Richardson – Week 3

Chapter 5

This Chapter of Mitchells, The ESRI Guide to GIS Analysis, focuses on “Finding What is Inside” of the image you are looking at. Sometimes, you only want to focus on a singular part of the image. Say for example, you have a map of types of agriculture in Ohio, but you only want to focus on Northeast Ohio. You can choose to only analyze a single area in order to get the full picture. You can also section your analysis based on things like county lines, and zip codes. You can also make this analysis discrete or continuous, like Mitchell discussed in earlier chapters. There are three ways of finding what’s inside. By 1, drawing areas and features, 2, selecting the features inside the area, and 3, overlaying the areas and features. Drawing areas and features is good for finding out whether features are inside or outside of the designated area. However, this method is not very specific, and often cannot provide the information needed for a full analysis of the map. Selecting the features within the area is good for summarizing the features inside, but it is only good for evaluating one single area, not a collection of larger areas. Overlaying the areas and features is good for finding out which features are inside, and how dense these features are. However, this process is quite extensive, and requires more processing. Mitchell also describes how it can be good for evaluating the data if layers are overlapped with discrete and continuous data. For example, you could have the discrete layers of land plots overlap with a floodplain. We can directly see which areas are being impacted. We can also do it inversely, by mapping continuous data of types of land, and over laying boundary lines over it. With these overlapping boundaries, you can then get a list of attributes of a given area within the image, whether its number of people, number of species, density of population, etc. We can overlay boundaries in GIS using either a vector or a raster model to ensure that all variables are both together in an image and sorted separately. The vector model is almost the overlaying of 3 separate images mapping different variables, and putting them all together. The raster model is the sort of “cookie cutter” image going into a figure to display the area of interest. 

Chapter 6 

This Chapter of Mitchells, The ESRI Guide to GIS Analysis, focuses on “Finding What’s Nearby”. This is useful for knowing what is in the general area of the location you are concerned with, and if surrounding areas could be impacted by what you are surveying. For example, we could look at nearby floodplains that are near a body of water that are at risk of floods, or houses near intersections of the highway that could be susceptible to effects of eminent domain. Measuring how near something is can be used in distance, or in cost, or “travel costs”. If something is very far away from the desired location, things like heavy traffic and gas prices could be a barrier of distance. For example, if you are mapping how close streets and homes are to a fire station, the streets that are within ¾ of a mile, and are within a 3 minute drive of the fire station represent very different parts of the town. You also need to account for the size of the area you are looking at. For smaller areas, you can look at this on a planar method. But if you are looking at something larger like a continent or the world, then you need to use a geodesic method, based on the curve of the earth. You are able to summarize what is within this nearby area and turn these variables into quantified data as well. You should use the straight line distance method “if you are defining an area of influence or want a quick estimate of travel range”.  You should use the cost or distance method if you are “measuring travel over a fixed infrastructure to or from a source.” You should use the cost over a surface if you are measuring overland travel. It is also helpful to use color coding legends in the figure to depict the distance from the point you are evaluating. 

Chapter 7 

This final chapter of Mitchells, The ESRI Guide to GIS Analysis, focuses on “Mapping Change”. This section specifically focuses on how to represent data of change over time, and how the characteristics of the area change as time progresses. An example of this, could be a representation of sea level rise over time. The first image that you show might depict sea levels in the 1950s, and then sea levels today, and then where sea levels are expected to be in the coming decades. A large reason for this according to Mitchell is to “anticipate future needs” and to “gain insight on the behavior of a certain event or region”. You can also use mapping change to show how a certain object or thing is moving locations over time – an example of this might be a representation of how the migration patterns of certain bird species are evolving due to the changing climate and weather patterns. This might show us two completely different regions of the world, but is still mapping the change in some variables. You can represent a change in a figure through three different types of time patterns: a trend – a change between two (or more) dates and times, before and after – conditions preceding and following an event, or a cycle – change over a recurring time period such as a day, month, or year. However, you do not want to use too broad of a time frame, nor do you want to use too many data points of comparison, because the main difference between the change in figures might be lost, and the message of the data may not be as clear as you desired. Mapping the change in a set of data is very important in order to understand how we are evolving, and what the trends are for future expectations.