Chapter four was all about how density mapping works in GIS and how to perform it effectively. Mapping by density is an effective way to see patterns in data, and is a sort of progression. to most and least mapping, which we learned in the previous chapter. Basically, being able to see the concentration of an occurrence/feature on a map allows one to get a general idea about the aforementioned feature. According to Mitchell, there are two main ways of mapping density using GIS: by defined area and by density surface. Defined area mapping means that you use a dot map to show density geographically, and is more accurate to the actual data points, but at the trade of it being harder to see a pattern emerge. Mapping by density surface, however, makes it easier to see the pattern, as it utilizes a raster layer to create a concentration gradient. There are many factors involved in choosing which form of density mapping to do, as well as how to effectively do said mapping. For instance, in density surface mapping, the cell size needs to be picked correctly, as if it is too large, it can make the pattern harder to discern, or if it’s too small, it can make data processing time much longer. It’s a balancing act of getting the most accurate data possible, without decreasing efficiency. This is also apparent when picking what units to use as the area in density mapping, as using the wrong unit can make skew the data. This chapter also empathized using a good color choice/ gradient, like chapter 3. This is because without easy to see differences, the data pattern can be hard to make out. Overall, this chapter was very effective at teaching the basics of density mapping.
Chapter five was a bit of a hard chapter. It starts introducing how to actually adjust/ modify the map parameters to show results for only certain sections. This is obviously a very important aspect of GIS mapping, but it’s a little complicated too. There is a lot of examples for why this is used, such as seeing differences in things like precipitation level or soil content inside of a floodplain, or observing the man made features inside a protected area. Analysis is one of the main purposes of mapping, as it allows for understanding patterns against geographic location, so being able to narrow down the parameters to just what a person is interested in is very important. According to this chapter, there are three main ways to do this: drawing areas and features, selecting the features inside an area, and overlaying the areas and features. Out of the three, drawing areas and features is the easiest and fastest to do, but it is purely visual and provides no concrete data. It can be used as a starting point, but is not proper for deeper analysis. Selecting features is better for getting quantitative data, but it cannot be separated into other areas, as it is treated as one by the GIS software at that point. Overlaying is the most accurate way of getting quantitative data, as it allows subsections inside the area a person is interested in. However, this method takes the longest and uses the most processing power, so it is not always suitable. Once you’ve picked which method to use, there are various ways to actually view the data, such as bar charts and pie charts, or tables. Choosing which of these to use to observe your data is also case dependent, but the chapter provides a good baseline for when each is most appropriate.
Chapter six was packed with a lot of complicated, but important information. This chapter taught me about how to analyze data based, not on what is inside a certain area, but what is around a certain area. This is obviously very useful for mapping, as it allows for things like analyzing distances between features or observing overlapping areas between features. What I found most interesting, however, was the idea of using cost to analyze a measure, as opposed to distance. In hindsight, it makes senes that not all mapping data is best viewed by distance, especially for things like urban planning. After all, things like traffic can make distance less reflective of the actual time taken. I especially enjoyed learning about how cost is changed by the geographic surface, and how the software can calculate said change. It is just very interesting for me to think about, and I find that one can use GIS to measure by cost to be very promising. Besides that, the chapter introduced a lot of new map making concepts, which is good, but also a bit hard to wrap my head around. For instance, spider diagrams are used to show the distance between a feature and a location, which can allow for one to see overlapping areas. This mapping technique has not been brought up before, and it is far from the only new one. Regardless, when there are so many types of data and data analysis, having a wide range of tools to observe this data is important. I also think that the information about setting a maximum distance for analysis is very important, as too much data could crash the computer, which is highly annoying to deal with. Nevertheless, I am excited to learn how to use the software.