This lab was an easy one but I still discover a lot about the GIS software and the application of raster data model. Raster data is a combination of grid of cells or pixels with specific values. According to the lecture, raster data is excellent for present continuous phenomena, such as elevation & temperature, because the editor can simply mapping out the small cells and change them accurately. However, this simple data structured data model still has some disadvantages. Because of the revolution and geographical changing over time, we can always discover errors when we look close to the cells. Also, it is very different for spatial analysis because no one have that energy or passion to measure the changing phenomena all the time for an absolute accurate data. When we are using raster data model, we should remember there will always be obvious mathematically errors among the cells on a large scale map.
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