Munroe – Week 3

Chapter 5

Chapter 5 is concerned with defining and analyzing what’s inside of the areas you’ve created using ArcMap. To begin, the chapter discusses defining analysis, specifically how many areas and what features are inside the areas. If you were to select a single area, you’d be focused on a specific, controlled area which could be something like a manually drawn territory or a natural boundary. Multiple areas would pertain to zip codes, disjunct parks or counties. Then, you have to determine if the features are discrete or continuous, where discrete are unique, identifiable features and continuous are seamless geographic phenomena, either spatially continuous or continuous values. Then, you need either a list, count or summary. With this step, you also need to determine if your values can be partially inside or outside of the boundaries, and how you want to quantify them. The chapter then discusses the three methods of finding what’s inside. These are drawing areas and features (which are good for finding out whether features are inside or outside an area), selecting the features inside the area (getting a list or summary of features inside an area) and overlaying the areas and features (good for finding which features are inside which areas and summarizing how many or how much by area). When you’ve selected features in the area, you can visualize results by count, frequency, or a summary of numeric attributes, using either mean, median or standard deviation. The chapter then finishes with how to overlay areas and features. First, overlaying areas with discrete features then overlaying areas with continuous categories or classes, where GIS tags each feature with a code or the area it falls within and assigns the area’s attribute to each feature. Second, overlaying areas with continuous categories or classes, where GIS uses vector or raster method to overlay areas with continuous categories or classes. Lastly, Mitchell mentions overlaying areas with continuous values, where GIS finds out which cells fall within each area and calculates the statistic for the characteristic you’re interested in and assigns the value to each cell it’s identified.

Chapter 6

Chapter 6 moves on to finding what’s nearby. A theme I’ve caught on to with these chapters is that Mitchell always wants to start with defining analysis. For this chapter, he talks about measuring what’s near whether it’s by set distance or travel to feature, cost or distance, or distance over flat plane or using earth’s curvature. Then, he asks us for the necessary information, meaning list, count, summary, distance or cost ranges, specifically inclusive rings or distinct bands. Mitchell goes further with defining three ways of finding what’s nearby. Straight line distance (good for creating a boundary or selecting features at a set distance around a source), distance or cost over a network (good for finding what’s within a travel distance or cost of a location), or cost over a surface (good for calculating overland travel cost). For straight line difference, you can either create a buffer to define a boundary and find what’s inside, select features to find features within a given distance, calculate feature-to-feature distance to find and assign distance to locations near a source, or create a distance surface to calculate continuous distance from a source. For measuring distance or cost over a network, you first specify the network layer, assign street segments to centers and set travel parameters. You can also specify more than one center and select surrounding features to be included in the map. Lastly, with calculating cost over a geographic surface, you begin by specifying the cost (where GIS totals the cost as it crosses each cell from the source, assigning a cumulative cost to each cell in a new layer it creates) and then modify the cost distance.

Chapter 7

The book finishes with mapping change, where we once again define our analysis. Mitchell mentions two types of change: change in location (seeing how features behave so you can predict where they’ll move) and change in character or magnitude (showing how conditions in a given place have changed). The type of features you choose to map also matter. They can either be discrete (physically move) or change in character or magnitude (events that represent geographic phenomena that change location). Additionally, you have to quantify time. It can be a pattern (trend, before and after or cycle) or partition (two or more times or dates or several time periods). Once you’ve determined this, you have to decide what you want to take away from the analysis. It can be how much it has changed (talking about change in magnitude or percent change) or how fast it changed (measuring the rate of change over time). There are three ways of mapping this information. The first is a time series, showing changes in boundaries, values for discrete areas or surfaces which is good for movement of change in character. This is good for strong visual impact, but readers have to visually compare the maps to see where and how much a change has occurred. The second is a tracking map, good for showing movement in discrete locations, linear features or area boundaries. This makes it easier to see movement and rate of change especially when subtle, but can be difficult to read if there are more than a few features. The third is measuring change, showing the amount, percentage, or rate of change in a place which is good for change in character.  This will show actual difference in amounts or values, but doesn’t show actual conditions at each time and is calculated only between two times.