Chapter4
This chapter explains what density maps are and how to create them. Density maps help me understand patterns rather than just the locations of individual features. We can map features using new data or previously summarized data, such as census tracts, counties, or forest districts. I was surprised that even when using the same data, the maps can look very different depending on whether they are density maps or other types of maps. Before reading this chapter, I thought density maps made with layers and different colors were easier to understand than those made with dots. However, after calculating density, I realized that dot density maps often work better because they make it easier to count and compare. I also learned that when creating a dot density map, it is important to specify how many features each dot represents and how large the dots are. Dot maps give the reader a quick sense of density in an area. Shaded maps, using a range of color shades, are also useful to understand which areas have the most or the least density. I was also surprised that some GIS software, such as ArcGIS, allows you to calculate density automatically. It is really cool! I was especially surprised by the textbook examples showing two maps with different cell sizes and two maps with different search radii. The differences in cell size and search radius make a big difference in how the maps look. Therefore, I think I should pay attention to cell size and search radius when creating density maps. Finally, I prefer when areas of higher value are shown using darker colors because it makes the maps easier to understand. I also wonder if there are cases where showing higher densities with lighter colors could actually make the map clearer. After looking into it, I found that this approach is sometimes used in night maps, aviation charts, maps designed for people with low vision, or certain types of visual design where the colors are intentionally inverted.
Chapter 5
This chapter explains how maps can help us see what is inside an area and compare it with other areas. Knowing what happens in an area by using maps helps people decide what actions to take. In order to find what is inside, we need to know the boundaries, check the features in an area, and analyze them. Before reading this chapter, I did not really understand the meaning of “finding what’s inside.” However, I fully understood it after seeing the map that shows calls to 911 within 1.5 miles of a fire station. The circle on the map, centered at a fire station, helps us see how to evacuate or reach hospitals in an emergency. The map shows this information at a glance. It also made me realize how important it is to know how many areas I have and what types of features are inside those areas. As the next step after mapping, I learned that I should think about what kind of information I need to analyze—such as a list, a count, or a summary—and how detailed the map should be. I think knowing these things helps make a map more efficient. When I make maps, I want to make sure who will use the map and what its purpose is. I also found it interesting that you can overlay another area on data that has already been summarized by area. This makes it possible to combine not only current data but also past datasets for further analysis, which I think is really exciting.
Chapter 6
This chapter explains that finding what’s nearby helps us decide how to measure nearness and what information we need for the analysis, which in turn determines which method to use. I didn’t know that when mapping what’s nearby based on travel, I can use not only distance but also cost, such as time and money. For example, if someone says a store is within 15 minutes from here, I might consider it close. But if you include factors like traffic jams, that perception can change. That’s why I used to think distance alone was what defined nearness. I also learned that inclusive rings are useful for showing how the total amount increases as the distance increases. I had only seen it used to show the relationship between the magnitude of an earthquake and the number of victims, but I learned that it can also be applied to various analyses such as commercial facility service areas, population distribution, and service coverage.  According to this  chapter, there are three ways of finding what’s nearby; straight-line distance, distance or cost over a network, cost over a surface. First, straight-line distance can create  a boundary or select  features at a set distance around a source well. Second, distance or cost over a network can find what’s within a travel distance or cost of a location over a fixed network well. Third, cost over a surface can calculate overland travel cost well. We can select one of them depending on what is surrounding features and  hot measure. WE need to specify the distance from the source and the GIS selects the surrounding features within the distance.