This chapter focuses on locating different aspects and patterns within the features of your map and how to analyze them. One important aspect to search through is your data, and there, you should start with the areas that you are mapping. If it’s a single area, you can figure out what information or patterns are specific to that area, but if you have multiple areas, you can compare them for your information. Additionally, you should recognize what types of data you have (continuous? discrete?) and if you need a count or a summary of an area. These can help you focus on certain types of information that are specific to your guiding question. Also within the area, you could analyze how features of your map interact with areas–do certain features only take place in certain areas, do they cross into multiple areas, etc.
There are three ways of finding information from inside your map. First, drawing your areas and features can provide you with very direct, visual ways of displaying and locating patterns. This type is also good for seeing patterns in or outside of a single area. Next, you can select certain features inside an area in order to find information. This is much better for finding lists or summaries of information. Finally, overlaying the areas and features with different layers requires more processing, but it can be very useful for determining which features are in several of your areas or how prevalent some feature is.
Frequency – the number of features with a given value or within a range of value, inside the area, and displayed at a table.
The most common summary of numeric attributes:
Sum. – the overall total number of something (like the total number of workers at businesses within a neighborhood)
Average/mean – the total of a numeric attribute divided by the number of features
Media – the middle value in the of a range of values
Standard deviation – the average amount of values away from the mean. This gives insight into how tight or loose the values are grouped.
Chapter Six
This chapter is all about maps that focus on places that are located close to the map’s subject, audience, or creator. It covers how to define what you need and how to actually find it before discussing how to add realities to what you are mapping, such as cost or time.
You are able to map categorical data such as cost or time, but most of the time, you’ll likely just need distance. It all depends on the information that you end up needing.
There are three ways of finding what you need–straight line distance, distance over a network, and cost over a surface. Straight line distance is the calculation of area within a features of your choosing, and it’s great for the creation of boundaries. Distance or cost over a network connects a source location to an aspect of the network within a chosen distance or cost. This is best for finding a location that matches distance or cost parameters (like, cannot travel for more than 20 minutes). Finally, cost over surface is where you take both aspects and specify the location as well as the travel cost.
If you want to find actual locations from your chosen feature’s source, you need GIS to calculate the actual distance between each location and the closest source.
When working with distance, it’s often recommended that you set a maximum distance, as without it, you can end up with extraneous data that does not realistically apply to your reason for mapping.
When measuring distance over a network, you should set travel parameters. This could include specifying cost for particular segments, turns, or junctions.
When finally getting information in your mapping that supports your question, you can further identify the area within a specific distance or summarize your data that is within the chosen distance parameter.
Chapter Seven
This chapter is all about celebrating the fluidity of society by mapping how certain phenomena change and grow over time, and using these changes to design a better future.
Change is important–it shows the trends of a time period, or what society deems to be relevant at the time. Change can come in several different forms, such as changes in location, in magnitude, or in character.
Your chosen features for your map is the best way to determine which area of change you should focus on. Yet, these features can also be categorized: features that move include discrete features and events, and features that change in character or magnitude include discrete features, data summarized by area, continuous categories, and continuous values.
When measuring change, you should also focus on the time period that you are using. What type of pattern are you using? Before and afters, trends over time (multiple events) or cyclical patterns are all good choices. Intervals are also important, as these can skew your data and/or presentation of data towards a different conclusion.
Another aspect to focus on is how much change actually occurs. Percent change is a common way to display how much occurred. How fast it changed is also good information to know.
There are three ways of mapping change: creating a time series, creating a tracking map, or measuring change. A time series is equivalent to mapping where the most or least are, but this time you are replacing it with certain dates. You will need to consider how many maps you’ll create. Tracking maps shows a certain feature at various points in time, and they are pretty useful for tracking discrete features. When measuring and mapping change, which is when you calculate the difference in value of a feature between two dates, you can calculate the change for discrete features, data summarized by area, continuous categories or continuous numeric values.
1 thought on “Abby Charlton – Week Three”
lots of stuff. will start to make more sense as you work thru the software tutorial and do a few applications in the “exam”
lots of stuff. will start to make more sense as you work thru the software tutorial and do a few applications in the “exam”