Chapter One:
This chapter was an introduction into GIS. The groundwork for GIS was provided by defining it as a process for examining spatial patterns and relationships of geographical features. GIS analysis starts with a question just like in a research hypothesis. From that question data is collected, modeled, and then presented. The process of GIS can be simply put as framing the question, understanding the data, choosing a method, processing the data, and then looking and interpreting the results. Three main types of geographical features are mentioned. These are discrete features which can be defined as a distinct point where the feature is either present or not like a stream or land value. The second is a continuous phenomena which can be measured anywhere and encompass an entire area such as temperature or rainfall. Lastly features summarized by area which is the amount of something in a specific area such as people per house in a county. All of these features can be shown with a vector model or raster model. Geographical attributes is another major concept which adds meaning to features such as categories- qualitative types, ranks- ordering, counts and amounts- numeric totals, and ratios- numerical relationships. The utility of tables in GIS for selecting, calculating, and summarizing information is a key component of analysis.
What I noticed is how GIS blends different data together to create one source of information. It is also about more than looking at maps but also finding the answers to spatial questions. Accuracy and perception have a huge role on one another. The way it is presented can change perception of the data.
Is there a way to minimize distortions for large areas or do we simply just choose where it has the least effect?
Chapter Two:
This chapter focuses on the practical side of GIS mapping. It explains that the maps help to reveal geographical patterns not just showing the locations. It helps to explain or show why features are there. Each map has multiple layers with different features assigned and symbols for their features. Mapping can be done in a few different ways. These are showing all the features as a single type- having the same symbol for each feature, displaying categories- different symbols/ colors per type, or mapping subsets- features filtered to highlight a theme. It is also warned against overloading a map as we as humans can only really work with seven categories at once. This is due to it getting too hard to tell different categories apart. Due to this, grouping categories together can be helpful and sometimes necessary. Scale and audience are also important. Those who are map experts can distinguish more details than the average person as they have a more trained eye for the smaller details. Geographic coordinates- addresses, latitude, and longitude are a requirement that one must be very careful with. This ensures that placement is accurate.
The crossover between science and communication are shown throughout this chapter. The choice of colors, symbols, and reference features are very important for the design of a GIS analysis and also correlates with psychology and design.
When it comes to grouping categories what guidelines should one be thinking of to avoid oversimplification or messing with the data.
Chapter Three:
This chapter focuses on comparing places based on quantities and where things do and don’t occur. This requires using quantities, can be in a few different forms, ratios, counts, amounts, etc. This chapter has classification schemes to group data values into classes, natural breaks (jenks)- groupings and patterns inherent in your data, so values within a class are likely to be similar and values between classes different, quantile-an equal number of features in it, equal interval-equal range of values, the difference between the high and low value is the same for each class, and standard deviation-distance from the mean value of all the features. Graduated symbols-symbols of different size to represent a variation can be used for mapping as well as graduated colors- colors that get darker or lighter depending on the data in that area, charts, contours- lines around to show variation, and 3D perspective views- looking at something from the side to help show the elevation. These all help to show the continuous phenomena. Ratios are important to normalize data values and allow for fairer comparisons across an area. There is a balance between precision and readability where too many classes or decimals can obscure the meaning while too few can hide something.
This chapter helped me to realize how much power analysts hold when interpreting something. The same data sets can produce different results depending on how it is interpreted. There is a strong link to map-making and statistical choices. Outliers can also affect the data and how they are taken within a data set.
Should consistency be prioritized by analysts while using classification schemes or flexibility?