Answer Sheet - Mastering ArcGIS Pro Chapter 2 Questions Exercises (1)
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Mastering ArcGIS Pro
Chapter 2
Chapter Review Questions
1)
For each of the following types of data, state whether it is nominal, categorical, ordinal, interval, or ratio. Explain your reasoning.
Arsenic concentration in mg/L: Ratio because there can be 0 arsenic present.
Vegetation Type: Categorical because it represents a list of plant types that can be further
divided into distinct classes.
Annual precipitation in inches: Ratio because it has an absolute zero. It might never rain.
Zip codes: Ordinal data because zip codes are created by ranking different areas based on
demographic factors.
Social security numbers: nominal data because it ranks citizens and classifies them with numerical values.
Elevation of climate stations: categorical data because it separates stations into various groups.
Football team rankings: ordinal data, as the teams can be ranked with no true zero.
Number of students in universities: ratio if that list is being used to look at larger trends of where most college students come from/rankings per state, etc. It would have a meaningful zero.
Letter grades: ordinal data, as it quantifies a student’s score into a ranked category.
College majors: nominal because they serve just as an identifying label, name and category. 2)
For each of the following attributes, state whether a single symbol, graduated color, or unique values map would be most appropriate. Explain your reasoning.
Political party: unique values because each county can only belong to one political party
Lung cancer rates by country: graduated color because the data is numeric and can be divided up into certain classes to show variation.
Flow rates of wells in gallons/minute: graduated color map because the values are
numeric and can be divided up into certain classes to show variation.
River Flow volumes (cfs): graduated color map because the values are numeric and can be divided up into certain classes to show variation.
Restaurant locations: single symbol map, because each location can be represented by a unique symbol or icon.
Soil class, such as loam, clay, etc.: unique value map because each soil class can be differentiated by a unique color or pattern.
3)
If mapping the following attributes for counties, indicate which ones would generally be normalized, and discuss what attribute field should be used.
Average annual snowfall: not affected; don’t normalize
Home vacancy rates: not affected; don’t normalize
Native American population: this would be normalized by comparing it directly to
the total population. 5 out of 100 or 2% or something like that.
Median home price: not affected; don’t normalize
Number of crimes reported: should be normalized by the whole county population
Number of car accidents: can be normalized by population, area, or even miles. 4)
State whether a unique values, classified, stretched, or RGB composite display should be used for each of the following rasters, and justify your choice.
Land Cover Classes: unique values display since each area of the map can only belong to a specific class.
7-band satellite image: RGB composite display because many bands are present
Elevation: stretched display method to represent the full range of values but also possibly classed, too.
Black and white aerial photo: stretched display method to convey the various ranged and hues
Tree canopy: classified because it can be differentiated into distinct classes.
Slope in degrees: stretched display because it is continuous and can be represented into various colors. 5)
Explain the merits of unclassed maps as compared to classed maps.
Unclassed maps have continuous data that has shades applied to each value, giving the map much more detail. Classed maps group data into classes, which shows the bigger picture, but much of the detail is lost. Classed maps are for a more general audience. 6)
Describe the difference between a geospatial data set and a layer.
A layer points to a location within a certain geospatial data set, which is where multiple layers can be stored. 7)
Explain the difference between thematic rasters and image rasters.
Roads, geology, height, or vegetation density are all represented by thematic rasters. They can hold discrete things like highways or land use polygons as well as continuous variables like elevation that can exist anywhere on the surface of
the world. The usual approach for displaying thematic rasters is through a unique values or categorized display method.
Image rasters represent continuous data that are represented visually through light
and color scaling to portray scanned maps, aerial photography, or satellite imaging. 8) For each of the following map types, find a map from the internet that uses this type of symbolization: graduated color, graduated symbol (lines), graduated symbol (points), and unique
values.
Graduated color map
Graduated line symbol map
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Graduated point symbol map
Unique Values map
Chapter Tutorial Questions
1) What is the data type of these two attribute fields in the volcanoes data set?
Elevation is interval data and type is categorical data.
2) List two ways to open the symbology pane.
Right click the layer you wish to edit or go to the feature layer: appearance: drawing: symbology button. 3) What three values are found in this field? Examine the other fields for clues and list what the three values represent.
U for U.S. Highway
S for State Highway
I for Interstate Highway
4) What kind of data does population represent? What kind of map should be used to display it?
Ratio Data and one would use a graduated color map
5) What kind of data is elevation? What kind of raster display method(s) could be used to display it?
Interval data and a stretched or classified map would be best. 6) What type of data does this raster contain? What type of map should be used to display it?
Ordinal data with unique monochromatic values
Step 56 ignore
Chapter Exercises
In this exercise, follow the stepwise prompts described on pages 75 and 76 to build each map. Capture the map by using the “Export” function under “File” and saving each map as a jpeg file that can be inserted into this Word document (this will produce a much higher resolution image than taking screen shots and using Paint to crop the maps. You will be graded on each map in terms of 1) content (is it correct), 2) display (does it make sense/is it logical and well arranged), and 3) aesthetics (is it artful/pleasing to the eye). Be sure to describe your choice of data, choice of symbols and colors, and choice of classification methods and normalization.
Volcanic Hazards Map
Figure 1. Volcanic Eruptions contrasted by population density and their proximity to hospitals map. I went with a monochromatic orange color for the population density, as it best exemplifies the areas of the state with low and high populations. I also went a red triangle for the
known eruption, which are proportionally scaled based on number of eruptions, because it signifies the danger these events introduce. Finally, the hospitals are labeled with a blue cross outlined in white.
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Farm Density Map
Figure 2. Map portraying the density of farms and their relation to major highways, airports, and railroads. Farmland per county is distinguished by number of farms per square mile in each county, which is represented as a percentage. The roads and railroads are further distinguished based on class. Airports are also included, and counties are named.
Figure 3. Zoomed in section of the farms map. I included this map to help the viewer distinguish the yellow dots and get a better feel for the density, as this was taken from the highest density area of the state.
Household Vacancy Map
Figure 4. Household vacancy rates based on county and its relation to major cities. I went with a graduated color with a defined interval, which was normalized by total households.
The major cities are proportioned to represent their total population. Finally, a county’s vacancy rate is distinguished by a color that corresponds to a certain percentage, which is all shown in the
contents pane.
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Oregon Physiography Map
Figure 5. State and county boundaries of Oregon contrasted by a physiological image of the state’s landscapes. I chose a thick black line as the outline for the state and a pinkish thin line as an outline for the counties, as they provide enough contrast against the world imagery. This allows the viewer to not experience difficulty differentiating the information the map is presenting, which is the state and country boundaries.