Chapter 1
Chapter one introduces GIS and how it is used to analyze geographic features. The most common analysis people do includes mapping the location, density, and change. GIS analysis is identifying and studying geographic relationships and patterns through maps and data layers. Analysis begins with a question. Your method of analysis depends on what question you have and how you are presenting the results. It is important to know what data you have and what data you need to calculate and create. Studies using approximate data are quicker, but those requiring accurate data take more time. I really like the example the chapter gives in describing the difference: if you are looking at assaults in a city, it will be a quick study, but if the information is used for evidence in a trial, you will need the precise measurements for the locations and numbers in a specific area over a period of time. The results of the GIS analysis can be displayed as a map, table, or chart. It is important to not only understand how GIS works but also what geographic data is being displayed. Discrete locations and lines do not have a distinct location, such as parcels of land value. Continuous phenomena can be measured at any location, so there is data everywhere you are mapping. If the data is not used in an area with boundaries, GIS uses interpolation on a series of points. Interpolation is assigning values to the area between the points. The third type of data is summarized data, which represents the density of certain features within a boundary, such as the number of households within each county. Geographic features can be represented by vectors and rasters. With vectors, features are defined with an x,y coordinate. With rasters, features are represented by multiple cells.
Chapter 2
Chapter two discusses how to prepare and map your data. Through observing a distribution of features, rather than individual ones, you can find patterns in the data. GIS mapping can be used to show where features are and aren’t, and the different types of features. The audience and issue determine how you present your mapped data. Every feature will need geographic coordinates and an identifying code. For individual locations, GIS will put a symbol at the given point. For linear features, GIS draws lines connecting each point. For features within an area, GIS draws an outline. Mapping subsets is common for individual locations rather than linear features because highlighting only linear features doesn’t provide any information about the surrounding areas. You can also map features by category, with each category having a specific symbol. GIS will store a value for each feature in the layer and an assigned symbol for each value. It may be helpful to have separate maps for each data set, otherwise it can get messy if there is too much data. You should keep the maximum number of categories to seven, as it can be difficult for most people to interpret if there are more. You can also group categories if you need to show a lot of data, but keep it to one map. There are three ways to group categories into detailed and general: assign each record two codes, create a table with a record for each detailed code and corresponding general code, or assign one symbol to each detailed category within the general category. It is important to include references such as major highways or rivers so the map can be more meaningfully interpreted. These references should use lighter colors so they don’t take away from the actual data.
Chapter 3
Chapter three explains the importance and process for mapping the most and least. Mapping the most and least can help people solve problems or see relationships. You can map discrete features, continuous phenomena, or data summarized by area. Discrete features are locations, linear, or areas. Continuous phenomena are defined as areas of continuous values. Data summarized by area uses shading based on its value. Maps can be used to find patterns or present patterns that have already been identified. If you want to find patterns, the data needs to be displayed in many different ways and with great detail. If you are presenting previously found patterns, you need only to create a map with generalized data. For mapping the most and least, you assign a symbol to each feature based on a quantity: counts or amounts, ratios, or ranks. A count is the number of features and the amount is the value associated with each feature. Ratios show the relationship between two quantities to even out the differences between large and small areas. Some examples are densities and averages. When summarizing by area, ratios should be used. Ranks show relative values in order from high to low. Ranks can be used, for example, when seeing which soil type in an area is best for growing crops. Classes are used when representing quantities on a map. The four ways to group data into classes are natural breaks, quantiles, equal intervals, and standard deviation. Natural breaks are set by natural groupings of data values. Quantiles have an equal number of features within each class. An equal interval has an equal difference between the high and low values. Standard deviation has features that are placed based on how much the value varies from the mean, which is calculated by the GIS.