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Which of the following statements are true for vector data models in GIS. A. It is a simple data model and has low cartographic output quality B. It is a compact data structure and has high cartographic output quality C. It is characterized by a case of data processing D. It is cheap data collection process as it was less expensive technology

Which of the following statements are true for vector data models in GIS. A. It is a simple data model and has low cartographic output quality B. It is a compact data structure and has high cartographic output quality C. It is characterized by a case of data processing D. It is cheap data collection process as it was less expensive technology Correct Answer B only

The data model in GIS:

  • In order to visualize natural phenomena, one must first determine how to best represent geographic space.
  • Data models are a set of rules and/or constructs used to describe and represent aspects of the real world in a computer.
  • Two primary data models are available to complete this task: raster data models and vector data models.

Key Points

Vector data model:

  • Vector data/layers in GIS refer to discrete objects represented by points, lines, and polygons.
  • Lines are formed by connecting two or more points and polygons are closed set of Lines.
  • Layers represent geometries that share a common set of attributes.
  • Objects within a layer have a mutual topology.
  • Vector sources include digitized maps, features extracted from image surveys, and many more.

Important Points

Advantages:

  • Data can be represented at its original resolution and form without generalization.
  • The graphic output is usually more aesthetically pleasing (traditional cartographic representation)
  • Since most data, e.g. hard copy maps, is in vector form no data conversion is required.
  • The accurate geographic location of data is maintained.
  • Allows for efficient encoding of topology and as a result more efficient operations that require topological information, e.g. proximity, network analysis.

Disadvantages:

  • The location of each vertex needs to be stored explicitly.
  • For effective analysis, vector data must be converted into a topological structure. This is often processing intensive and usually requires extensive data cleaning. As well, the topology is static, and any updating or editing of the vector data requires re-building of the topology.
  • Algorithms for manipulative and analysis functions are complex and may be processing intensive. Often, this inherently limits the functionality for large data sets, e.g. a large number of features.
  • Continuous data, such as elevation data, are not effectively represented in vector form. Usually, substantial data generalization or interpolation is required for these data layers.
  • Spatial analysis and filtering within polygons is impossible
  • It is a compact data structure and has high cartographic output quality.

Therefore, it is clear that option 'B' is correct about the Vector data model.

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