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Understanding Raster Data

Excellent raster data to represent the boundaries are changed gradually, such as soil type, soil moisture, vegetation, soil temperature and so on. The main limitation of raster data is the large size of the file; the higher the resolution of its grid-the larger the file size and is highly dependent on the available hardware capacity. Each data format has advantages and disadvantages.

Raster data (also called grid cells) is data generated from remote sensing systems. In the raster data, geographic object is represented as a grid cell structure called a pixel (picture element). In the raster data, resolution (visual definition) depends on the size of its pixels. In other words, a pixel resolution depict actual size on the earth’s surface represented by each pixel in the image. The smaller the size of the Earth’s surface are represented by a single cell, the higher the resolution.

Selection of data format used depends on the intended use, the available data, the volume of data generated, the desired accuracy, and ease of analysis. Matrix raster has a geometrically regular shape and has ordered automatically, therefore each pixel cell position or positions do not have to be recorded one by one. If everything is recorded even be a waste of memory unnecessary.

This is what distinguishes it from vector data. Nevertheless, some local coordinates [in units of column lines] (which serve as ground control points or GCPs) in the raster data set is needed to bind (me-register) this grid system to a desired coordinate system. Meanwhile, to read (content) raster data file correctly, the data recording sequence must be observed.

Raster has characteristics that can distinguish them from each other. These characteristics can include spatial resolution, temporal, spectral, orientation (to the north), the existence of zone (area where the pixel-pixel have the same identification number), the domain of pixel values ​​(intensity), and the coordinates of the pixel.
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Figure 2. Example of Data Display Coordinate System Raster After Transformation

In the coordinate system like this (post-transformation), the origin of coordinates (X0, Y0), the raster data is located in the lower left corner point. In addition, there are a number of M column (abscissa) and the N line (ordinate) in accordance with the direction of each coordinate axis. Each pixel or grid cell has a width and height values ​​b (according to the spatial resolution). So by paying attention to these values, the coordinates of the point of the other corners are left-over (Xo, Yo + N * b), the bottom-right (Xo + M * a, Yo), and right-upper (Xo + M * a, Yo + N * b).

By utilizing the principle of the same count, it can be seen that the coordinates of the center point pixel row i and column j is (Xo + (j-0.5) * a, Yo + (i-0.5) * b. The boundaries of pixel row i and column j is (Xo + (j-1) * a <X <Xo + j * a) for X, and (Yo + (i-1) * b <Y <Yo + i * b) for Y.