4. Types Of Gis

Types of GIS

Types of GIS •Vector GIS •Raster GIS •Hybrid GIS

Vector approach • It is used for storing information about the boundaries between areas. It is suitable for storing information about contour, road, and network analysis.

Raster approach • It is method of storing information about the interior of the areas. This raster model is appropriated for storing information about inside the boundary of a lake or inside the boundary of a forest.

In a vector model •

Objects (Point, lines) are defined by its positions with coordinates and topology. In this model spatial entities represent more or less they represent in the real world.

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Point item – one (x, y) coordinate

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Line – a set of (x, y) coordinates

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Polygon – a polygon is an area bounded by a closed loop of straight line segments.

Kinds of Vector Data Model • There are three kinds of vector data model, they are – The Spaghetti model – The Topological model – The Trangulated irregular network model

The Spaghetti Data model • Major bends are nodes • Points in between the bends are vertices. • Lines between vertices are called arcs.

Topological Data Structure

•Nodes are Two end points •There can be several vertices between nodes •There is only one arc between any two nodes

The Triangulated irregular network model

•TIN is a vector based topological data model that is used to represent terrain data. •TIN represents the terrain surface as a set of the interconnected triangular facts. •For each of the three vertices, x, y, z coordinates are encoded.

In a raster model • The space is regularly subdivided into cells (usually square in shape). The location of geographic objects or conditions is defined by the row and column position of the cells they occupy.

Hybrid GIS Hybrid GIS is the integration of Raster and Vector GIS.

Advantage and Disadvantages of Raster and Vector Data Models:

Vector Data Models: Advantages: • Good representation of data • Topology can be described for network analysis • Compact data structure • Efficient network analysis • Efficient projection transformation • Accurate map output Disadvantages: • Complex data structure • Expansive technology • Analysis is complex • Difficult overlay operations • Not compatible with remote sensing imagery.

Raster Data Model Advantages: • Simple data structure • Spatial analysis easy • Cheap technology • Easy and efficient overlaying • Compatible with remote sensing imagery • High spatial variability is efficiently represented • Simple of Own Programming • Same grid cell for several attributes Disadvantages: • Large data volume • Inefficient use of computer storage • Difficult network analysis • Inefficient projection analysis • Loss of information when using large cells • Less accurate (although attractive) maps.