Pros and cons of vectors Advantages of vector

Pros and cons of vectors • Advantages of vector files include the following: • Vector files are useful for storing images composed of line-based elements such as lines and polygons, or those that can be decomposed into simple geometrical objects, such as text. More sophisticated formats can also store 3 D objects such as polyhedrons and wire-frame models. • Vector data can be easily scaled and otherwise manipulated to accommodate the resolution of a spectrum of output devices. • Many vector files containing only ASCII-format data can be modified with simple text editing tools. Individual elements may be added, removed, or changed without affecting other objects in the image. • It is usually easy to render vector data and save it to a bitmap format file, or, alternately, to convert the data to another vector format, with good results. • Some drawbacks of vector files include the following: • Vector files cannot easily be used to store extremely complex images, such as some photographs, where color information is paramount and may vary on a pixel-by-pixel basis. • The appearance of vector images can vary considerably depending upon the application interpreting the image. Factors include the rendering application's compatibility with the creator application and the sophistication of its toolkit of geometric primitives and drawing operations. • Vector data also displays best on vectored output devices such as plotters and random scan displays. High-resolution raster displays are needed to display vector graphics as effectively. • Reconstruction of vector data may take considerably longer than that contained in a bitmap file of equivalent complexity, because each image element must be drawn individually and in sequence.

Pros and cons of Rasters • • Pro’s The geographic location of each cell is implied by its position in the cell matrix. (for example bottom left corner) Due to the nature of the data storage technique data analysis is usually easy to program and quick to perform. The inherent nature of raster maps is ideally suited for mathematical modeling and quantitative analysis. (for example attribute maps) • Discrete data (such as forestry stands) is accommodated equally well as continuous data, (e. g. elevation data), and facilitates the integrating of the two data types • fixed resolution( can be good or bad) • “remembers” the start and end points of a line • Con’s • cell sizes determines resolution at which data is represented • It is especially difficult to adequately represent linear features depending on the cell resolution. • Since most input data is in vector form, data must undergo vector-to-raster conversion. Besides increased processing requirements this may introduce data integrity concerns due to generalization and choice of inappropriate cell size.