9. Analyzing Spatial Relationships

9.2 Spatial Join

Containment Spatial Join (point-in-polygon)

Proximity Spatial Join (point-to-point)

9.2 Spatial Join

Let’s look at the relationship between city and 20 min fly circles illustrated above. ArcView Theme-on-theme selection allows for selecting cities within the fly circle. But can we identify which fly circles serve which cities? Actually we can do this at least one by one. But it is too time-consuming. What if we want to have a statistics of all fly circles, such as how many cities are served and how many people are served by the fly circles in the entire country. If we look at the relation between them, we can say cities are within fly circles. In that case, point is in polygon. Sometimes this relation is called point-in-polygon overlay. Graphically the relation is as follows:

In terms of theme tables, the relation can be shown as follows:

If you join two theme attribute tables together using their Shape field as the common field, ArcView automatically bases the join on the spatial relationship between the features in the two themes. This is called a spatial join.

A spatial join is similar to an attribute join; however it is based on the spatial relationship between the features in the two themes. For each feature represented in the destination table, ArcView looks to see if it has one of the following spatial relationships with any feature represented in the source table, and if it does, that feature's record from the source table is joined into the destination (target) table:

	source theme
target theme		point	line	polygon
point		nearest	nearest	inside
line		nearest	part of	inside
polygon		n/a	n/a	inside

We typically deal with point-in-polygon relation, which is called containment spatial join, and point-to-point relation, which is called proximity spatial join.

Containment Spatial Join (point-in-polygon)

Open a source theme table; Polygon theme is the source theme. (e.g., fly circle)

Open a target theme table; Point theme is the target theme. (e.g., city theme)

Click the [Shape] field for a source theme table, and then click the [Shape] field for a target theme table.

Select the Join button .

The source theme attributes will be appended to the target theme table.

Summarize on the fly circle; Click the field [Rad_20m_id] and select the Summarize button ; In the Summary Table definition dialog box, select pop_98 for the Field, and sum for the Summarize by, and then press Add button; Press OK button.

The summary table shows how many cities and how many people each fly circle serves as shown in the field [Count] and [Sum_Pop_98].

Join this summary table to the theme table of a 20 minutes fly circle. Make a thematic map showing the population served by each fly circle. This map clearly shows the degree to which each fly circle is likely to be congested.

If you want to save this theme permanently, you can do so by choosing Convert to Shapefiles… in the Theme menu when the theme is made active. When you selected some features among this active theme, only the selected features will be converted to the shapefiles.

Proximity Spatial Join (point-to-point)

Finding the nearest facilities from a certain facilities would be asked quite often. For example, where is the nearest post office from your office? Where is the nearest DMV office?, and so on. Proximity spatial join allows you to get a complete list of nearest relation between source and target theme. In our example, we want to assign each helipad to the nearest hospital. The hospital is the target theme, and the helipad becomes the source theme. The join is performed based on the nearest relationship.

Result: Target theme to which source theme attributes are appended along with Distance field.

Open target theme table (hospital); select the field [shape]

Open source theme table (helipad); select the field [shape]

Select the Join button .

The source theme attributes will be appended to the target theme. ArcView adds a Distance field to the target table. This field is automatically calculated by ArcView and contains the distance to the nearest feature represented in the source table for each feature represented in the destination table. The distance is calculated in the view’s map units. Query hospital based on the attributes appended from a source theme tables (e.g., helipad id), and label the distance to a specific helipad.