4.4: Principles Of Database Management – Raster

As described in Chapter 1, the raster data model aligns the Earth’s surface into a grid of columns and rows. Cells, or pixels, the building blocks of the raster data model, form at the intersection of the columns and rows, and each cell contains a single attribute value, representing the condition of a specific portion of the Earth’s surface. That means that a single raster layer only contains the values for one specific attribute across space. That last point is important because raster layers fill space. Their attributes occur everywhere in the study area; there are no blank spaces. Empty areas get a “0” value, but every pixel gets a value. If you need more than one attribute, you construct multiple layers, each containing a single specific attribute for the same area. Conceptually, it is a simple model. As in Figure 4.3, your study area is divided into cells, and each cell of each layer has a single attribute that represents that area.

Figure 4.3: Raster image. Image by Mike Tuck.

There are many ways—some more complex than others—the raster data model may be stored. The two general categories are regular and irregular. The regular structure is conceptually simple, and includes two types: full raster encoding and run-length encoding. Full raster encoding creates a data file that records the attribute value for every pixel. It’s as though you read an image’s pixels like a book, starting in the upper left corner and reading from left to right and downward row by row. The data file looks a bit different. It records each pixel’s attribute value on a separate line, so if you had an image with 640,000 pixels, your data file would have 640,000 lines, making it a very long data file. Figure 4.4 is a simplified example.

Figure 4.4: Full raster encoding. This figure is the beginning—just the first three rows—of the data file for the image in Figure 4.3. Color is added to highlight the different attribute values.

Run-length encoding is more efficient than full raster encoding. Since the same values often occur in runs across several cells, run-length encoding enters the attribute values as pairs: the first number is the run length and the second number is the cell’s value. This substantially reduces file size especially if contiguous pixels have the same value. Contrast Figure 4.5 with Figure 4.4.

Figure 4.5: Run-length encoding. This figure also depicts the first three rows of Figure 4.3. Compare run-length encoding with full raster encoding (Figure 4.4). Color is added to highlight the different attribute values.

Irregular raster data structures, like quadtree and others, are more complex, proprietary, and beyond the scope of this e-text. They usually make file size smaller and provide ways to store raster data for quick retrieval.