Chapter four is about mapping density. This type of map or feature when creating a map is especially useful when you have largely varied sizes in the area that is being analyzed. Density maps are also good with showing patterns as opposed to individual connections. Within this, there are two ways to go about creating a density map. One way is by defined areas. In the book, this method is a rather quick and easy way to display information that has already been summarized. This isn’t the most detailed way of making a density map because it doesn’t come straight from raw data. If there is no need for that extra detail though, this is a great method to get a pattern down and to get a visual to start with. The other method of making a density map is by density surface. This method is more detailed but takes a lot more data input since it isn’t already summarized. This method looks a lot like raster models because of the layering and use of cells. It is possible to switch between the two by assigning values to the summarized maps. Things such as the cell size, search radius, methods of calculation, and units affect how the map will come out. Small cell size makes a smoother map versus a more jagged map with large cell size. Small radius shows a lot of variety in information versus a generalizable map with larger search radius. This chapter also revisits chapter 3 with the concepts of natural breaks, quartiles, equal intervals, and standard deviation. This connection is helpful to relate the ideas in my mind. I am interested to see how other types of maps incorporate these same grouping categories. I also wonder what other categories could be similar between different models or maps.
Chapter 5 is about taking a closer look inside the maps to understand the use of certain features, values, or layers. The idea of discrete v continuous values is revisited. Discrete is identifiable and unique like locations or addresses. Continuous can be numerical values or categories but the values vary greatly. After this, more methods were given to … Areas and features, inside areas, and overlay were described. Studying the areas and features is good for quick and easy information but it is hard to find individual values because it is mostly visual and not numerical. Selecting inside an area is good for precise information about that area but anything outside of it is not helpful. Overlying methods is great for understanding the parts that lacked in the other two options but it takes a lot of data input to give a lot of detail. Next, the ways of making these maps were considered. Lines and locations, discrete area, and continuous features were the options. Lines and locations use thick lines and dots to mark location. Discrete areas are mapped by distinct features such as buildings or rivers with lines or shading. Continuous features use a lot of gradients and color to show how areas connect. The way to summarize these features or values was also given with some options. At this point I have noticed it feeling more like a tutorial or like what I expect when we actually start mapping. This is an interesting turning point but because of that I think this chapter is really beneficial for getting ready to start applying some of this knowledge. The next handful of pages goes on to describe overlaps. This is also a topic that has been revisited but in more detail.
This chapter starts with an evaluation of costs versus distance in mapping. One way to map is by distance which is often sufficient but not the most detailed. Cost includes travel expenses and a lot more effort but is very precise. This is a common theme with the comparisons of mapping methods throughout this book. Going along with that theme, the new methods of planar and geodesic mapping were introduced. Planar mapping calculates values with the earth being a flat surface and this is fine when these values are over a small area because it is generally flat. However, when a larger area is being analyzed the curvature of the earth has to be taken into account for. This is known as the geodesic method which is used for large areas of mapping. District bands are useful if you want to compare distance to other characteristics and inclusive rings are useful for finding out how the total amount increases as the distance increases. Methods used for finding values inside of a map were explained. Straight line distance is quick and easy but less precise and it measures distance. Distance in cost over a network measures distance or cost and is good for measuring this relation over one individual infrastructure. Cost over surface is a method of measuring cost and is good for layers but takes a lot of data preparation. Creating a buffer is another important step to demonstrate boundaries of the values. Boundaries are the edges and their uses and centers can be sums. The rest of the chapter was mainly about how to put all of these newer methods into practice to create a useful and beneficial map. I’m curious to see how all of this information will translate to the tutorial portion/book.