Andisman, Week 3

Chapter 4 Mapping Density

Mapping density allows for the visualization of the concentration of the values that you are studying, therefore, displaying patterns potentially indicating what action needs to be taken if areas meet your criteria. Mapping density is often displayed through degrees of color and can be in a general/fuzzy display like weather radar or clear separation such as with states, or through the distribution of symbols such as in dot density. Density can be achieved by simply mapping the locations of features. Using measurement units such as hectares or square miles, map density shows you distribution across the area. Density can be useful for something like population. It is important to note the difference between mapping features and feature values. Features could be the locations of businesses, or feature values could be the number of employees at each business, and therefore the patterns visualized with density can be very different and used for different purposes. There are two ways to create a density map, either by defined area or by creating a density surface.  Density value for an area is calculated by dividing the total number of features or total value of features by the area of the polygon. A density surface is typically created with GIS as a raster layer. This is a more detailed approach but requires more work. Use map density if you already have data, lines, or points summarized by area. On the other hand, use density surface if you have individual locations, sample points, or lines.  

 

Chapter 5: Finding What’s Inside

This chapter explores three ways to see whether an activity is happening inside an area or summarize information from multiple areas to compare. An example of this could include monitoring specific types of arrest, or chemical exposure. This can be done within a single area, or several areas. This chapter also recalls differentiating discrete vs. continuous features. The first of the three ways to find what’s inside is to draw areas and features by making a map that shows the boundaries of the area. This approach visualizes whether or not the features you’re looking at are inside or outside an area, and you need a dataset containing the boundary of the area and another dataset containing the features. Another approach is selecting the features inside the area. You do this approach by specifying the area and the layer containing the features so that GIS can select a subset of features inside the area. This approach is beneficial for generating a list/summary of features in an area and needs a dataset containing the areas, a dataset containing the features, and, if any, attributes you want to summarize. Finally, the last approach is overlaying the areas and features. With this approach, GIS combines the area and features to create a new layer with the attributes of both. It is good for finding features that are present in multiple areas, and needs a dataset containing the areas and a dataset with the features. When selecting which approach to use, consider the guidelines for choosing: If you have a single area and only need to see the features inside, use the draw the areas and features approach. On the other hand, if you have a single area but need a list or summary of discrete features fully or partially inside. Finally, use the overlay option if you have multiple areas or need a summary of continuous values. 

 

Chapter 6: Finding What’s Nearby

This chapter focuses on the aspects of looking outside the target area’s boundaries and assessing what is nearby within a set distance. It can help for  tasks such as monitoring  occurrences, examining nearby relevant factors, or addressing impacted nearby areas. ‘Traveling range’ is a noteworthy term for this chapter, and can be measured by distance, time, or cost. Similar to finding what’s inside, there are three approaches to finding what’s nearby. You can measure straight line distance, measure distance or cost over a network, or measure cost over a surface. It is important to understand and consider the nearby features because what is outside the focused area may be highly relevant to the internal mapped area. This outside distance is called the feature’s area of influence. Straight line distance is used for defining an area of influence around a feature, creating a boundary, or selecting features within the distance and is a relatively easy approach that measures distance. Though, it only gives a rough approximation of travel distance. Distance/cost over a network is used to measure travel over a fixed infrastructure and has the capability to measure distance or cost, though can be more in depth because it requires an accurate network layer but offers a more precise result. Finally, using cost over a surface is used for measuring overland travel and calculating how much area is within the travel range. It has the ability to measure cost and gives you the ability to combine several layers, however, it requires some data preparation to build the cost surface.  

 

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