Introduction to Geographic Information Systems in Forest Resources

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Discussion

Cartographic choices lie at the heart of creating maps for communication. How you decide to represent your data will determine what the map communicates. You can draw the reader's attention away from one detail and toward another. You can distort data so that the reader gets a skewed picture of the underlying "reality" of the map data.

Consider these 2 maps; both show the population of each state in the contiguous USA, where the darker color represents higher population. The first map shows the total population, while the second map shows population density (population per unit area). In the first map, California shows the largest population, and some of the Northeastern states show low population. However, in the second map California shows somewhat low population density, while the Northeast shows the highest population density. Both maps represent the same general thematic data (population), but each uses a different cartographic method, and each map communicates a different idea. You would use one or the other of these maps depending on the ideas you want to communicate.

Frequently, different map symbols are chosen because of their psychological impact (for example, green and blue solid filled symbols are often used to show "cool," or non-threatening areas, while red is used to show "hot," or dangerous areas). Line weights also impart relative importance to different linear features (interstate highways are usually drawn thicker than county roads). Different point symbols can be used to signify characteristics of places (National Park maps often show amenities such as boat launches, trailheads, picnic areas, and restrooms with specialized marker symbols). Think carefully about what you want to communicate, and choose your map symbols accordingly.

Classification is another method of changing what you want to communicate with your maps. Research has shown that it is more difficult to comprehend or compare a large number of objects, values, symbols, or colors. Classification allows you to lump similar features into classes; fewer classes are easier to compare to one another. In the maps above, if any more classes were used, the classes would become visually indistinguishable from one another. It is also easier to differentiate among large numbers of classes of ramped colors representing numerical values (e.g., population) than it is to differentiate among large numbers of classes of categorical values (e.g. dominant ethnic background).

Any good GIS software will give you the ability to quickly and easily change the way maps are displayed, by changing symbols, colors, or classification schemes

Thematic mapping

The ArcGIS Layer Properties for Symbology allow you to change the symbology of layer features within the map. There is a great deal of flexibility about how to display features. Many built-in symbol palettes are available for area, line, or point features, and it is also possible to create custom symbols.

To change the symbology for a layer, left-click the layer name and select Properties. Within the Layer Properties dialog, the Symbology tab contains the controls for altering symbology.

Most of the cartographic changes described in this section are accessed via the Layer Properties for Symbology.

Choosing a legend type

Several legend types are available:

• Single symbol (all features of a layer will be drawn with the same symbol)
  Use a single symbol when you only need to display features' locations.
  
  
  
  
• Unique value (features with common attribute values will be drawn with the same symbol)
  Use this to display categorical data, such as soil type, county, or ecoregions. Be careful with unique values display, as a large number of unique class values can easily make classes indistinguishable.
  
  
  
  
• Graduated color, also known as choropleth (colors will gradually change with changes in a numeric attribute value)
  Use graduated color to show data that progress over a range of numeric values, such as stand age, temperature, or precipitation. This map shows the establishment year of forest stands. While this map and the previous both display origin year, in the former, origin year is treated as a categorical value, and in the latter as a ratio value.
  
  
  
  
• Graduated symbol (size of point markers will increase proportional to a numeric attribute value)
  Graduated symbol displays are useful in displaying the relative magnitude of numerical attributes for point data. In this example, forest stand centroids are being displayed with dots that are proportional in size to site index (a proxy measure of forest productivity).
  
  
  
  
• Dot density (a numeric attribute value is used to assign a number of dots representing relative frequency for polygon attributes)
  Use dot density to display how an attribute (such as number of elk or trees per acre) is distributed over a large area. Note: the dots are placed randomly and do not represent the true location of features!
  
  
  
  
• Chart symbol (a bar or pie chart is used to represent the value of several different attribute fields at once)
  Chart symbols are good for comparing a number of attributes at the same time. Here, we can see a chart that displays the size class, stocking level, and site class for each stand. Chart symbols can be displayed as bar or pie charts.
  
  
  
  

Classifying map displays

Classifications are used to group features in similar classes. Classification methods can only be used for numeric attributes. Different classification methods are used to show patterns or groupings of data values. For data sources that have a lot of unique numerical attributes, classification allows the reader to make sense out of the data.

Classification methods (type of classification, number of classes) are only used when displaying data using either graduated colors or graduated symbols.

The 5 classification methods ArcGIS uses are:

• Jenks natural breaks (the default multi-class numerical classification method)
  ArcGIS attempts to find clusters or concentrations of data and place class breaks between the clusters. By default, the number of classes is 5, although you can change the number of classes if you wish. Here are stands displayed in 5 natural breaks classes, according to age.
  
  
  
  When you choose a classification method, a histogram is displayed showing the number of features in each bin. Here is the Jenks classification for the image above. Note that the class breaks are displayed in dark blue vertical lines.
  
  
  
  The chart shows the number of acres in each unique age class. This method uses then Jenks optimization statistical technique. Here is a histogram displaying the total area by age, without any class breaks. Jenks method decides where to put class breaks by minimizing variation between classes
  
  
  
  
• Quantile
  Quantile classification creates classes of roughly the same number of individuals. Note the different class break values between this map and the natural breaks map. Each class here will have approximately the same number of forest stands.
  
  
  
  In the quantile histogram, the total of the values of each bar within each bin should be roughly equal.
  
  
  
  
• Equal Interval
  Equal interval classification divides the range of values into intervals of roughly the same size, and then displays features according to the class they fall in. Here, are equal interval classes of about 40 years. Because the range of ages is large, but most stands are young, the oldest stands fall in a class by themselves.
  
  
  
  Here you can see that the intervals for each bin are equally.
  
  
  
  
• Standard Deviation
  Standard deviation classification will show the variation in data around the mean value. This shows the relative spread of attribute values. Here, the oldest stands are far outside the mean stand age, and show up dark blue.
  
  
  
  The map shows standard deviations, but the histogram shows the relationship between standard deviations and actual age values. The class containing > 1.5 standard deviations corresponds to the age range of approximately 90-203.
  
  

Normalizing data

Normalization of data values expresses attributes as relative values rather than absolute.

Normalization can express an attribute as a percentage of the total. For example, a map could be made to show each stand's contribution of fiber in comparison to the total amount of fiber on the forest.

Alternatively, normalization can express the ratio of one attribute to another. For example, a map could be made to display the per-area contribution of fiber to the forest total. The best example of this is the raw population vs. population density maps from the top of the page, in which the population field is divided by the area field.

Do not normalize attributes that are already expressed in percentages or densities (these data are already normalized), otherwise you will make your data unintelligible.

Manipulating classes

It is possible to alter the classification by adding and deleting classes, by altering the position of class breaks, or by editing class labels. Here are examples of both manipulations. Both of these maps display the same data, but with different numbers of classes, different colors, and different class labels. When would use one instead of the other?

Adding and deleting classes

Classes can be added to and deleted from the legend classification scheme. To add classes, simply specify a different number of classes in the classification scheme. To delete a class, right-click the class in the Layer Properties > Symbology dialog and select Remove Class(es).

Sorting values & labels

Legends can be sorted in ascending or descending order. The Range field are sorted numerically, and the Label field is sorted alphabetically. Note that the symbols are the same but the values are reversed.

Flipping symbols

The order of symbols can be reversed as well as the data ranges and labels. The order of the symbols will change, but the order of the values will remain the same. For example, if your colors ramp from green to yellow to red, flipping the symbols will reverse the order of the colors.

In this example, the 3-class legend is flipped. Note that the values are the same and in the same order, but the colors have changed.

Ramping colors

Color ramping is automatic when you choose the graduated color legend type. However, it is possible to change the first and last color, and have them gradually change between. You can also merge several individual monochromatic color ramps and ramp the colors that fall between (e.g., blue > green | green > yellow | yellow > red | red > white).

In this image, the color ramp goes from green through yellow to red.

Working with null values

Sometimes attribute data contain null values. A null value is different from an actual value of 0 (for example, a value of 0 is valid for temperature, but not valid for a speed limit). Null values are often coded numerically as 0 or -9, or as blanks in character fields. It is possible to perform a query to exclude null values; any features with this value will not be displayed.

Scaling symbols

Marker symbols can be scaled so that as you zoom in and out, the size of the marker changes with the scale. Without scaling, as you zoom in, the absolute size of the markers will stay the same; with scaling on, the markers will increase in size.

Here is a view with simple point symbols:

This is a larger scale view with scaling off:

And with scaling on:

Rotating symbols

If a field exists within a point layer's attribute table describing the angle of the feature, this can be used to rotate each marker by that value. Marker symbol rotation can be used to show the direction of travel of a point phenomenon (e.g., an animal's direction of migration based on a telemetry point or wind direction from a weather station).

Offsetting lines

Lines can be offset any distance you like. This is handy when you are displaying several lines that lie on top of each other (for example, the Pack Forest boundary is delineated in places by roads and streams). Offsetting allows your map to display all lines. The offset direction is controlled by the arc's direction.

Here are similar views, one with line offset at a value of 0 (no offset), and the other at a value of 2 points.

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