Howard Week 2

Mitchell Chapter 1-

I found this reading much easier to understand than the previous week’s reading. Its format, how it breaks down the information, makes me feel more confident about the information presented. I especially appreciated the step by step guide on the process of GIS analysis- frame the question, understand your data, choose a method, process the data, and look at the results. I learn best when steps are clearly laid out for me to re-write to help memorize them. Also, geographic features are broken down into discrete- pinpointed locations, continuous phenomena- values assigned between points or enclosed boundaries, and summarized by area- a data value applied to an entire area instead of any specific location within it (ex. demographics). You also represent geographic features in GIS through either a vector- features are rows on a data table, or raster model- features are a matrix of cells in continuous space. There are subsections of the geographic features I previously mentioned, which are called geographic attribute values. The types of attributes are categories- groups of similar things represented using numeric codes or text, ranks-which put features in order from high to low based on feature attributes, counts and amounts- which shows the actual number of features on a map or any measurable quantity associated with some feature, ratios- show the relationship between two quantities, created by dividing one quantity by another for each feature, and common ratios are proportions and densities, continuous (not including categories and rank attributes) and noncontinuous values- which is a way to know how the values are distributed to help group them. The last part of the chapter shows how to use the data tables in the GIS software with a step by step process. The common operations you use in data tables are selecting- choosing features to work with a subset of them or assign a new attributed value to those features, calculating- to assign new values to features in a data table, and summarizing- to summarize the values for specific attributes to produce statistics.

Chapter 2-

This chapter focuses on mapping where things are and beginning to understand why things are the way they are. The first subsection is “why map where things are” describes the benefits of looking at a distribution of features on a map, which help you more easily identify patterns, in comparison to looking at just individual features. Mapping where things are can show you where on a map you need to take action, or the specific areas that meet your criteria, and explore causes for the patterns you see. The next subsection, “deciding what to map” states that in order to look for patterns in your data you need to map the features in a layer using different types of symbols. What information you need from your analysis will help you display the features, like where they are and are not, map the location of different types of features and if certain types occur in the same place. You should use the map based on your intended audience for the issue you’re addressing. The next subsection is “preparing your data,” which is making sure your features have geographic coordinates assigned to them- either using the databases or mapping it by hand, and that your features have assigned category values- a code that identifies its type, and can be divided into subtypes as well. “Making your map” is the next subsection, which describes the features you tell the software that you want to display, the symbols to use to draw them, and that you can map all your features in a layer as one type or show them by their categorical values. It also describes what the GIS does for each way to map features. This subsection is very in depth and I will most likely refer to it fairly often. The last subsection is “analyzing geographic patterns,” and describes multiple ways features in a category can be presented as, such as a clustered, uniform, or random distribution, for example. Patterns can be the result of multiple factors, and any patterns that you can’t see just by looking usually need statistics to measure and quantify the relationship. 

Chapter 3-

This chapter describes what mapping the most and the least entails, how to do it, and its benefits. The first subsection, “why map the most and the least,” explains that people map where the most and the least are to see the relationships between places or to find places that meet their criteria, by mapping features based on a quantity associated with each. “What do you need to map” is the chapter’s next subsection, describing what you need to do to decide how to best present the quantities to see the map’s patterns. You can map quantities associated with the geographic features listed in chapter one, and make sure to remember the purpose of your map and its intended audience when deciding how to present your information. The next subsection, “understanding quantities,” describes how you need to assign symbols to features based on an attribute that contains a quantity- amount, ratio, or rank. Counts and amounts show total numbers and allow you to see the value of each feature and its magnitude compared with others, ratios show the relationship between 2 quantities and can even out differences between small and large areas, or areas with many or few features, so the map more accurately shows the features’ distribution, and ranks put features in order from high to low and care useful when direct measurements are difficult or if a listed quantity represents a combination of features. “Creating classes” helps you decide two to represent your quantities on a map, either by assigning each value its own symbol or grouping values into classes, typically based on which feature you choose to map your data. The 4 most common classification schemes, natural breaks, quantile, equal interval, and standard deviation are also explained and compared to each other in depth. “Making a map” is the next subsection, and describes the options GIS has for creating maps to show quantities- graduated symbols, graduated colors, charts, contours, and 3D perspective values, along with creating the view, z-factor, light source, and perspective view very in depth. “Looking for patterns” tells you to either look at the transition between the least and most are, whether values cluster or not, to see how the phenomena behaves.