Chapter IV
Chapter four is entirely focused on density based mapping. At first I believed this chapter was going to feel like a tedious slog, given that density based maps do away with precise location in favor of a more relative form (such as population per square mile). Effectively mapping density is a trade off from point based data to quantitative data which I believe to be somewhat redundant given that point based data typically tend to show density anyways.
However, upon reading the chapter I do believe that density mapping has its uses, especially when cross examined with more point driven data. An example the textbook gave for this was comparing sights of crimes with regional information on average income in the areas or reported gang activity.
The GIS software does plenty of work as far as plotting and interpreting the density based data goes, including totalling the number of values within a designated area and dividing it equally across the size of the area in question as well as both general averages of the data and weighted averages.
Much of the general advice from the previous chapters apply here as well. One which I feel is a little bit redundant at this point is the specification on the classes of value a density map should have to be easily readable. This is something that was discussed in the previous chapters relative to the different classes of point based data. (More point classes makes the map harder to read, applies the same to value classes in density mapping)
Chapter V
Finally I am getting to exciting things! Mapping within a certain radius and interpreting data within that is the kind of geographical analysis I took this class to learn about.
The chapter designated several types of area based maps: Single areas (Within a single area, it is in the name) Buffers (an area surrounding a certain feature or features) and boundaries. (the boring one)
There is also a distinction to be made between the maps I just discussed and mapping multiple areas, such as contiguous areas which typically are located right next to each other, and Disjunct areas which have “buffer land”.
Then the chapter discusses discrete and continuous features. We have been over this.
The GIS software is capable of several methods of analyzing limited maps. The book has the example of a flood map and shows the GIS being able to find specific designated areas that may fall within or without the flood path, as well as being able to count and/or list the designated areas within the flood path. There is even the ability to create distinctions between the areas and categorize them by value or type based on whether they fall within the designated focus area or create visual data representations based on the data within the areas.
Chapter VI
I feel the subject matter of this chapter overlaps considerably with the previous chapter. Once again, this is based nearly entirely on mapping within a certain area. The primary difference being the discussions on how the GIS software can calculate the distance (or cost) and possible travel routes.
Of course, nothing fun is ever easy and frankly a wrench was thrown into my ideas on applying this when the book discussed the differences between miles based on a certain geographical projection (effectively assuming the earth is flat) and based on the curvature of the earth. I hope the difference between these values will not be too big of an issue given the rather limited area I intend to map, but I know for a fact if I were mapping a larger scale project that this would potentially derail my analysis completely.
The book describes the differences between different methods of mapping using proximity as the primary considerations as well as discussing the measure these methods record and which situations these can be applied in.
I actually really enjoyed reading about the cost over surface method. I am currently reading about the construction of the first trans-continental railroad which used a great deal of cost over surface mapping when surveying the land and even using that to modify the land to be better suited for rail transportation. (The TV show Hell on Wheels famously depicts a “cut crew” who would dig up large amounts of earth to construct a level railbed.)
This leads into the next thing I thought was interesting: Networks. Using lines that can represent road, railroads, or airways the GIS can automatically calculate the distance or cost by only following the network to the intended destination. I feel like that is one of those things that is so obvious to the common man that it effectively vanishes from our consciousness.