Chapter 1:
What is GIS analysis? – Finding patterns in your data based on their geographical locations and finding relationships between features.
Understanding geographical features
| Discrete: As any point, the feature is either present or not; an actual location can be pinpointed. |
| Continuous phenomena: Can be found and measured anywhere. |
| Summarized by area: Data that applies to a certain defined area, but not any specific point within it. |
Representing geographical features
| Vector: Each feature is a row on a table, and areas are defined by x, y locations. | Typically discrete and summarized by area are displayed this way. Vector can also be used for continuous. |
| Raster: Features are represented as a matrix of cells. | Continuous often displayed this way. |
Understanding geographical attributes
| Categories | Groups of similar things |
| Ranks | Put features in order, from high to low |
| Counts | Total number of features on a map |
| Amounts | Any measurable quantity associated with a feature |
| Ratios | Relationship between two quantities shown by division of on by another |
Chapters 2 & 3:
Chapters 2 and 3 surprised me because they overlap heavily with statistics, expected, and art, unexpected. While I was aware that visual qualities would come into this because GIS can make maps, I didn’t expect so much, so early just about aesthetically and intuitively displaying data. The chapters explain how to make it most clear and obvious what your data means to your audience, even talking about how you might display differently for different groups depending on priority and familiarity, and these explanations make it clear how maps can be used to confuse viewers as well. During elections, I often see voter maps where most of the individual blocks are red but it is still a blue state; these maps are used by people wondering how that could be because the map doesn’t show the number of people in each block, leading to a perceived over-importance of large areas with small amounts of people.
Displaying too many categories at once can make a map difficult to use and understand because there is too much information being presented, but too few categories leads to an oversimplification of data that doesn’t give the full picture. The GIS user must decide on a case-by-case basis what on appropriate way to display the information is.