Chapter 4
Chapter 4 explains the reasoning behind mapping density, as well as when it is important to map density, what to map and the two types of ways of mapping density. Density maps allow viewers to observe each individual feature of a map using a uniform areal unit of measurement, such as per square mile, per county, or per census tract. Census tracts are specific geographic regions defined solely for the purpose of conducting the census. When would a density map be used? One example could be: a local nonprofit wants to see which areas of the State of Ohio have a more concentrated homeless population using census tracts as a measurement, and so the nonprofit collects the data on the number of homeless individuals in each census tract, with the darker shade being the highest concentration of homelessness and the lighter shade being the lowest concentration. When choosing what to map, you can choose to map (1) the density features, which include the number of businesses, schools, parks, etc., or (2) to map feature values such as the number of employees at each business, the number of teachers per school, the number of trees per park, etc.. Density maps can be represented using a random distribution of dots on a map to show the concentration of particular features, or using a density surface, which is a raster layer that can show the number of features within a particular radius of cells. For example, if local law enforcement were mapping the density of individual crimes within a given area, a density surface could be used to show the concentration of higher occurrences of crimes in a given area and which areas crime occurs the least. When creating a dot density map, dots should not be so large that areas with higher density are obscured and difficult to interpret.
Chapter 5
Chapter 5 explains the reasoning behind “mapping inside” an area and its uses. Mapping inside requires you to draw a boundary around the area that you want to analyze. For example, if a construction company is trying to see which neighborhoods are more prone to flooding, the construction company may draw a boundary around a particular area of interest and see which properties are near floodplains or if floodplains intersect with certain areas to get a better sense of where to build. In the chapter, Mitchell also provides an example of a district attorney being able to draw a boundary to map out which crimes occurred and whether the crimes that occurred were within a certain radius of a school, which could lead to tougher criminal penalties. The chapter also touches on discrete and continuous features when mapping inside. Discrete features are easily identifiable features on a map such as roads, rivers, waterstreams, or even locations such as student addresses. Continuous features are represented using seamless geographical phenomena such as vegetation. For example, a geographer could represent the different types of soil using continuous categories. When mapping inside, a geographer may want to know which type of soil is within a 1000-square feet radius. When counting the number of features within a boundary, Mitchell states that you should include features that are partially within the boundaries inside of count and if you want to emphasize the different categories and features within a particular boundary, that you can use GIS to create an overlay that clips out the features and portions of categories that’s on the outside of a boundary that way you are left with a map of only the boundaries and all of the features and categories inside the boundaries being focused on. You can also create an overlay to where the features of the summary statistics you’re mapping are in color and the outer boundaries features are still present but in black and white to emphasize their nonimportance.
Chapter 6
Chapter 6 explains how to map what’s nearby. Similar to the last chapter, you could draw a circle around a particular area of interest to see what is all within the boundaries. Chapter 6 explains that while doing that, you can also map what’s nearby based on the distance specified from one area to another as well as the travel costs. How can this be done? Mitchell explains that this can be done using a simple straight-line distance. For example, if Starbucks executives were looking to see which grocery stores, parks, or recreational centers are nearby and how far, the distance from each of the locations could be represented using a straight line which could represent a mile or 2 miles, etc. Travel costs could also be measured when looking at what’s nearby. To calculate the travel cost, Mitchell points out that you would need to use GIS, assign each street segment with a cost. To do this, you would need to find the per unit cost (for example, labor and fuel costs) and then multiply that by the length of each street segment. You can also measure the travel time for each street segment or block while considering the speed limits for each street segment and multiplying the length of each segment by the speed limit. This is the formula the chapter provides for calculating travel time: “minutes = length / ((mph * 5280) / 60)”.