2. Modelling the Real World - Data Types and Models - Vector and Raster

 The Earth’s surface is really complex, and hence, it is exceedingly difficult to represent the real-world features in a Geographical Information System. So, we use to simplify the complex real-world features before we input them into GIS. This simplified features that that we input into a GIS is called an entity.

            Real world features are of two basic forms: Objects and Phenomena. Objects are discrete, identifiable units that have some sort of spatial reference, usually in the form of geographic coordinates. They have well defined boundaries. For example, houses, factories, roads, rivers, or lakes. Phenomena are distributed continuously over a large area. For E.g. Terrain, temperature, rainfall. In GIS, the real world is represented in these two basic forms. Thus, there are two distinct approaches of representing the real world in geographic databases. These two models that help to represent complex earth’s surface features in a simplified forms are,

1. The object-based model or vector data model and

2. Field based model or raster data model

Modelling of Spatial Objects

Object based model - As explained earlier, objects are discrete, identifiable units that have some sort of spatial reference and have well defined boundaries. A vector data structure is a computer implementation of an object-based model.  Vector data model uses coordinates to store the shape of spatial objects much as if they were being drawn on a map by hand. It uses the geometric shapes of point, line, and polygon to represent spatial features. A point has zero dimensions and has only the property of location. Each point is stored as a coordinate pair (X, Y). A point is also called a node. Wells, benchmarks, and location of cities and towns are examples of point features. A line is one dimensional and has the property of length. A line has two end points. A line is also called an edge, link, or an arc. Roads, streams, and contours are examples of line features. A polygon is two dimensional and has the properties of length and breadth.  A polygon is made of connected lines and may share boundaries with other polygons. Forests, land parcels, and water bodies are represented with the help of polygons. The spatial information and the attribute information for these models are linked via a simple identification number that is given to each feature in a map. 

 

Depending on the nature of the objects and the geographical scales at which they are recorded spatial objects are represented as graphical elements of points, lines, and polygons in vector (object-based model).

Field based model - The field-based model represents geographic space as populated by one or more spatial phenomena that vary continuously over space.  Raster data structure is a field-based model. The raster data model represents the Earth’s surface as an array of two-dimensional grid cells called pixels, with each cell having an associated value, which represents the characteristics of a spatial phenomenon. These cells or pixels are used as building blocks for creating points, lines, areas, networks, and surfaces. The JPEG, BMP, and TIFF file formats are based on the raster data model. Although pixels may be triangles, hexagons, or even octagons, square pixels are most common. Raster models are useful for storing data that varies continuously, as in an aerial photograph, a satellite image, a surface of chemical concentrations, or an elevation surface. 

Each cell in a raster carries a single value, which represents the characteristic of the spatial phenomenon at the location. Cell values can be either positive or negative, integer, or floating point. Cells can also have a ‘No Data’ value to represent the absence of data.

 

Comparison between Raster and Vector Models

            The raster-vector approaches are two alternate methods for storing and representing spatial phenomena. As models they have relative strengths and weaknesses in representing real world features. The advantages and disadvantages are listed below:

 

Advantages
Vector data format	Raster data format
1. Data can be represented at its original resolution and form without generalization.	The geographic location of each cell is implied by its position in the cell matrix.
2. Graphic output is usually more aesthetically pleasing.	Data analysis is typically easy to program and quick to perform.
3. Accurate geographic location of data is maintained.	Good for complex analysis and efficient for overlays
4. Topology information can be stored with vector data models.	Works best for surface modeling and for applications where discrete features are not important
Vector data provides an increased ability to alter the scale of observation and analysis.

 

Disadvantages
Vector data format	Raster data format
1. The location of each vertex needs to be stored explicitly.	The cell size determines the resolution at which the data is represented.
2. For effective analysis, vector data must be converted into a topological structure, and any updating or editing of the vector data requires re-building of the topology.	Linear features and paths are difficult to display and depends on spatial resolution.
3. Display of continuous data as a vector require substantial generalization.	Raster datasets can become exceptionally large because a value must be recorded and stored for each cell in an image.
4. Spatial analysis and filtering within polygons is impossible	Most output maps from raster systems do not conform to high-quality cartographic needs.