Chapter 1:
Overall, it is quite interesting to view GIS from an introductory standpoint. Since I know very little about what GIS actually is, it is quite nice to grasp the basic background behind what GIS is. The chapter first starts off with the generic process of what GIS entails. The simplistic steps behind GIS remind me of the steps found within the scientific method. The chapter then goes into the types of geographic features found within the GIS maps. Discrete features are the features on the maps that can actually be defined, which are generally represented as dots or lines. Continuous features are a little more complex to me, but they seem to be features that can be measured pretty much anywhere. There can also be features that can be summarized by area, which is a more density based data. The chapter then goes on to explain how geographic features can be represented. The first way is the vector model, which seems to be a more discrete method, which seems to pinpoint exact points and areas by using coordinates for instance. The raster model seems to be a more continuous representation, where there are layers representing the entire region of the given map. Overall, the differences between vector and raster models seem to have some overlap between them and therefore can be quite confusing. The chapter then talks about attribute values, which relate to geographic features. The five attributes (categories, ranks, counts, amounts, ratios) all make sense to me. The chapter then closes off with understanding the use of data tables. The three features that you use for the data tables are selecting, calculating, and summarizing. Overall, this part seems quite complicated, and I think that actually practicing it will make it easier to understand.
Chapter 2:
This chapter talks about the importance of mapping, and the process of how to undergo mapping through the GIS software. Personally, I find maps interesting, which is one of the reasons why I took GIS. From what I know about maps, they tell you where places are and what unique features are present in different locations. However, I find it interesting that GIS can use maps to help pinpoint certain areas that need particular attention. The chapter talks about the process of mapping. The questions that it asks seem similar to the questions found in chapter 1, which takes the process as a step by step methodology. With using GIS, there are many ways that one can map their data. Mapping with a single type method can show simplistic and universal features, which helps those find a distinct pattern. Another mapping process is through mapping by category. This adds a key to help distinguish different areas found on a map, which helps to create an idea of where different regions are located. Also when it comes to categories, you want to make sure that you don’t have too many,or else it becomes complicated for the reader. If you need to have a large amount of categories, then you might just want to generalize the categories to make things more simplistic. It is also important to know what symbols to use for defining each category in your key. Overall, the purpose of mapping with GIS is to help one analyze certain patterns going on with their data. It can be as simple as zooming in or out or removing certain features on your map that will help you pinpoint certain patterns.
Chapter 3:
This chapter talks about mapping the most and the least, which I honestly had no idea what that meant prior to reading this chapter. However, I have learned that it is a process of mapping that helps researchers correlate patterns or find areas that need to take action. Basically, it is diving deeper into the general ideas of mapping that were discussed in Chapter 2. It also takes in certain ideas from chapter one, as the beginning of the chapter talks about discrete and continuous mapping, along with ideas from the five attributes. Although this information was a little on the repetitive side, it was still good to relearn the information, along with understanding the importance of it to the overall idea of the chapter. After the review session in the beginning of the chapter, it talks about how to properly represent the data on a map. Using counts, ratios, and amounts would generally yield maps that show different classifications. The overall idea of using classes for mapping made sense to me. However, what was a completely new concept was the use of standard classification schemes. There are four of these schemes, which consists of natural breaks, quantile, equal interval, and standard deviation. I have only heard of one of those, and the other three seem a little confusing for me to fully understand what they mean. However, it was easier to understand the overall methods in choosing what classification schemes to use depending on what data you have. The end of the chapter discussed other important aspects, such as determining how many classes you need, and how to deal with outliers.