Vector data is considered to be a more traditional method for cartographic representation, it delivers a representation that is sharp, clean and scalable. In comparison between the two forms of data, there are particular advantages and disadvantages of use.
In this vein, raster representation are more closely linked with representing physical properties or phenomena found on the globe. Raster datasets are useful in the storage a presentation of continuous data, such as weather events and climate projections, or elevation surfaces. But provide a geographical context and now we can position this correctly on a globe and then run analyses off the cell values which can be considered colour wavelength bands. At a simple level, satellite imagery can be considered a digital photograph of the surface of the globe, each cell indicates a particular colour. Satellite imagery provides a perfect context example of this image vs. The main point of difference between the digital photograph and the GIS representation is that in the GIS there is accompanying data detailing where the cells can be found on a globe and how big these cells can be.
Here each cell, which in this instance is referred to as a pixel, corresponds to a particular colour value. When transferred into a GIS setting, the cells in a raster grid can potentially represent other data values, such as temperature, rainfall or elevation. In an alternate sense, we can consider a digital photograph as an example of a raster dataset. Raster data provides a representation of the world as a surface divided up into a regular grid array, or cells, where each of these cells has an associated value. Ubiquitous online mapping portals, such as Google Maps and Open Street Maps, present data in this format. Vector data is extremely useful for storing and representing data that has discrete boundaries, such as borders or building footprints, streets and other transport links, and location points. These points can be joined, in a particular order, to form lines or joined into closed areas to form polygons. At its simplest level, vector data comprises of individual points stored as coordinate pairs that indicate a physical location in the world. Data in this format consists of points, lines or polygons. Vector data is what most people think of when they consider spatial data. Both of these methods present data in their own format, with their own advantages and disadvantages. Note: The values in the above examples are arbitrary and do not correspond to any specific polygon or encoding method.When we come to depict any spatial data in GIS, from physical assets and locations to real-world events and trends, there are two differing systems to display data Raster and Vector representations.
DEFINE RASTER APPROACH SERIES
The encoding consists of a series of nodes in the quadtree, each representing a quadrant and its color value. Quadtree encoding: Divide the grid into four quadrants recursively until each quadrant contains only one color value.For example, "3 black, 2 white, 1 black" would represent a series of three black cells, two white cells, and one black cell in a row or column. Run-length encoding: Encode each row or column of the grid as a series of alternating values representing the color of the cells.A value of 1 represents inside, and a value of 0 represents outside. Bitmap: Assign a binary value to each cell of the grid indicating whether the cell is inside or outside the polygon.To represent a simple polygon on a coarse grid using different raster data encoding methods, we can use the following methods: Points are represented as single coordinates, lines as pairs of coordinates, and areas as a series of connected lines that form a closed shape. The computer stores the mathematical equations that define these objects and uses them to render the entities on the screen. The vector approach, on the other hand, represents entities as mathematical objects such as points, lines, and polygons. Point entities can be represented by a single colored pixel, line entities by a series of colored pixels in a row or column, and area entities by a collection of colored pixels that form a closed shape. Each pixel is assigned a color value, and entities are represented by assigning colors to the appropriate pixels. The raster approach represents entities by dividing the screen or image space into a grid of pixels or cells.
0 kommentar(er)
