Ch. 1
Chapter 1 laid some groundwork for understanding and using GIS Analysis. This section focused on geographic features and data. Some of these topics were: how to use data and decide how you want to represent your data, understanding geographic features and ways to represent them, utilizing data tables, summarizing, etc. Another topic that was addressed that I am excited to learn more about is coordinate systems. It seems that they are very important to understand that your data will appear accurately.
Something I found important was the different types of geographical features. Understanding that there is not just one type of feature used in GIS helps me comprehend part of why GIS is so advanced and useful. The 3 different types of features (discrete, continuous phenomena, summarized by area) are something I feel like everybody knows but it sits at the back of your head and it’s not really something you’re ever conscious of.
It was interesting to see (through images and writing) how GIS allows you to visualize different data sets together using overlaying. It seems like such a simple and common thing and I’ve never thought about how data is layered to create maps like these.
Reading about the different geographic attributes and when to use them was very valuable. It’s definitely something I’ll come back and refer to when we start using the software.
I found the data table information difficult to understand. It took me a few read-throughs to make sense of the information. Data is obviously a crucial part of GIS so I made sure to grasp the information.
Ch. 2
Chapter 2 focused more on the actual mapping and how to use different mapping techniques to achieve different outcomes. It also addressed how maps should be presented with the audience in mind. An audience familiar with the area wouldn’t need as much detail and as many references points as an audience that isn’t familiar with the area. Also, not all maps will have the same amount of details, depending on size (although this seems to be more for aesthetics than practicality).
This section also addressed how inputting data and creating the map will look. I learned about using a subset of features. This is useful when you want to be able to separate different features on a map. Although I learned more about subsets and when to use them/what to use them for, I think I am still a little confused on what they actually are. But, as I read on, I did understand how mapping by category can be more logical than mapping with subsets. Mapping by category makes different features distinguishable.
Displaying features by type is a productive way to display large amounts of data. It allows you to combine a lot of data onto one map in a way that is not cluttered. It also offers an option to make multiple maps in order to separate large amounts of data. Another way to simplify the data is to group categories together. The text provided multiple ways in which to group categories effectively. Of course, it notes that a con of this is that important information can be lost. In this case, if it is really important, you could just split the categories up onto multiple maps.
Lastly, this chapter describes how to interpret geographic data patterns. The 3 types of patterns were clusters, uniform, and random. Looking at geographic patterns is useful when observing maps in order to understand why a community works a certain way or when planning a visit.
Ch. 3
This chapter addressed mapping quantities and the different ways that can be useful. When using quantitative data and summarizing by area, ratios should be used so that the distribution of the data is accurately represented. The text mentioned the most common ways to find ratios in GIS: averages, proportions, and densities. It talked about when each of these are useful and how to calculate them.
Ranks is another feature that was addressed. Ranks put things in order and don’t show exact values, but values in relation to each other. This is useful when the feature you’re using is hard to get an exact measure on or if it takes multiple data factors into account. I learned why it is wise to group values together because if you didn’t, the map would be confusing and would not convey any valuable information.
Classes should be used when comparing data to a specific value or trying to see which data meets a certain criteria. Classes allow you to group data based on your needs and what you are trying to gain/understand.
A new topic to me, standard classification schemes, was introduced in this chapter. These are valuable when looking for patterns in your data. There are four common schemes. Natural breaks is one where classes are broken up by the natural grouping of the data values. There can be an uneven number of features in each group using this method. Another common grouping, quantile, contains an equal number of features in each group. The next scheme was equal interval. The way I understand it is that the max and min of each interval are the same distance apart. I am not sure if this is completely correct though. The last one is standard deviation. This one, I am familiar with. This organized features based on how far their value is away from the mean. The text then went into depth about these and when to use each as well as combating problems that may arise.
This chapter was long, so it covered quite a bit more material throughout the rest of the chapter. This included how to choose, use, interpret, and find patterns in different map types. I anticipate this information to be extremely helpful once we start to create our own maps.