2.4. Raster Data

 The raster data model represents the Earth’s surface by means of an array of two-dimensional grid cells called pixels. Each pixel has an associated value, which represents the characteristics of the spatial phenomenon. These cells or pixels are used as building blocks for creating points, lines, areas, networks, and surfaces. Raster data represent points by single cells, line by sequences of neighbouring cells, and areas by collection of contiguous cells. The JPEG, BMP, and TIFF file formats are based on the raster data model. All liquid crystal display (LCD) computer monitors are based on raster technology as they are composed of a set number of rows and columns of pixels. Although pixels may be triangles, hexagons, or even octagons, square pixels are most common. Raster models are useful for storing data that varies continuously, such as an aerial photograph, a satellite image, a surface of chemical concentrations, or an elevation surface. 

Elements of Raster Data Model

n  Cell value - 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.

n  Cell size - The cell size determines the resolution of the raster data. The ground area covered by a single pixel determines the spatial resolution of the raster. Resolution is determined by measuring one side of the square pixel. A raster with pixels representing 10 metre length and 10 metre breadth will have a spatial resolution of 10metre. Raster images with a small pixel size, covering a small area are called ‘high resolution ‘images. While Raster images with a large pixel size, covering a large area are called ‘low resolution ‘images. Thus, the amount of detail in a raster image depends upon the size of the pixel. Smaller the pixel, greater resolution and larger the pixel lesser the resolution. The size of the pixel also determines the size of the raster file. This is why high-resolution images are bulkier than low resolution images.

 

n  Raster bands -   A raster dataset may contain one or more layers called bands. A band is represented by a single matrix of cell values, and a raster with multiple bands contains multiple spatially coincident matrices of cell values representing the same spatial area. For example, a colour image has three bands (red, green, and blue) while a digital elevation model (DEM) or a scanned map has one band (holding elevation values), and a multispectral image may have many bands. Most satellite imagery has multiple bands, typically containing values within a range or band of the electromagnetic spectrum. In the case of multiple bands, each band usually represents a segment of the electromagnetic spectrum collected by a sensor. Bands can represent any portion of the electromagnetic spectrum, including ranges not visible to the eye, such as the infrared or ultraviolet sections. 

n  Spatial reference - Each pixel in a raster is associated with a specific geographical location.  In the case of scanned maps this spatial reference is provided by means of georeferencing. Georeferencing is the process of assigning real-world coordinates to each pixel of a raster. It is the process of adding geographic information to the image so that GIS or mapping software can 'place' the image in its appropriate real world location. Raster data must have the spatial reference information so that they can align spatially with other data sets in a GIS.

            Types of Raster Data

Raster Data is further classified into various types; they are:

n Satellite Imagery  - Remotely sensed satellite imagery are recorded in raster format. The pixel value in a satellite image represents light energy reflected or emitted from Earth’s surface. By analysing the pixel values, an image processing system can extract a variety of themes from satellite images.

n Digital Elevation Model(DEM) - A digital elevation model (DEM) consist of an array of uniformly spaced elevation data. It is the computer graphic representation of any terrain surface.

n Digital Orthophotos - A digital orthophoto is a digitized image prepared from an aerial photographs or other remotely sensed data. In digital orthophotos, the displacement caused by camera tilt and terrain relief has been removed. A digital orthophoto is geo-referenced and can be used with topographic and other maps.

n Binary Scanned Files - The data in these type of files are stored in binary format (value of 0 and 1). These type of image files are mostly monochromatic, i.e. they are only available in black and white.

n Graphic Files - In this type of raster data we can include maps, photographs and images which can be stored as digital graphic files. Major popular graphic files in raster format are GIF (Graphic Interchange Format), TIFF (Tagged Image File Format), JPEG ( Joint Photographic Experts Group).

Raster Resolution

            The ground area covered by each pixel determines the spatial resolution of the raster. The size of the cells in the raster data model determines the resolution at which features can be represented. Resolution is determined by measuring one side of the square pixel. A raster with pixels representing 10 metre length and 10 metre breadth will have a spatial resolution of 10metre. Raster images with a small pixel size, covering a small area are called ‘high resolution ‘images. While Raster images with a large pixel size, covering a large area are called ‘low resolution ‘images. Thus the amount of detail in a raster image depend upon the size of the pixel. Smaller the pixel, greater resolution and larger the pixel lesser the resolution. The size of the  pixel also determines the size of the raster file. Smaller cell sizes result in larger raster datasets to represent an entire surface; therefore, there is a need for greater storage space. This also results in longer processing time. The cell size determines how coarse or fine the patterns or features in the raster will appear. The smaller the cell size, the smoother or more detailed the raster will be. If a cell size is too large, information may be lost, or subtle patterns may be obscured.

Data Compression

            While storing the raster only the value of the cell is stored and not the column and row number. Even when only the cell values are stored the size of the data becomes enormous. This data size creates severe performance problems. Data compression is therefore important in a raster. The most common methods used for the compression of raster data are, 1. Run length encoding, 2. Chain coding and 3. Block coding

            Run length encoding is the method of reducing a row of cells with the same value to a single unit. Thus cell of the same value in a row may be compressed by stating the value and their total. For Example - The line of data AAAAAABBBBCCCCCCCCC can be compressed as 6A4B9C

            In chain coding, raster data is compressed by storing only the cells that lie on the outer border of a homogeneous area.

            Block coding is a method which subdivides an entire raster image into hierarchical blocks. The cells of homogeneous quadratic areas are stored as one unit or block.

 


 


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