Chapter 4:
This chapter gets into the details of mapping the density of a feature. Meaning the map shows the locations of the highest/lowest concentrations of the feature- a mapping style that is very good for observing patterns. Similar to the previous chapters, being aware of the information you’re looking for from the map, and what the features are is a key thing to keep in mind before and when building the map. Chapter four really begins to step out of the correlation aspect between features and tip into a causational mindset of asking questions and developing factual statistics based on an aspect of the map. The textbook goes into detail about all the different ways to map through density, from using points, lines or by area to visualize the map- to measuring specific features, versus their mathematical value. Each method can be placed onto a map in various visual representations, like a dot map or by color blocking areas. I personally find the color blocking to be a much easier, more comprehensible map. Although, I do recognize that there may be specific reasons for conveying a map through a dot map, and appreciate the simpler graphical plotting it takes rather than the area’s calculated steps. This chapter also explains that in relation to a specific location the density and population can be two very different things. The population may be the same, however, the density could be scaled way in or out depending on the size of the area. Think if Texas and California had the same population. Texas is larger, so the density would be more spaced out, while California’s would be a bit more crowded and localized. Chapter four explains how to display density surfaces, which are usually displayed through raster layers, commonly good at representing point/ line concentrations on a map. Continuing off this, the maps can be calculated/ determined through these methods: Cell size (coarse and fine), search radius (generalized vs localized), calculation method (a simple method- only in radius areas, weighted- mathematically), and units (areal units where the density value is calculated). Compared to the next two chapters, this one was relatively basic- and contained an amount of generalization similar to the past chapters, albeit with more depth.
Chapter 5:
Chapter five explains how to make maps within specific areas and to analyze that data from inside areas on a map. Like all the other chapters, it stresses the importance of defining what it is that you are trying to analyse or get information of- if it’s a calculation from single or multiple areas, or from a discrete or continuous feature. The distinction between these two features determines whether you’re making a map with a uniquely identifiable feature or a continuous and seamless geographic feature. Again, it is important to know before you create the map what kind of results you would like to obtain (a list, count, or summary). Knowing this will alter how the map looks at the end of its mapping. I found it interesting that you could decide to manually leave certain features out of the map/ data set. Like, some features can extend outside the area boundary (rivers or roads), so understanding if the information would benefit from keeping those features within the area data, or not is a good skill to develop. It is also good to note that certain results require these partial boundary features to be included in order to complete the data (example being lists and feature counts). The textbook describes three ways to make the calculation of this inside area. These are: Drawing areas on top of features (map contains a strong boundary of the area), selecting features inside an area (a subset of features from within an area, and is good for summaries), and making an overlay area with features (a mixed method, and is good for comparisons). This section contains examples of what each method is good for and their comparisons, which is very helpful in understanding how each one works, and which ones to use in practice. In this chapter, it provides further detail on how to actually create these area maps, with separate explanations between discrete areas and continuous ones. It explains that GIS can create reports (tables or lists) based on the data of the completed map and area. That it can also make statistical summaries like counts (total numbers), frequency (table/ bar/ pie chart, number of features with a given value) and summaries of a numeric attribute (summary, average, median, standard deviation). Chapter 5 provides clear and distinct step by step tutorials on how to use/ analyse the data acquired and other steps within map making. I also appreciate the call backs to previous chapters, instead of just repeating the information, the textbook references where you can find it and moves on. This kept the chapter from being too repetitive and not getting stuck in past information.
Chapter 6:
Chapter six focuses on a different use of GIS, of finding what goes on within an area and distances around that area in a certain range. It also showed an ability to monitor data within a range, to see the changes and develop a continuous data set. A key component of this chapter’s analysis is through traveling range, the calculation of this data through the measurement of distance, time or cost. Ways to measure this is through straight-line distance, measure distance over a network (streets/lines, connected plots) and measure cost over a surface. This cost is most commonly time, but can also represent money (the literal cost), the effort taken, or travel costs- which are the more precise measurements over the other distance measurements. One thing I thought was interesting was mentioning that maps can differ depending on planar/ geodesic methods, aka flat maps vs. curved maps following the earth’s curve. This is something that when you stop to think, would obviously be different from one another, but because most people are so used to planar flat planes, isn’t a big thought. Following this, once again the concept of localized or global maps is something to keep in mind when creating your analysis. Know the basic, groundwork information before beginning on your map. Another call back to the previous chapter is the list of features, counts, and summary statistics. It repeats certain information in further detail, only better ingraining it into my memory. Like the previous chapters, there are a lot of technical things that are actually quite grounded in common sense. For example, the ability to determine cost ranges through singular and several ranges, or visually creating a map with either inclusive rings or distinct bands. It is simply the technicality of engaging the GIS software to make/ calculate the maps with these features that can be confusing, and need solid explanations. I liked the clarity on three main ways to find nearby features, although by the end of the chapter it did feel repetitive between them. Like, by the end I wasn’t fully confident which method or style the textbook was explaining how to map out. A lot of the instructions are more or less similar to one another- or at least have one thing in common, so that’s helpful. One thing I keep thinking of when reading all these chapters is that I’m quite glad that the GISystem does most of the calculations for me… I would for sure mess up the map if I had to do the calculations myself. It makes me think about how people might have worked with maps and calculating features back before the system was built, how they must have had to learn to do all the math themselves and map it by hand! Finally, I said this for chapter 3, but I love how the textbook includes comparisons between the two options. It was relevant to all these chapters. It makes everything very clear- able to distinguish and figure out which mapping method I should use and why. One question I had regarding the ability to set max distances was if you could also specify a minimum distance, and what reasons someone might have to do so?
