CH 1
This book (site it) defines GIS analysis as “a process for looking at geographic patterns in your data and at relationships between features.” This chapter walks you through exactly what GIS analysis looks like. Sometimes it’s just creating the map, while other times it is a lot more complex by adding layers and different data that’s been previously collected. Frame the question, understand your data, choose a method, process the data, and look at the results are the steps the book suggests a person should take when running the analysis. Different methods could make the information easier to gather but slightly vague or more tedious to gather and precise. It is up to the creator to decide which is better for the question that they are trying to answer. The book also walks the reader through the types of maps and the types of data that can be shown through mapping. These include categories, ranks, counts, amounts, and ratios. Categories group similar things together and determine if there is a geographical pattern. Ranks order the data from highest to lowest. An example of this could be precipitation in a given region or libraries within each school district. Counts and amounts are expressed on a map as the actual value. This might be universities in a state or grocery stores in a county. These allow the viewer to understand the scale at which the feature is prevalent in the space. Ratios show a direct relationship between two pieces of data. Continuous values would be projected using ratio counts and amounts. These features will have a range of data so it is considered continuous. Noncontinuous values are usually quantitative. These would be categories or ranks. GIS analysis allows you to individualize the data by selecting and calculating the exact type of data that you want to express.
CH 2
GIS analysis allows you to layer information to identify possible correlations between two variables. This chapter is entirely about mapping and how to use mapping to identify important pieces of information. It is so interesting to me that so much information has already been entered into the GIS database. Each time I read something else I realize that GIS is so big and it’s something I have not been privy to at all. When creating a map there are so many possibilities and GIS allows you free reign to adapt and curate the perfect map for the information that you are trying to display. You can map a single type which would be something like roads or forests. You can type and subtype layers of your map. The example in the book is all crimes are a type that would be entered into GIS. Then you can subtype the crimes into different categories. This makes the map more or less detailed based on what is needed. Category mapping is using different colors to differentiate within a category. This could be stored with the subcategories being which stores. The book uses roads and crime as an example. The book says that you should not display more than seven categories because otherwise it could become blurred and people may have a hard time distinguishing between different shades of colors. Mitchell goes on to discuss that it is important to use scale when creating a map. Using too many or too few categories can make the map confusing or too vague for the viewer. Categories can be grouped in different ways. One way is to give each record a general and detailed code that can be used when creating the map. The second option is to create a table for each detailed code within the general codes. This one is more tedious but it is easier to edit once it has been input. Assigning symbols to each piece of data is the third option. This is the least invasive for the dataset, but it does not save in the dataset itself. The biggest thing to consider when picking symbol designs is that color is easier to distinguish than shape, and using a variety of widths and colors will make reading the map easier.
CH3
Chapter three begins by describing different types of maps and the different figure types. “Discrete features can be individual locations, linear features, or areas.” These discrete features are represented with different levels of a single dot. The example given is smaller and bigger dots representing the locations of businesses by number of employees. Continuous features can be an area or surface with continuous values. This might look something like a COVID-19 infection map. Continuous maps usually have shades of color to display the values that they are trying to represent. The person creating the map must know what type of map they want. What question are you trying to answer? It is also important that the numbers that are being represented are accurate and the values are understandable to a viewer. Mitchell goes on to describe how to create ranks and classes in the GIS analysis. Standard classifications are natural breaks, quantile, equal interval, and standard deviation. The best scheme will be evident based on the type of data and the goal of the map. Natural breaks can be determined by viewing a chart of the data and seeing a jump in the intervals. That would be a good time to split the data. Quantiles might cause the data to present in a deceiving manner if this is not the best classification. It displays the data and then identifies the quartiles within the data. Equal intervals break down the range into four even groups to display where the majority of the figures are. The standard deviation is decided based on the intervals away from the mean. Standard deviations would be good for seeing which features are outliers and which are above and below the mean. This type does not show the actual values which would not be beneficial in certain situations. Outliers can be dealt with in different ways depending on what they might represent. In some cases you can use a different symbol to identify outliers, another example would be to group them in their class or a class with other outliers. Mitchell goes on to outline a way to determine the best map that is available. This job is subjective, but it’s important to know the pros and cons of the different types.