TUTORIAL TWO: MAP DESIGN

In this presentation we will elaborate more on the importance of Choropleth Maps, Group Layers, Scales, Attribute Classification, Definition Queries, Hyperlinks, and Map Tips.

CHOROPLETH MAPS

Choropleth Maps are maps that use graduated colors to show change in statistical data.

When making a Choropleth Map it is important to pick colors that are easy to contrast from each other.

Another important component of Choropleth is the value assigned to each color. But we’ll get into that more when we talk about attribute classification.

CHOROPLETH MAP: THE GOOD

In this example we see the 2000 population of the United States. The coloring is good because we can easily look at the map and see that lighter colors are low population and the darker colors are the higher populations.

CHOROPLETH MAP: THE BAD

This is the same map as the last slide with a different color scheme. Beware when picking colors. The change in color is not as easy to see in this map as the previous map because the two colors chosen were too similar to each other.

CHOROPLETH MAP: THE UGLY

This is again the same map but with a new scheme. Now it is easy to tell difference with this map, however a person would have to look at a legend for every color. It is always best to use different shades of only 1 to 3 colors that are somewhat similar.

GROUP LAYERS

Group layers are a tool to improve organization

With group layers we can group like shapefiles together and set parameters that all the shapefiles will obey.

Group layers are very helpful when handling projects at different extents. This gives us the ability to turn whole groups of shapefiles off so that we can work at different extents without clutter.

EXTENT SCALES

Extent Scales are a tool that can help in map building and in interactive maps. It does this by turning layers on and off at certain extents.

It helps in map building because it will prevent some shapefiles from cluttering your view while you work.

It helps in interactive maps because at far extents you will see a broad view, however when you zoom in the extent scale settings will turn on more detail.

Extent Scales are often used in interactive maps like Google Earth, Bing Maps and Yahoo Maps.

EXTENT SCALES: THE CLUTTER PROBLEM

In this view all layers have no extent view. As you can see the map is a little confusing. Only three states have counties. Also the cities are covering much of the counties at this extent. In the next slide you will see how this problem is fixed by applying an extent scale.

EXTENT SCALES: THE SOLUTIONIn these maps I created group layers of what I wanted and then assigned each an extent scale. As you can see the one to the left does not display the counties of the three states. We only see the States and US cities.

The map to the right is a zoomed in view of the same map and the counties of the three states are now visible and the cities are not so that they do not hide any counties. If I wanted I could add another cities shapefile and have it turn on if I zoomed in closer to the counties.

ATTRIBUTE CLASSIFICATION

Earlier we talked about Choropleth Maps, now we will talk about how to change the values that those colors will represent. These will also work with graduated symbols as well.

The following classifications we will be talking about are: Natural Breaks (Jenks) Equal Interval Defined Interval Quantile Geometrical Interval Standard Deviation Manual

ATTRIBUTE CLASSIFICATION: NATURAL BREAKS (JENKS)

Jenks sets breaks at naturally occurring gaps between groups of data. The range of each gap will vary and so will the number of features in each gap. This method of classification works well with many sets of data and is often used. However as you can see the numbers are not rounded. While the distribution might look nice the legend looks sloppy. We will talk about this a little bit later.

ATTRIBUTE CLASSIFICATION: EQUAL INTERVAL

The equal interval method places breaks were the range of the breaks are all an equal value. Using this method is common when you desire showing ratios. When used in the map to the left it shows you that a majority of the states fall into one category. Also the numbers in the legend are not rounded, this would be fine in some cases but for public view rounded numbers are preferred.

ATTRIBUTE CLASSIFICATION: DEFINED INTERVAL

The defined interval method works very similarly to the equal interval, the only difference is that you get to choose what the interval is. Then the program will assign as many breaks as it needs to include all the features. As you see the numbers in these legend is much neater looking than the previous legends but the distribution is not as nice as the natural breaks.

ATTRIBUTE CLASSIFICATION: QUANTILE

The quantile method will place the same number of features into each class. This is only good for data that has a linear distribution. As you can see this map differs greatly from the maps that you were shown before. That is because the breaks are of varying ranges so this would never be a good way of showing population. The legend shows you the differences in the breaks.

ATTRIBUTE CLASSIFICATION: GEOMETRICAL INTERVAL

The geometrical interval method creates each break by multiplying the previous one by a coefficient. This method is best used with continuous data like pH, temperature, or precipitation.

ATTRIBUTE CLASSIFICATION: STANDARD DEVIATION

The standard deviation method finds the average of the field of interest (population in this map) and then tells how many standard deviations each feature is to the average. This is a good method to use is you want to show which features are below average, average, or above average. Another advantage of using the standard deviation method is that the legend looks more professional and appealing.

ATTRIBUTE CLASSIFICATION: MANUAL

The manual method allows the map creator to pick the values that they use. In this map I started with natural breaks then rounded the numbers up. Doing this allowed me to keep a similar distribution of features with a better looking legend. In the next chapter you will learn even more about cleaning up the legend. The most important thing about assigning a classification is to pick the one that best represents YOUR data and what you want that data to show.

NOW YOU CAN LOOK AT THEM SIDE BY SIDE AND SEE THE DIFFERENCES

Natural Breaks (Jenks) Equal Interval Defined Interval

Geometrical IntervalQuantile Standard Deviation

ATTRIBUTE CLASSIFICATION: DECIMAL PLACES VS SIGNIFICANT DIGITS

In creating a choropleth or graduated symbol map you will have the option of rounding the numbers by decimal place or sig figs. The simplest way of choosing which one to use is to think of who the audience of the map is.

If the audience is science professionals and you are dealing with concentrations then it would be appropriate to use sig figs.

If the audience is the general public you would most likely want to use rounded numbers with a appropriate number of decimals places.

DEFINITION QUERIES

Definition Queries work very much like Select by Attribute. However the difference is that instead of highlighting the desired features the undesired features are removed from the map.

This is more beneficial than the Select by Attribute function because you no longer have to create a new layer for desired features.

DEFINITION QUERIES: THE TOOL

The top box is where you would select which field you want to limit the features by.

Then you would choose which expression key you want to limit with. We’ll get into what these keys mean in the next few slides.

Once you have chosen an expression key you would then type in a value that would be in the field you are limiting by or you would use the “Get Unique Values” button.

It is best to use the Get Unique Value button because when entering an expression you have to use the EXACT spelling that would appear in the field. This includes capitalization.

DEFINITION QUERIES: THE EXPRESSION KEY “=“

This expression will limit the shapefile to values that matches whatever follows it.

EX: “NAME” = ‘Baca’ will limit the features to

those that have the name Baca. (the B would have to be capitalized).

“pH” = ‘6’ will limit the features to those that have a pH value of 6.

DEFINITION QUERIES: THE EXPRESSION KEY “<>“

This expression will limit the shapefile to values that does not match whatever follows it.

EX: “NAME” <> ‘Baca’ will limit the features to

those that do not have the name Baca. (the B would have to be capitalized).

“pH” <> ‘6’ will limit the features to those that do not have a pH value of 6.

DEFINITION QUERIES: THE EXPRESSION KEY “>“

This expression will limit the shapefile to values that are greater than the value that follows.

EX: “NAME” > ‘Baca’ will limit the features to

who's name comes after Baca alphabetically.

“pH” > ‘6’ will limit the features to those that have a pH greater than 6.

DEFINITION QUERIES: THE EXPRESSION KEY “>=“

This expression will limit the shapefile to values that are greater than or equal to the value that follows.

EX: “NAME” > ‘Baca’ will limit the features to

who's name is Baca and what comes after it alphabetically.

“pH” > ‘6’ will limit the features to those that have a pH greater than or equal to 6.

DEFINITION QUERIES: THE EXPRESSION KEY “<“

This expression will limit the shapefile to values that are less than the value that follows.

EX: “NAME” < ‘Baca’ will limit the features to

who's name comes before Baca alphabetically.

“pH” < ‘6’ will limit the features to those that have a pH less than 6.

DEFINITION QUERIES: THE EXPRESSION KEY “<=“

This expression will limit the shapefile to values that are less than or equal to the value that follows.

EX: “NAME” < ‘Baca’ will limit the features to

who's name are Baca and come before it alphabetically.

“pH” < ‘6’ will limit the features to those that have a pH less than or equal to 6.

DEFINITION QUERIES: THE EXPRESSION KEY “LIKE“

This expression will limit the shapefile by using a wild card. There are 2 wild cards that can be used. “%” or “_”.

EX: “NAME” LIKE ‘_aca’ will limit the shapefile

to any value that has 1 letter followed by “aca”.

“NAME” LIKE ‘Miss%” will limit the shapefile to any value that starts with “Miss” and ends with any number of letters.

DEFINITION QUERIES: THE EXPRESSION KEY “NOT“

This expression will allow you to choose which values are excluded. This expression is combined with another such as “LIKE”

EX: “NAME” NOT LIKE ‘Miss%’ will exclude

values that start with “Miss”.

DEFINITION QUERIES: THE EXPRESSION KEY “AND“

This expression will allow you to limit a shapefile by the contents of 2 or more fields.

EX: “STATE” = ‘New York’ AND “COUNTY” =

‘Onondaga’ will select any feature that has a State value of New York and a County value of Onondaga.

DEFINITION QUERIES: THE EXPRESSION KEY “OR“

This expression will allow you to limit a feature by 1 or more fields.

EX: “STATE” = ‘Maine’ OR “STATE” = ‘New York’

will limit the feature to states with the name Maine or New York.

“POP2000” > 10000 OR “POPDENSITY” > .25 will limit the feature to populations will more than 10,000 people or a population density more than .25.

DEFINITION QUERIES: THE EXPRESSION KEY “IS“

This expression is used to include or exclude “NULL” values.

EX: “POP2000” IS NULL will limit the feature to

only those that have NULL for values. “POP2000” IS NOT NULL will limit the

features to those that are not NULL.

DEFINITION QUERIES: THE EXPRESSION KEY “()“

This expression is used when doing complex expressions. It is used to dictate what operation is used first. We will come back to this in a later lesson.

These are the expressions that have buttons available for them, however there are more that can be done. These will be explored in a later lesson as well.

HYPERLINKS

These are links that we can connect to a point, line or polygon. These links can lead to a document or websites. They are every useful when you create a PDF or interactive map.

Interactive maps like Google Earth, Bing Maps, Map Quest, and Yahoo Maps use these.

MAP TIPS

These are pop ups that will give you information about the item you are hovering above.

This can be useful when working on a map because you don’t have to have labels on, which can clutter a map.

You can choose any field to be displayed by Map Tips.

THAT’S IT FOR NOW!

Next time we will cover: Prebuilt Layouts Landscape vs Portrait Guidelines Titles Legends Scale Bars Reports Graphs Neatlines Data Driven Pages Map Animations