List advantages and disadvantages of vector and raster data for GIS. What kind of applications would each be most suited to?
Advantages of the raster model :
• A simple data structure—a matrix of cells with values, representing a coordinate, and sometimes linked to an attribute table.
• A powerful format for intense statistical and spatial analysis.
• The ability to represent continuous surfaces and perform surface analysis.
• The ability to uniformly store points, lines, polygons, and surfaces.
• Capability to perform faster overlays (than vector datasets) with complex data.
• The same cell-based structure is used to represent all feature types; therefore, all feature types may be treated the same. This uniform structure allows you to combine a variety of geographic features in one geoprocessing operation (for example, query, overlay, or expression). You can combine a surface (elevation) with area features (forestry), linear features (rivers and roads), and point features (wells) in the same analysis.
• The ability to compress the datasets using either a lossy or lossless compression.
• Compatible with remote sensing images and all results images of spatial data scanning.
• The application software is cheaper.
Disadvantages of the raster model :
• Inherent spatial inaccuracies due to the cell-based feature representation.
• Datasets can be very large.
• Projection and transformation cooordinat is not easily.
• Difficult in representation topology connections.
Advantages of the vector model :
• Need a small space or place for storage data (disc).
• One layer can be connected with or many attribute for saving the space of storage data.
• Easily makes connection between topology and network.
• Have a high spatial resolution.
• Graphic representation spasial data closely likes man-handed map.
• Very good in correction limits, apparent and clear for making administration maps and owned-lands.
• Easily for making projection and coordinates transformation.
Disadvantages of the vector model :
• Have a complex data structures.
• Data not easily for manipulates.
• Users cannot created owned programs for applications needed. In this case, a complex of the vector data structure and analysis and function procedures needs high capability because its more difficult and complicated— users must buy a software because of expensive technology.
• Needs a long time only for all the process. Vector data often out-of-date.
• Not compatible with remote sensing images data.
• Needs more an expensive software and hardware.
• Overlay vector layers with simultant needs a long time.