Chapter 4: Mapping Density
Mapping density allows the user to see where the highest concentration of a feature is located and highlights patterns in areas of different sizes. There are two methods when mapping density: shading an area based on density value or creating a density surface. The method should be based on the data type; the GIS program uses a density surface to map features, and map data is usually already summarized by a defined area (counties, forest districts, etc.). Mapping density by defined area is commonly created using a dot map, which represents the density of individual locations summarized by defined areas (each dot represents a specific number of features and is not based on the features’ actual location). To calculate the density value for the area, the user can divide the total number of features/total value of features by the area. The density surface is created in GIS as a raster layer, with each cell in the layer getting a density value based on the number of features within the cell’s radius. Users should map by defined area if their data is already summarized by area or map by density surface if they want to see the concentration of point or line features. Density by defined area is calculated based on the areal extent of each polygon and is usually displayed as a shaded map. In a dot density map, the user maps each area based on a total count/amount and a specific value of how much each dot represents. Then, GIS divides the value of the polygon by the amount represented to figure out how many dots to draw in one area. A dot map represents density graphically, and the individual dots represent total numbers/values in each area rather than a calculated density value. GIS creates density surfaces as raster layers with a specific calculated density value for each cell in the layer, which is good for showing where/how point/line features are concentrated.
Chapter 5: Finding What’s Inside
Users map the inside of an area to monitor and understand what is occurring inside a given parameter and compare it to several other places; this provides the user with an idea of what is happening and where to take action. There are three ways users can define their analysis to find what is inside a given parameter, including drawing an area boundary on top of the features, using an area boundary to select the features’ insides and list or summarize them, or combining the area boundary and features to create summary data. Finding what is inside a single area allows the user to monitor activity/summarize information about the area (e.g., an administrative/natural boundary such as a watershed). Finding what is inside several areas allows the user to compare the areas (e.g., a group of zip codes). The features inside a given parameter can be discrete, unique identifiable features, or continuous, seamless geographic phenomena. By drawing areas and features, the user can show an area/feature’s boundary and then see which falls inside/outside the boundary. When selecting the features inside the area, the user specifies the area and the layer containing the features, then GIS chooses a subset of the features inside the given area. When overlaying the areas/features, GIS combines the areas/features to create a new layer with the attributes of both or compares the two layers to calculate the summary statistics. When choosing the best method for the user’s data/results, they should follow the guidelines to select the most appropriate method. First, the user should draw the area/features if they have a single area and only need to see the features within that selected area. Select the features inside if you have a single area and make a list/summary of discrete features that are fully or partially inside. Overlay the areas and features if there are multiple areas with a summary of what’s inside each, there is a single area with a summary of discrete features, including the portion of features, or there is a single area with a summary of continuous values.
Chapter 6: Finding What’s Nearby
User map change to gain insight into how features/factors behave to anticipe what future conditions may be like, decide on a course of action, or elevate the results of an action or policy. Users can demonstrate change in an area by showing the location/condition of features at numerous dates or calculating and mapping the difference in specific values for each feature between two/more dates. Geographic features can show change in two ways; either through change in location or change in character/magnitude. Mapping a change in location allows the user to see how features will behave in the future allowing them to predict where future movements may take place (e.g., mapping the patterns of hurricanes throughout the months). Discrete features can be tracked as they move through space over time, these can be individual features (an animal), linear features (a river), or an area feature (boundary lines). Events represent geographic phenomena that can be tracked and occur at different locations over time (movement of crimes in a given area over time). Mapping a change in character/magnitude shows how the same condition in a given location has changed over time (e.g., changes in categories of land cover in a watershed now vs 20 years ago). Discrete features can change in character/quantity of an attribute associated with them (e.g., changes in traffic volume over a 24-hour period). Data summarized by area are totals, percentages, or other quantities that are associated with features within a defined geographic area (e.g., population in each county for each year). Continuous categories demonstrate the type of features in a given area, represented by boundaries or as a surface. Continuous values are measurements that are monitores at fixed points and are always available, such as air pollution. The time pattern being used to measure can be mapped in three ways; as a trend (change between two dates/times), as a before and after (conditions before and following an event), or as a cycle (change over a recurring time period). Change can be mapped in three ways, through a time series (one map for each time/date showing the location or characteristics of the features over time), a tracking map (a single map showing the location of the features over time), or measuring change (the amount, percentage, or rate of change in a specific place).