Mitchell, chp. 1,
Andy Mitchell describes GIS as “a process for looking at geographic patterns in your data and at relationships between features.” (Andy Mitchell, 2020, pg 3). This description of GIS narrows down the broad field of GIS mapping into an understandable description of how GIS analysts collect data and record patterns to create a multilayered model of recorded data. As described in the textbook, collecting this data is similar to the typical scientific method. This process consists of asking a question, understanding your data, choosing a method, processing the data, and analyzing results of the process. In GIS, there are continuous phenomena, which are continuous data that starts as sample points. GIS analysts then assign values to the area between these sample points. This process is known as interpolation. This process is crucial for collecting precise measurements and recording data of an area over time. It is crucial to note that you can also treat some noncontinuous data as continuous to create maps that highlight how quantities may vary across a given location. This process helps fill data gaps from unmeasured areas and simplifies complex, intricate data.
Additionally, GIS utilizes map projections and coordinate systems to ensure accurate results when combining data layers. “A map projection translates locations on the globe (which is almost a sphere) onto the flat surface of your map. All map projections distort the shapes of the features being displayed, as well as measurements of area, distance, and direction.” (Andy Mitchell, 2020, pg 13). The quotation explains that a 3D sphere is translated onto a 2D map, and this process distorts the features to compensate for the dimensional change. This is one of the main complexities in GIS and topography: changing the 3-dimensional measurements into a tangible 2-dimensional mapping system.
Mitchell, Chp. 2,
The second chapter varies from the first by describing the processes of mapping, where things are in relation to their location on maps. You must first ask what information you need and how you will use the map. After concluding the intent and required data, you must prepare your data, such as coordinates and assigned category values. The category values portion of the data is crucial to assign features to a correlated code in order to categorize them. I found this portion of the reading fascinating due to how you categorize the data by hierarchical types and subtypes in order to create organization within the masses of data to maximize simplicity and efficiency. After you have prepared and organized the data, you can begin actually creating your map. You can map all single features or subset features in order to create more intricate data that reveals patterns that are not always apparent with just single features. The GIS system’s role in this process is to store the location of each feature as a set of coordinates or pairs. Various unique symbols are used to pinpoint the locations of the features that you input. The textbook expresses that you typically want to include 7 or less categories because more than this can create difficulty in seeing the patterns. You can have more than 7 categories in your map however, you want to group the categories into each other to make them easier to identify. In order for your map to be meaningful, you want to utilize recognizable features such as landmarks like highways, towns, rivers, etc. You can also use reference features specific to your map and analysis to observe the relationships in the data. An example of reference features could be if you’re mapping the growth of a fast-food chain, you could map the nearby competitors that contribute to fluctuations in data and have geographic relationships.
Mitchell, Chp. 3,
The third chapter expresses the importance of grouping the map data based on quantities and mapping the most and least. Mitchell, Chp. 3 explains this by saying, “Mapping features based on quantities adds an additional level of information beyond simply mapping the locations of features. For example, mapping the locations of businesses gives a sense of where workers are, information that might be useful for a transportation planner. But mapping the businesses based on the number of employees at each business gives a much better picture of where employees are.” (Andy Mitchell, 2020, pg 52). After reading this chapter, this description and example helped me understand the different utilizations of mapping locations and features like I described previously, and mapping quantities in order to add additional information and create a more organized map. The example that Mitchell used highlights how the locations of employees can be extremely useful for certain data, but the quantifiable number of employees at each individual location paints a much better picture of where each employee is across the different locations. The quantities that you are mapping (most and least) can be categorized in counts and amounts, ranks, and ratios. Counts and amounts display the total value of each feature and its extent in comparison to other features being recorded. It is important to note that counts are used for the actual number of features, whereas amounts are used for describing the total value associated with the features. Ratios, however, show the relationship between various quantities that are collected by dividing one by the other to collect ratios like proportions and averages. Rank these features in order in terms of highest to lowest of the recorded data. An example of a rank: maybe if you’re collecting data on thriving tree species in an area, you would rank the strongest trees at the top of the rank and the weakest at the bottom. These 3 forms of data organization help to sort large quantities of data into understandable and observable sections.
Sources:
- “Andy Mitchell’s, May 26, 2020, Esri Guide to GIS Analysis, Volume 1, Second Edition (Chp.1, pg.3), (Chp.1, pg. 13), (Chp.3, pg. 52)