McConkey – Week 3

Chapter 5: 

Chapter 5 deals with mapping what’s on the inside a designated area. Sometimes you will already have boundaries available in ArcMap but other times you will need to draw this area or areas on top of the features manually. The chapter lists several reasons you might want to map data inside a boundary, but as always it is important to keep in mind what you are trying to accomplish and how that will affect your approach. Mapping a single area will be different than mapping multiple areas while handling discrete or continuous data will affect your approach. Mitchell also notes that it is important to have some type of label whether it is a number or a unique name for each area mapped. The three ways of finding what’s inside are described as drawing areas and features, selecting the features inside an area, and overlaying the areas and features. Drawing areas and features are the easiest and most simple method, but it really only gives you a visual representation and not information about the features inside. Selecting the features inside an area allows you to get info on what is happening in a single area, but you are not able to see what is happening in each of several areas. For example, a map of parcels within a watershed using this method will let you see which parcels are within the watershed, but may not distinguish the type of parcels. With this method, you can use GIS to create a report of the selected features or statistical summaries. This data can come in the form of a count, frequency, or as a summary of a numeric value (i.e. sum, average, median, or standard deviation). Overlaying the areas and features avoids this by allowing you to see what is within each of several areas (i.e. parcel type), but it requires more time and processing than the other methods. Overall, I really liked this chapter and the examples provided. 

Chapter 6:

Chapter 6 deals with mapping what’s nearby a feature. There are many reasons why you might want to find out what is occurring within a set distance of a feature or to find out what is within traveling range. Reasons could involve legal policy decisions, business or environmental precautions, or simply a scientific analysis of an area. While distance can define or measure the proximity or features, travel costs may also be used. Travel costs, which may include time and money, may vary even if the distance between a set of features is the same due to other factors. For instance, it will cost a car more gas money to traverse a highly trafficked area rather than a relatively low trafficked area. It would also take less time for a deer to cross a valley to get to a stream than it would to cross a deeply forested area. In this way, the valley has a lower travel cost. Something to keep in mind is whether you are considering the curvature of the earth in your distance calculations or not. The planar method is used for smaller areas that can generally be observed as flat, while the geodesic method is used for larger areas where the curvature of the earth is taken into account. You may not think the curvature of the earth would need to be considered when dealing with relatively small areas, but major bridge constructions sometimes have to account for the earth’s curvature as the tips of supporting structures will be further apart from each other than they are at their respective bases. Information from an analysis can come in the form of a list, a count, or a summary of statistics.The reading describes three ways of finding what’s nearby: straight line distance, distance or cost over a network, and cost over a surface. As always, each method has its own uses, pros, and cons. Straight-line distance is used for defining areas of influence near a feature or selecting features at a set distance around a source, which gives an approximation of travel distance. Distance or cost over a network measures travel distance or cost of location over a fixed network or infrastructure, but requires a network layer. Cost over a surface is used for measuring overland travel costs and determines how much area is within the travel range. The rest of the chapter goes over these methods and guides you through making and modifying distance maps. Overall, I liked this chapter even though distance cost was a new concept for me. The chapter does a good job of describing why it might be important to calculate the distance between features (with the respect of area). 

Chapter 7:

Chapter 7 informs why it may be important to map change over time. Mapping changes over time is one of my favorite uses of GIS technology as it can be applied to countless environmental questions. Mapping changes over time is a great way to visualize patterns and predict future changes. This could involve examining weather patterns, changes in land use, or changes in population density. When mapping change it is important to remember the types of changes that exist. For instance, the book outlines changes in location, character, or magnitude, which all can describe geographic phenomena. Recognizing the types of features, such as discrete or continuous, is vital for choosing the appropriate method to map change. Measuring the time pattern is also key to mapping change. The three types of time patterns described are trends, before and after events, and cycles. Snapshots may be used to capture a set of conditions at one point in time, such as land cover or population data. Summarizing can be used to map discrete events that are not continuous in time. An example of this would be summarizing the daily precipitation for a region into monthly averages, which may show trends in weather patterns and may allude to the overall climate of the region. When mapping trends it is necessary to consider intervals, the number of dates, or total period. For instance, depicting urban sprawl annually may have as much of an impact when comparing the sprawl across several decades. For mapping cycles, a snapshot or summarization over a period can be used depending on whether the data is continuous or discrete. The chapter also lists three ways of mapping change. A time series is good for depicting changes in boundaries, surfaces, or values of discrete areas, which can lead to a strong visual impact. Tracking maps are great for showing movement in discrete locations, area boundaries, or linear features. These maps can become cluttered and difficult to read if there are more than a few features. The measuring change method involves showing the actual difference in values or amounts between two times only. This type of map only shows the change and not the actual conditions at either time. The rest of the chapter delves deeper into these methodologies and how to apply them appropriately. In conclusion, I don’t think the book could have ended on a better chapter since the earth and its features are constantly changing. As human beings, we are fascinated by change, so being able to map change is really rewarding and can lead to new insights to our behavior and geographical phenomena.