Hollinger Week 3

Chapter 5:

Chapter 5 built off a lot of what was learned in chapters 1-4. It reaffirms the importance of knowing whether your features are continuous or discrete when mapping. Mitchell notes that when dealing with discrete areas you can represent features with several different methods. This includes drawing boundaries on top of each other, on top of a color-coded area, or shading and labeling the boundaries. The reading then details for continuous features you should draw areas symbolized by category and quantity and then draw the boundary on top. I think the difference here is important as continuous data must be represented differently, in this way almost separately for the map to accurately show features and help the viewer get a sense of the range of continuous values.

The chapter then goes on to talk about what kind of data you can get from maps like lists and summary statistics before it gets into what I thought was the most important part of the chapter. This was the portion discussing overlaying areas and features. I talked about two different methods of doing this – the vector method and the raster method – this reaffirmed the difference between vector and raster layers while providing a new mechanism for producing maps and representing features. Briefly, with vector overlay splits category or class boundaries where they cross areas and create a new dataset with resulting areas. Vector is more precise, but it has one problem – slivers. As I understand it, slivers are where borders are offset. If these slivers are so small, it is important to merge them with surrounding data. This brings us to the raster overlay. Raster overlay combines raster layers and counts the number of cells in each category within each area then calculates aerial extent by multiplying the number of cells by the area of a call. This can ultimately be less efficient depending on cell size, but it does prevent slivers.

Chapter 6:

Chapter 6 was all about finding out what’s near and relevant to your feature(s). It talks about how travel is often measured by cost, which is time, money, effort (referred to as travel costs), and distance. The chapter then moved on to outline 3 different ways to find what’s nearby. The first and probably simplest of these is straight-line distance. Essentially, given a source feature and distance, the GIS will find features within the distance. The next method is distance or cost over a network in which GIS finds segments within the distance or cost given source locations and a distance or travel cost along each linear feature. Finally, there is cost over a surface in which you specify the location of the source feature and a travel cost, GIS creates a new layer showing the travel cost from each source feature.

This brings us to some new vocabulary from the chapter. First off, source locations are often referred to as centers. An impedance value is the cost to travel between the center and surrounding locations. Edges are lines, Junctions are where edges meet, and turns are used to specify the cost to travel through a junction check that these exist, are correct, and are in the right spot. These all help to define the network layer.

Another part of defining the network layer is cost. You can specify street direction or more than one center (rural vs urban areas) as these details can change the cost by lengthening travel. The GIS also checks and tags each distance of each segment keeping a cumulative total of cost or distance. One thing I did not understand about cost was the calculation. To find the monetary value the book gives the equation of Cents = length*(cost per mile/5280), but I feel as though travel costs are dependent on many other factors like traffic, gas prices, etc. So, I am slightly confused about how the given cost is an accurate reflection without some way of factoring those in.

Chapter 7:

Chapter 7 discussed mapping changes over time and how it can help predict future needs. It talked about mapping features previously discussed such as discrete features, data summarized by area, continuous categories, and continuous values. Specifically, it talked about how these features can change in character and magnitude. A change in character might be something like a physical movement of a feature, whereas a change in magnitude might be something like a hurricane or storm getting “worse” or “better”.

The chapter then moves on to talk about time. There are 3 ways to measure time: trends, before and after, and cycles. A trend is a change between 2 or more dates and times. This shows increases, decreases, and direction of movement. Before and after are conditions preceding and following an event. This lets you see the event’s impact. Finally, a cycle shows change over a recurring period and can give about the behavior of the features you are mapping. There are two ways to represent these changes in time as well. The first is a snapshot, which shows the condition at any given moment and is used to map continuous phenomena. The second is a summary where an event either is or isn’t occurring at a given time and is used for mapping discrete events. For cycles, you can use a snapshot or summary, for discrete events use a summary, and for continuous data use a snapshot.

The final portion of the chapter discussed the 3 ways of mapping time. The first is a time series. This represents movement or change in character. It can use a trend, cycle, before and after, and shows conditions at each date/time, but it can be hard for readers to compare visually. You should use this for a snapshot when you have 2 or more times. The second is a tracking map which is used for movement and can represent a trend, cycle, or before and after. It is easier to see subtle movement but can be difficult to read if there are many features. You should use this method when you have feature movement over 2 or more times. Finally, Measuring Change measures a change in character. This can represent a trend or before and after and shows the actual difference in amounts or values. However, it doesn’t show any actual conditions and only uses 2 times. The chapter then goes into thorough detail on the process of creating each of these maps. Overall, I thought this chapter was straightforward and I don’t have any questions about it.