Introduction to Geographic Information Systems in Forest Resources

UW Home GIS@UW Search

Syllabus Schedule Class Meetings Assignments Course Data Internet Search Current Grades Contact Us CFR 590 Internet-only section Lab Locations

Discussion

You should now know the fundamentals of GIS, as applied in ArcView 3.x.

• What GIS is
• How GIS works
• What GIS can do
• GIS data types
  • Spatial data
  • Tabular data
• Modifying views of data
• Managing data sources

Thorough knowledge of these topics are necessary before undertaking any analytical tasks. In this section basic vector analysis will be discussed.

One of the most basic analytical tasks in a GIS is locating features in one theme based on the location of other features in the same theme or in another theme. This type of relationship is based on the spatial properties of the themes, including the spatial extent and location of features within themes, as well as the feature type of the themes.

Here are some examples of analytical questions which can be answered with these methods:

• Which forest stands lie within 100 m of a road?
• Which inventory plots have been affected by a recent slope failure?
• Does any stream pass through the oldest stands in a forested area?
• What is the age-class distribution of stands adjacent to stands younger than 10 years?
• What is the mean slope of the group of stands within 50 m of a stream?

In addition to the selection of features within or among themes is the topic of aggregation, or merging, of features based on an attribute value. In this case, boundaries (for polygon themes) or nodes (for line themes) are eliminated between adjacent features with the same value for a given attribute. Aggregation can simplify understanding of complex data sets, in an analog to the summarizing of tabular data.

Analyzing spatial relationships

• Theme-on-theme selection
• Selecting points near a line
• Selecting adjacent features
• Line-on-polygon selection
• Polygon-on-line selection
• Point-in-polygon selection
• Polygon-on-point selection
• Polygon-on-polygon selection

Spatial join and spatial merge

• Spatial join: inside
• Spatial join: nearest
• Spatial merge

Analyzing spatial relationships

Many of the reasons GISs were developed were to answer conceptually simple, but technically difficult spatial questions. These questions include relationships of adjacency, nearness, intersection, and containment of features among different themes. ArcView 3.x 's basic spatial analysis functionality includes methods to deal with these analytical tasks.

• Theme-on-theme selection

Theme-on-theme selection is used to select features in one or more themes based on the spatial, (locational), relationship to another theme. Features in one or more themes that share the same space, or are near to, selected features in another theme, can be selected, displayed, and analyzed. The themes used in theme-on-theme selection are known as the target theme(s) and the selector theme. The selector theme contains features that are known or selected, and the target theme(s) contain features that we are curious about.

Based on the feature type of the target and selector themes, several possible spatial relationships exist:

To select points near a line, a line theme is made active, and several features are selected from that theme. For example it may be of interest to count the number of marbled murrelet nests that are within 10 miles of existing roads, or airports within 25 miles of interstate highways. In the following example, a selection is made on gates that are within a certain distance of streams.

If no selection is active, then all line features are assumed to be selected. This is the selector theme. Here, a selection is made on streams. Next, a point theme is made active. This point theme is the target theme (in this example, the Gates theme is made active).

From the menu, Theme > Select By Theme is chosen, which invokes the Select By Theme dialog. Here, gates that are within 900 ft of selected streams are also selected. If there were an active selection on gates already, we could reduce or add to the selection by choosing the Add to Set or the Select from Set buttons. To select only those gates meeting the selection criterion, select New Set.

Now those gates within 900 ft of the selected streams are also selected.

It would have been just as easy to select both gates and culverts in this selection by also making the Culvert  theme active.

• Selecting adjacent features

To select features that are adjacent to other features, first make a selection on the selector theme. Next, make the target theme active, and select Theme > Select By Theme from the menu. If the selector and target themes are both polygons, this will be identical to an intersect operation in the Select By Theme dialog. If the target and selector themes are one and the same, the new selection will contain both the initial selected set, and the features adjacent to the selected set.

Here, a selection is made on stands adjacent to 100+ year-old stands. First, a selection is made (using the Query Builder) for stands >= 100 years.

Next, the menu choice Theme > Select By Theme is used, and the selection is formatted:

 

When the Add to Set button is clicked, this selects not only the 100+ age stands, but also those adjacent ("within 0 distance units of").

• Line-on-polygon selection

A common question for land and resource management is "What streams/roads/highways pass through a given set of stands/subdivisions/counties?" Line-on-polygon selection is used to select linear features that fall on top of selected polygonal features. To follow the above example through, we shall find the streams and roads that pass through the selected set of stands.

A selected set is already active on the selector theme, Stands. Streams and Roads are made active, and the selection is formatted:

Which selects those streams and roads passing through the selected set of stands (stands are not displayed in the image below, in order to make the streams and roads more visible).

• Polygon-on-line selection

Polygon-on-line selection is the reverse of the previous example. In the previous example, we have a selected set of polygons, and we are interested what linear features pass through these polygons. In this case, we are interested in the polygons that are on top of a selected set of linear features.

For example, a stream monitoring project may have identified stream reaches in which water turbidity from sedimentation is unusually high. We are interested in identifying the forest stands through which these stream reaches pass, in order to see if there is a relationship between land management practices and stream sedimentation.

In this case, select streams of interest from the Streams (27 Creek)

and then make the Stands theme active. The Select By Theme dialog would look like either of these (the functionality is equivalent for polygon-on-line selection):

The new selected set of stands are those through which the selected streams pass:

• Point-in-polygon selection

Point-in-polygon selection is used to identify point features from one theme which are located within selected polygons of another theme. The point theme is the target, while the polygon theme is the selector.

For this example, examine the Pack Forest continuous forest inventory (CFI). One of the problems in the CFI is that some stands have few of no inventory sampling points, while others may have more sampling points than necessary. In order to calculate accurate statistics, the sampling scheme must properly represent the population. Point-in-polygon selections can be made to count the number of survey points within a selected group of stands.

Here, the 30-40 year old stands are selected.

This Select By Theme query selects CFI plots centers within these stands

The selected CFI plot centers are shown in yellow.

Examination of the CFI plot theme attribute table shows that only one of these has been sampled. It seems that our 30-40 year old stands are highly under-represented in the forest inventory.

• Polygon-on-point selection

Polygon-on-point selections are the reverse of the previous case. Here, we are interested in the value of polygons which lie on top of selected point features. Polygon-on-point selection could be used to determine habitat preferences for bird nesting areas. Assuming we have a habitat polygon theme (land use, land cover, seral stage, vegetative species, etc.), we could select polygons that share the same space as nest sites.

Following the previous example, let's find the stands which have not been sampled, or which are non-forested in the last inventory sampling.

First, CFI plots with no basal area for hardwoods or conifers in 1994 are located.

Then stands sharing the same space are located.

Either a lot of stands were not visited in the last inventory, or many of them had no standing or measurable volume.

• Polygon-on-polygon selection

Polygon-on-polygon selection is the selection of the intersection of two selected sets of polygons from separate themes. An example would be the identification of forest stands that have been affected by a recent burn. This "intersection" does not select the spatial area in common between the two themes, but completely selects any polygons where there is any overlap. True intersection will come in the next module, Vector Analysis 2.

In the following example, we want to identify stands which have at least part of their area in unstable soils. First, select the Soils polygons containing moderate to highly unstable soils:

Then make Stands the active (target) theme, and select polygons which intersect with the selected set of soil polygons.

The map can be used for field reconnaissance to help determine what measures may need to be taken to minimize slope failures in these areas.

Spatial join and spatial merge

Spatial joins are a special case of tabular joins, but instead of joining tables based on a common attribute field, theme tables are joined by the use of the shape field. Like other tabular joins, this appends a source table to a destination table, but the results are somewhat different. Spatial joins append the attributes of one theme to the attributes of another theme, based on the property of proximity or containment, rather than by typical primary-foreign key relates.

Two types of spatial relationships are used to compare the locations of the features in the joined themes: nearest and inside. Like the other types of spatial analysis in ArcView 3.x, the type of spatial join is also dependent on the theme feature type. This matrix shows the relationships which are possible between source and destination theme tables, based on the theme feature type:

The destination theme is the theme we are interested in making a selection on. The source theme contains features that we want to use for defining the selection on the destination theme.

In the proximity relationship, the record for the feature in the source table that has the greatest proximity to the record for the feature in the destination table is appended to the record in the destination table.

In the containment relationship, the record for the polygon (source) completely containing the line or point (destination) is appended to the destination table's record.

The part of relationship applies only to line themes in which lines in one theme are subsets of lines in another theme.

A spatial merge creates a new theme in which multiple input features one common attribute value are merged into single features. The new features need not be adjacent. The new features, although possibly composed of many objects (points, lines, or polygons), are stored as one single feature with one single attribute record. When one individual object of the feature is selected, all objects of that feature are selected.

• Spatial join: containment

The relationship of containment is used when we want to know what polygons contain features from other themes.

Whenever the source theme feature type is polygon, the spatial relationship between it and the destination theme is containment. This is because a polygon in the will or will not contain another point, line, or polygon. If any destination theme features are completely contained within source theme polygons, then the source theme attributes are appended to the corresponding destination theme records. Where destination theme features are not completely contained within source theme polygons, the newly appended fields will appear as blanks.

Following the CFI examples, here we are interested in which stands each plots lies in. Another way of stating this is that for each plot, we are interested in finding out which stand that plot is located in.

First, the Stands theme table is made active (source), and Shape is the active field. Next, CFI Plot Centers is made the active table (destination), with Shape as the active field. The Join button is pushed (or Table > Join is selected from the menu). The new CFI Plot Centers table contains Stands attributes for the stand which contains each individual plot center.

Here, a query is made on the new virtual table for all plots with age greater than 100 years. Although the results of this are the same as selecting 100+ year old stands, and then performing a Select By Theme, this method is much more efficient, especially if there were a need to perform many of these types of queries. The power here is that we are able to make direct selections on the points, based on attributes from the underlying polygons.

As with all theme tables, it is possible to change view properties based on an attribute value; here, CFI plots are mapped according to the age of the stand in which they lie. This may seem trivial, this map would be difficult to make without a GIS, because age is not an explicit attribute of the CFI plots. It is the spatial join that allows this type of analysis.

• Spatial join: proximity

If the destination theme represents point or line data, it is possible to find the nearest point, line, or polygon in a source theme. In addition to the source table attributes being appended to the destination table, a field called nearest is also added to the table, representing the distance between the source and destination features.

Here, we find and map the distance of CFI plots to existing roads. Note that after the join, the field Distance appears.

The plots can be mapped according to their distance from existing roads. This type of map could be used to schedule field work, so that plots that are close to roads can be staggered with plots that are far from roads.

• Spatial merge

In this example, a new theme will be created in which single features are created for stands within the same age class. Originally, we start with a polygon theme where each separate shape is its own polygon with its own record. The spatial merge will create a new theme, where polygons in the same class will be merged together into single polygons (though these single polygons may have several different individual shapes).

The Stands theme table is opened, and the Age_class_1999 field is active. The table is summarized . The important summary statistic for spatial merge is the Merge_Shape statistic. Other summary statistics can be added if necessary.

Which results in a new theme where stands have been aggregated that have the same age class. Those stands which originally were unclassified have been dropped from the new theme.

Polygons which share the same age class but which are not adjacent are part of the same "polygon" feature. A spatial selection of one of these shapes selects all shapes with the same value.

The theme attribute table shows these as a single feature with a count of the number of original polygons in the class, as well as the sum of area (which was added to the summary definition).

Syllabus Schedule Class Meetings Assignments Course Data Internet Search Current Grades Contact Us CFR 590 Internet-only section Lab Locations

The University of Washington Spatial Technology, GIS, and Remote Sensing Page is provided by the College of Forest Resources and the College of Ocean and Fisheries Sciences through Unit-Specific UIF. Site administrator: Phil Hurvitz.

Copyright © Phil Hurvitz, 1998-2003