Nair – Week 2

Chapter 1:

The first chapter acted as an introduction to the book. The process of analysis was given in a detailed manner. I liked how the chapter said framing questions was the first way to start analyzing data. Understanding data, choosing a method, processing the data, and looking at the results were explained briefly as a part of the process. I liked the different types of maps under the Geographic Features Category to show maps summarized by area, discrete or continuous phenomena.  I thought the maps co-relating businesses with areas/zip codes were interesting because I have always associated GIS maps with disaster management or weather, so this felt new. I knew that Geographic features could be represented using vectors, but this was my first time coming across the “raster” method, which is the representation of a matrix of cells in continuous space. Most of the analysis in this method occurs by combining layers to create new layers with new cell values. The book also included important tips like using the perfect-sized cell instead of too large or too small of a size for a more precise map. I will keep this information in mind when I start making actual maps on the software. Geographic attributes were divided into multiple things like categories, ranks, counts, amounts, ratios, etc and even working with the data tables seemed very math-oriented and statistical than something more social sciencey than I previously assumed. There was a lot of calculation and selection used to summarize data. Overall, different concepts for different types of analysis’ were mentioned, and I found them useful because understanding them will help me get a better idea of what kind of analysis I would like to do. Also, I’ve been trying to find an intersection between technical and social sciences, and I’m trying to see what kind of doors GIS opens up for me there. 

Chapter 2: 

The second chapter focused more on the concept of mapping. It talked about how maps are prepared and bought into this world.  I’ve never had the chance to map stuff before, except for one data visualization project where I visualized the crime rates in each state in India. I like how the entire process is laid out and explained in a well-detailed manner. I feel like for someone with zero to little experience with mapping, this chapter can be helpful since it starts with understanding the location and what exactly we want to map and then goes on to prepare our data and how we can map single or multiple types or by category. Some sections specified how GIS can be used to make these maps more efficient. It was interesting to see the use of maps to quantify thefts, burglaries, and crime in specific locations. It also made me think about other places where we can use maps to resolve nationwide issues like this. Maps give you information that will help analyze further to find solutions.  A few things that my dorky self would enjoy doing while mapping is choosing symbols and colors(Also, the chapter makes use of pastel colors  for maps, so I find it very cute.) 

Mapping is usually looked at as something simple, however, the chapter mentions things like the usage of maps or maps that use eighteen zoning categories. The chapter also describes how ArcGIS provides base maps, which can be used as reference features for mapping. This will help me when I start working on the software. 

Chapter 3: 

The third chapter takes mapping into detail. Looking at the title — Mapping the Most and Least, makes me think that chapter will talk more about quantifiable skills required to make maps. I liked the business analogy used at the beginning of the chapter to explain why we need to map the most and least quantities. This chapter, just like the previous two chapters, had detailed instructions on specific map-making processes. It mentioned things like displaying areas using graduated colors while surfaces are displayed using contours or 3D view. The next page also included a splotchy green map that looked really cool. The chapter also included things that could potentially sidetrack us from the main task, like exploring data or presenting a map and how to explore data in a way to see emerging patterns and questions. Economic and statistical terms were used throughout, like counts, amounts, ratios, ranks, proportions, etc. All the terms were clearly defined, which was helpful for someone like me who has never been in an ECON class before. The chapter made use of multiple formulae to make sure that the data was accurate and precise.

The chapter noted that similar quantities should be grouped in one class together to make it easier for the student to make the map. Mitchell mentions various classification plans, namely standard deviation, quantile, and natural breaks, and their advantages and disadvantages. As I suspected before, the chapter’s primary focus was to explain how stats and math are used to create maps. 

Chapter 4: 

The fourth chapter focuses on mapping according to density, and similar to chapter three, it consists of various economic and statistical terms. It starts with explaining why map density is essential and can be used in multiple areas with a specific type of data. Density maps can be helpful when looking at patterns. It helps with areas with a higher concentration, so I’m assuming that people with no knowledge will also be able to decipher the maps. The author also mentions that its important to decide what to map and what kind of data will be used so that it is compatible with the style. The book mentioned two ways of mapping according to density — By defined area, where you calculate a density value for each area using dot maps, and by density surface, which uses the raster layer mentioned in the first chapter.  Each cell in the layer gets a density value based on the number of features within a radius of the cell. Different comparing methods and ways to choose them were mentioned in the book to make it easier for students when they start mapping. 

Like chapter three, this chapter also included specific class ranges and colors for ratios for shaded maps. The book instructs on creating different types of dot density maps on different scales of data. It goes further on how to calculate density values by converting density units to cell units, searching for radius, and using different calculation methods and contours.