Chapter One
I think the definition that Mitchell provides for GIS is very effective because of how simple it is: āGIS analysis is a process for looking at geographic patterns in your data and at relationships between features.ā This definition is short and to the point but this description allows me to better understand all of the capabilities of GIS rather than just āmaps.ā I also think it was useful to approach using GIS in terms of a research question you are trying to answer, like starting with framing the question and really understanding what you are trying to get out of the project at hand will help guide you on what type of data you need to acquire and then which methods to use to then process the data and eventually try to interpret the results. I found the breakdown of types of features to be very useful. Terminology such as ādiscrete featuresā and ācontinuous phenomenaā were not terms that I have really heard before and it was useful to understand that discrete features are used for locations and lines when an actual location can be pinpointed, whereas, continuous phenomena is used for an entire area. āThe two ways of representing geographic featuresā also brought two new terms I was unfamiliar with which were āvectorā and āraster.ā Vector uses rows and tables and is more of the traditional x and y approach. Raster models āuse a matrix of cells in a continuous space.ā From my understanding, the raster model layers different data points for analysis. In the next section, I learned how map projections use a sphere to project coordinates onto a flat surface and how it distorts the shapes, area, measurements, etc. Coordinate systems use a 2D system and have specific units. I noticed that the types of attribute values (categories, ranks, counts, amounts, ratios) are very similar to different types of data in statistics (nominal, ordinal, interval, and ratio), which was a great segue into talking about data tables!
Chapter Two
This chapter talks about why we map things and immediately I was met with the quote āmapping where things are can show you where you need to take actionā which is literally so important for public health. For example, John Snow used maps and data points to understand that the cholera outbreak was coming from the Broad Street pump and was able to identify the problem this way. I also think the section on how to use the map was important because it mentioned using the appropriate map for your audience. This is very relevant to any type of work related to policies where you are trying to persuade lawmakers or decision makers. I learned how one of the foundational parts of starting to map data is importing or assigning coordinates and category values. The paragraph explaining what GIS does was very helpful to understand how it goes from data to mapping this information. I also found the visual example on page 31 to be helpful because in the first image it starts with one set of coordinates, then in the next picture it starts to connect the coordinates, and in the last photo, it shows the highlight of the parcel of land mentioned in the text. In the category sectionĀ I also appreciated the more in depth explanation of what GIS does and how it looks up symbols based on category. I didn;t know the simple example of line thickness on road maps was using GIS before! I also learned that most people canāt distinguish more than seven categories which honestly makes so much sense because I think when I look at figures that have more than seven I get very overwhelmed! I also think it is interesting how much of an impact grouping categories can have on your data and it is something that I have not really thought about! Overall, this chapter was very insightful and provided a lot of useful information!
Chapter Three
I found the concept of āMapping the Most and Leastā to be very thought provoking. At first, I didnāt quite understand this concept but once I read through the public health example of physicians per 1,000 people it made more sense. I also found the section on Ratios to be very useful. Although this is a concept I have learned a few different times in my academic career, it is always helpful to have a reminder of the different types of ratios and how they can most effectively be used, especially in terms of mapping data. I was a little confused by ranks at first but once it explained it in terms of text and then provided a visual example on page 62 it made much more sense! Classes were also a useful refresher in terms of what their purpose is, as well as an example on page 63 which uses poverty rates. Standard classification schemes was another concept I was not as familiar with. The text gave a good overview that explained it as grouping similar values to find patterns. I liked how it was broken down into the four categories of natural breaks (natural groupings), quantile, equal interval, and standard deviation. The information about how to choose a classification scheme was also useful and something I made note of: uneven data: natural breaks, evenly distributed data and want to emphasize differences in features: standard deviation, evenly distributed data and want to emphasize relative differences: quantile. Outliers are always something that will come up in data sets and can be very impactful to what you are trying to portray. I appreciated the tips and trips on what to look for with outliers. I found the entire section on making a map to be very useful, especially the table with all of the breakdowns of features, values, advantages and disadvantages. The checklist for choosing a map type will also be useful in the future!
(Also including a photo of Marlin)
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