Chapter 4
Chapter Four covered Map density and its purpose. By mapping density, we can see where the highest concentration of a feature is. Mapping density is important to show the number of people per census tract. Density maps are something I am familiar with and have used before in different classes. What I found interesting was that you can map the density of features or feature values. For example, you can map business locations or the number of employees at each business. You can also map density graphically, using a dot map, or calculate a density value for each area. The operation of creating a map by a defined area or by density surface varies greatly. The density surface method may provide better information however it requires more effort. The chapter concludes by reviewing the methods and features of each. It explains what GIS is doing when creating density surface maps, like how the software will total the number of features that fall in an area and divide it by the area of the neighborhood. The calculations GIS creates are determined by the parameters specified by the user. Such as cell size, search radius, calculation method, and units. After reading this chapter, I have learned a lot more about the niche parts of GIS. There are so many important factors that go into map making and it is important to be diligent.
Chapter 5
Chapter 5 started by discussing why we should map what’s inside an area. This is important to mapping because it tells us if we need to take action on a certain topic. Many organizations and people rely on this type of mapping to complete their jobs and make communities better. When mapping, you must determine if you are looking for something inside a single area or each of several areas. Single areas include a service area around a central facility and a buffer defines a distance around a certain feature. As well as a natural boundary, an area you draw manually, result of a model (ex.boundaries of a floodplain). When finding something in several areas you are able to compare them to each other. These areas include contiguous (ex. zipcodes), disjunct (ex. state parks), and nested (ex. 50-100 year old floodplains). You can either have discrete or continuous features in your chosen area. Discrete features are unique and identifiable like locations. Whereas continuous features represent seamless geographic phenomena like precipitation or elevations. There are three ways of finding what is inside a given area by drawing areas and features, selecting features inside the areas, and overlaying the areas and features. Each method explains what it is good for and what information you need for the method . I found it interesting that there were so many options when finding what is inside and what the tradeoffs are between them. They discuss how to choose the best method and how to complete each. Each method has its own criteria and process different from the others. Finally, the tools in GIS can help us create summaries for our results, including a count, frequency, and a summary of a numeric attribute (most commonly a sum). A count is the total number of features in an area and the frequency is the number of features with a given value or within a range of values. You can display frequency in the form of a bar chart in order to read the data better. I found this helpful to know for the future, because it may be easier to read for me. The summary of a numeric attribute (sum) can just be the overall total of something in the map.
Chapter 6
This chapter begins with asking why map what’s nearby. When using GIS you can discover what is in traveling distance and find out what is occurring within a distance or feature. I found the example of the wildlife biologist interesting because that is something I resonate with. It discussed that they may want to know what is in a certain traveling range around a stream. They would use the features in this area to determine prime deer habitat. I found the following paragraphs to be interesting. It discussed that distance is one way of defining how close something is but nearness does not always use distance. You can actually measure something nearby with cost, for example time, money, and effort expended. By mapping costs rather than distance you are able to find a more precise measure of what’s nearby. This was interesting to me because I have noticed that sometimes somewhere that is 15 miles away is actually closer than somewhere that is 10 miles away. So seeing that being measured and explained through a GIS standpoint was intriguing. Next the chapter went over three ways of finding what’s nearby, straight line distance, distance or cost over a network, and cost over a surface. Each method is good for certain things and requires different data. I found it very helpful that this chapter gave a list of guidelines for choosing the best method. It helped me better understand why you would use different strategies for different problems. This chapter built on various previous concepts which made the question of why map what’s nearby much easier to understand.