the spatial object based on a spatial reference system . In the case of continua, which are spatially unlimited, the geometric information consists of the position specification for numerical values ​​that change continuously from place to place (value fields).

Two models are widely used to describe geometry:

Grid model

Raster graphics

In a grid model , the area of ​​interest is divided into sub-areas with homogeneous semantics . In this context, one speaks of mosaic or tessellation . The most common form of tessellation is the division of the room into square or rectangular grid cells (grid). The semantics are represented by the numerical values ​​of the matrix elements. This gray value is not to be interpreted as a color, but as secondary information. The gray value of a raster cell in an infrared image stands for a semantic statement: e.g. B. for the vitality factor of plants.

The grid geometry is well suited for describing two-dimensional facts and for the layer concept. For example, specific gray values ​​result in the overlapping zones of two levels. The regular grid makes it an easy math exercise to calculate the total area of ​​the overlap area.

The essence of georelational models can be simulated in the grid model by pointers that refer from a grid cell to a factual file where detailed semantic information is available. In this context, the cell value plays the role of a key for a file or a section of a file. This pointer does not have to be defined for each grid cell. It is sufficient to refer to a centroid (internal key), which then references the external file.

Typical file formats are: BMP , TIFF , GIF , JFIF

Vector model

Vector models are based on points and lines. Areas are represented by closed polygonal lines . Vector models are also called linear models, while raster data represent an area model (in 3-dimensional space wire model versus volume model ).

The vector model is very well suited for the representation of linear objects (e.g. lines, traffic routes or river networks).

Vector data require less storage space than raster data, although very powerful compression algorithms are available for this. The semantics are assigned to the geometric elements. In contrast to the raster model, in which the gray value of a cell represents an implicit assignment, links must be explicitly defined in the vector model. In this context, one speaks of a georelational model.

The elementary parts can be put together to form higher-quality structures (graphic structures). Thematic attributes can also be linked at this level.

In vector models, section and area calculations are more complicated than in the raster model.

Typical file formats: WMF , Shapefile


The topology deals with those properties of the spatial reference that are independent of the metric. It characterizes the spatial relationships of spatial objects to one another and is therefore also referred to as the “geometry of the relative position”: the environment, inclusion, neighborhood or overlap are features of topological relationships.

Every metric space is also a topological space. The topological properties that remain unchanged during geometric rotation, translation or scaling are referred to as topological invariants.

Topological elementary structures are 0-cell (node), 1-cell (edge) and 2-cell (mesh). In the grid model, the topology is already implicitly defined by the cell matrix. It must be formulated explicitly in the vector model. Often topological relationships can be derived from calculations of the geometric model, but efficient topological modeling forms an important basis for data consistency.


The semantics complement the geometry. While geometry asks "where", the question of semantics relates to "what".

In contrast to the external spatial reference, the semantics describe all information related to the inside and the essence of the object. Semantics is the meaning of a spatial object in a subject-specific context. This meaning arises in spatial object models through belonging to a certain object class. It is refined by the interplay of class-related, non-spatial attributes. These can be of a qualitative or quantitative nature. Quality refers to information on the type or condition of an object. Quantity, on the other hand, focuses on quantity, value, intensity or size.

The semantics result from the structuring of the technical data and the consideration as a whole. Another special feature of semantics is that it is by no means free of subjectivity . The user associates certain features with an object, which are predetermined by his living conditions or his specific view of the object.

However, one can exclude the semantics in the sense of the individual perception and use the term as a representative of the meaning given to an object with regard to a specific question through technical attributes.


The term dynamics is used to characterize all changes in geographic objects over time. The intensity of dynamic modeling depends on whether the goal of the system is a “snapshot” (static) or dynamic behavior is in the foreground.

Modeling on topics such as currents, transports, spatial development etc. direct their attention to temporal changes. Considerations for the introduction and visualization of dynamics naturally play a crucial role in these cases.

Examples of spatial objects

Model of a stretch of river
  • Geometry: Description of the stretch of water with a line of lines.
  • Topology: The stretch of water ends where the river flows into the Danube.
  • Semantics: measurement and observation values ​​for water level, number of plant species, etc.
  • Dynamics: Changes in the geometry and some features of the semantics due to the erosion of the running water.
Thematic attributes are subject to the selection of the subject-specific context and also influence the geometric representation. From a hydrological point of view, a very precise geometric description of the course of the water with all river bends, changes in width and depth is of interest. From a limnological and water ecological point of view, only a rough geometric description of the course of the water is of interest. More important is z. B. the proximity to biotopes (cf. Streit, Geoinformatik script, version 3.4, chapter 4).
From an economic point of view, it may be of interest whether the river can be used as a transport route for shipping.
Model of a climate station for measuring meteorological parameters
  • Geometry: Description of the spatial location of the climate station using geographic coordinates.
  • Topology: The climate station is located in the municipality of Groß Gerungs.
  • Semantics: measurement data for air temperature, precipitation, air pressure etc.
  • Dynamics: Temporal variations of the meteorological parameters.
Information on the geometry of the climate station can be limited to the coordinates of a point in a spatial reference system. The semantics and their temporal variation are much more complex in this example: series of measurements of various parameters are automatically recorded by the station at set intervals and of course must be available in the digital object for analysis. The thematic cartographic representation should definitely be supplemented with diagrams. Height above sea level and terrain exposure are of particular importance for climate stations. This information should always be "at hand" for analysis and presentation and should also be included as metadata for all records of the climate station.
Model of a biotope
  • Geometry: Border of the biotope with a closed line (polygon).
  • Topology: the biotope is cut by a road.
  • Semantics: biodiversity , biochemical cycles, predominant soil type, etc.
  • Dynamics: Change in topology by abandoning the street and renaturing the former traffic areas.
The semantics of a biotope are demanding in modeling. The biotope is the spatial representative of a biosystem (ecological impact structure). The complex functional relationship of the biofactors (animals, plants, humans) interacting in the biotope gives an idea of ​​the degree of difficulty of efficient data modeling.


  • N. Bartelme: Geoinformatics: models, structures, functions. Springer, 2000
  • Ralf Bill: Basics of Geo-Information Systems, 5th, completely revised edition Wichmann, 2010
  • G. Hake, D. Grünreich, L. Meng: Cartography. de Gruyter, 2002
  • Peter Robineau: Semantics in the vector model. Diploma thesis:
  • Ulrich Streit: Introduction to Geoinformatics. Lecture notes, version 3.4

Web links

Individual evidence

  1. United Nations Expert Group on Geographical Names [UNGEGN], Standing Committee on Geographical Names [StAGN] (Ed.): German glossary on toponymic terminology. German dictionary for the technical language of geographic naming . Version 2002 edition. Frankfurt 2002 ( [PDF; 861 kB ; accessed on August 8, 2008] English: Glossary of Toponymic Terminology .). German glossary of toponymic terminology. German vocabulary for the technical language of geographical naming ( memento of the original from March 15, 2014 in the Internet Archive ) Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice.  @1@ 2Template: Webachiv / IABot /
  2. 100 feature, geographical / object, geographical. StAGN, 2002, p. 20.
  3. 104 feature, topographic / object, topographical. StAGN, 2002, p. 21.
  4. ^ Geographical object. (No longer available online.) In: Geoinformatik-Service, Lexikon. Professorship for Geodesy and Geoinformatics (GG), University of Rostock , archived from the original on June 30, 2007 ; Retrieved August 8, 2008 . Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. @1@ 2Template: Webachiv / IABot /
  5. 053 feature class / object class. StAGN, 2002, p. 15.
  6. after Hake, Grünreich, 1994, p. 8.
  7. from Streit: Geoinformatik script
  8. a b Hake, Grünreich, 1994, p. 10.
  9. cf. Bartelme, 2000, p. 125.
  10. Bartelme, 2000, p. 54.
  11. a b c from Streit: Geoinformatik script. Chapter 4.