Chapter 4
This chapter has been helpful in assisting me in understanding how a GIS maps density. Mitchell discusses how there are various ways in which density is mapped. There is defined area
density and density surfaces. Defined area density includes dot density mapping, in which the number of features represented by the dots is chosen by the analyst, as well as the location of the
dots inside the defined area. I learned that the final product can be greatly impacted by the choices the analyst makes, especially because the dots do not show the exact location of the
features. Shade density mapping is also included in defined area density and is greatly impacted by the classification methods. Quantiles and equal intervals, discussed in the first few chapters,
come into play again in this chapter, as they play an important role in the final product. However, density surfaces display the density differently because they create a surface based on the search radius from each point. I learned that the final product can be affected by the cell size because it can be coarse or smooth depending on the choices the analyst makes. Mitchell discusses how density surfaces can show subtle patterns that defined areas might not show, but they require extra work and care. I learned that the final product can be greatly impacted by the choices the analyst makes and that density surfaces require extra care. I also learned the importance of using the same classification methods when comparing multiple density maps. One thing that caught my attention is the importance that the analyst has in the final product, as their decisions may affect the final product to a large extent.
Questions:
1. When should a dot density map be used over a density surface?
3. How do the classification methods stop or create false density patterns?
Chapter 5
Chapter five discusses what is inside an area. Mitchell states that if the analysis is done on one area, the goal is usually to summarize or monitor what is going on inside the area. If the
analysis is done on several areas, the goal is to compare the amount or kind of information inside each of the several areas. There are three ways that this can be done: listing what is inside the
area, counting what is inside the area, and summarizing the attributes of what is inside the area. The third method involves adding up or averaging the attributes of the features inside the area.
One problem that Mitchell presents that I had never thought of before is how to determine whether or not to count features that are only partially inside the area. The second problem is
how the boundaries of the areas are represented. In some cases, the boundaries are represented with an outline, and in other cases, the interior of the area is shaded to help identify the area as a
whole. This, in my opinion, affects interpretation because, with the boundaries, the focus is on the separation, and with the shading, the focus is on the area as a whole. What I got from this chapter was the importance of consistency. For example, the boundaries, if one is represented differently from the other, then the two areas are not being compared fairly. Mitchell is able to
connect this chapter to the previous ones by showing the use of the concepts discussed in the future. This chapter has helped me understand that area analysis is simple but detailed, requiring
a lot of decisions.
Questions:
1. How do you determine whether partially included features should be included in an area?
2. What methods of mapping are best suited to represent the results of boundary-based analysis?
Chapter 6
Chapter six of the book discusses how GIS solves the problem of what is near a feature. This is another important problem that occurs in spatial analysis. In this chapter, Mitchell
explains that there are three different ways of measuring what is near a feature. One way is by straight line distance. This is the simplest method to use, but it is not always realistic since it
does not take into consideration any obstacles that may be encountered along the way. The second way is network distance. This is more realistic since it considers what path one has to
follow. The third one is cost over a surface. This is more advanced since it considers many different factors that may influence movement. The path that one has to follow may be difficult
even though it is straight. There are also buffers, which are used to define what is near a feature by creating a buffer around a feature and defining what is a certain distance away. Buffers can
be used to represent distance, time, or cost, depending on the analysis. The reminder about using planar versus geodesic distance was important to me because it is crucial for obtaining accurate results. Smaller areas can be analyzed using planar methods because the curvature of the Earth is insignificant, but as the area gets larger, it is crucial to use distance to obtain results that accurately represent the Earth’s curved surface. Another topic that Mitchell reviews is earlier concepts such as counting or summarizing features within zones, demonstrating how each
chapter builds on the previous one. What stood out to me is how proximity analysis, although simple at first, can become complex depending on the real-world situation. Different issues call
for different approaches, and if the wrong one is used, it could lead to the misrepresentation of the level of nearness of something. This also made me think of how easy it is to misrepresent the
distance between two points on a map if one does not take into consideration the real situation.
Questions:
1. When is straight-line distance sufficient to be used on its own?
2. How do buffers change depending on the units used, such as distance, time, or cost?