Chapter 1: I think it’s interesting how GIS has become more accessible over time with an increase in social media and tech use. Before coming into college as an ENVS major, I had honestly never even heard of GIS as a field. I like how this book begins with the basics of GIS and explains what it is and how to use it before getting into more of the actual map-building concepts. I think building up a base level of knowledge on GIS will come in handy later when we are presented with more complex topics. I also think it’s interesting how the book explains there are various ways to display the same data. Some methods are just more in-depth and are useful for certain scenarios whereas other methods may be more useful for quick looks at patterns. The explanation of the difference between discrete and continuous data was helpful, and I had not realized there was a distinction between these two kinds of data, but when the book presents the pictures, it makes sense that they are two different things. It is also very helpful that the book includes pictures next to the concepts being introduced so that once we begin map building, we can visually recognize these terms. Interestingly, single-point locations like businesses look very similar as both a vector and raster, but lines on a map, like highways, look much different as a vector compared to a raster. Areas appear to have the most loss of detail when expressed as a raster compared to a vector. The portion of the book explaining the various attribute values was slightly confusing at first because each type seems like they have similar functions (or at least the words all seem similar to me). However, once I went back through and read it a couple more times and studied the maps closer, it began to make more sense. I also suspect that once we begin making our own maps this will be a little more intuitive in practice.
Chapter 2: The first second chapter begins by explaining that you can either map things to identify individual features or to look for patterns in the distribution, though it’s interesting how when looking at the two different maps, they are actually the exact same. I also think it’s very cool that by identifying patterns on a map, a range of different professions from police officers to biologists can determine plans of action based on the data. It is slightly unfortunate that smaller maps cannot show as much information as large maps so they don’t become overcrowded, because sometimes maps may need to be in a small format. However, if there is too much information on the map to be able to read or identify anything, it would defeat the purpose of it entirely. I like how the book explains what the user does to input data for a map versus what GIS does when making the map. When I use R in my biology classes, we also use subsets a lot to uncover hidden patterns. Usually, we’re working with a very large dataset and it’s a lot easier to understand the data with subsets, and I like how that also translates to maps! Like the last chapter, I think a lot of information is being presented here and it’s a little confusing/overwhelming now, but in a couple of weeks when we begin implementing all of these terms, it will all come together. One interesting thing I did not know that this chapter said was that people can typically only distinguish up to 7 factors on a map, which does make sense. I think that it’s helpful that the book includes directions on what not to do- basically things that may make a map look confusing or hard to see data points. This part will be good to look back on when we make maps. It also brings up ways to make maps with lots of data less confusing, such as using text labels. I like that this chapter introduces ways to analyze the data. I think it will be important to discover the trends in the data being mapped and not just simply to make a map to look at for no reason.
Chapter 3: This chapter seemed slightly daunting at first because of its length, but luckily it was a lot of tables and pictures! I feel like the beginning of this chapter was slightly repetitive, as it introduced some of these concepts earlier. However, it’s nice that they go more in-depth with each of the ideas and show more examples of maps demonstrating certain concepts. I think I’m slightly confused about classes and the four different schemes, but as I’ve been saying I’m sure it will make more sense in practice and I can come back and look at this part of the book for reference. I do like how the chapter compares the different classification schemes by listing the pros and cons for each and also giving a general explanation of how they work. I think displaying concepts like this in a textbook really helps me understand the material. I think this chapter will be extremely helpful to look back on later when choosing a map type. The 3D perspective maps are really interesting and I didn’t realize that GIS was capable of doing this! I don’t have as much analysis or reflection on this chapter since it was mainly maps, but again I think showing the maps is obviously a very good way of introducing ideas and comparing different terms.