Analyzing Spatial Data

1
Analyzing Spatial Data

• Working with tabular data.
• Graphic selection query.

2
Working With Tabular Data

• Querying data.
• Selecting features by attribute.
• Lists all the fields from the attribute table.
• Shows values within selected fields.
• Creating reports.
• Joining tables.
• Relating tables.

3
Working With Tabular Data

• Associate layer files with non-spatial tabular
  data.
• Note that this is always geographic to tabular.
• Joining tables.
• Spatial join.
• Relating tables.

4
Working With Tabular Data

• Joining tables to associate non-spatial data.
• Process of attaching tabular data to geographic
  features.
• Physically merging two attribute tables using
  their common item.

5
Working With Tabular Data

• Case for joining tables.

6
Working With Tabular Data

• Example
• City_name Pullman

Original feature class
New feature class
Relationship
7
Graphic Selection Query

• Spatial join attributes of features in two
  different layers are joined together based on the
  relative locations of the features (adjacency).
• Provides a more permanent association between the
  two layers because it creates a new layer
  containing both sets of attributes.

8
Graphic Selection Query

• With a spatial join, features are selected based
  on location
• Find the closest features to another feature
  (distance).
• Proximity is based on straight line distance
  between features.

9
Graphic Selection Query

• Spatial join.
• Find whats inside a feature (containment).
• Join the attributes of the features that fall
  inside a polygon.
• Find what intersects a feature (intersection).
• Join the attributes of the features that
  intersect it.

10
Aggregating Features

• Dissolve features of a single layer based on a
  specified attribute value.
• Takes out borders between features.
• Append two or more adjacent layers (not
  overlapping) into a single layer.
• Reduce the spatial extent of one layer based on
  the extent of another (clip).

11
Aggregating Features

• Find those features falling within the spatial
  extent common to two layers (intersect).
• Combine two polygon layers (union).

12
Aggregating Features

• Use Union to overlay two polygon layers
• Has the combined attribute data of the polygons
  in the two inputs.
• Contains all the polygons from the inputs,
  whether or not they overlap.
• Produces a new layer combining the features and
  attributes of two polygon layers.

13
Aggregating Features

• If aggregated features are saved as shapefiles
  the attribute data are not updated. Use X-Tools
  Extension.
• If saved as feature classes in a geodatabase the
  attribute tables are updated in new fields called
  shape_area and shape_length.

14
Working With Tabular Data

• Relating tables defines a relationship between
  two tablesalso based on a common fieldbut
  doesnt append the attributes of one to the
  other. Instead, you can access the related data
  when necessary.

15
Working With Tabular Data

• Case for relating tables.

16
Working With Tabular Data

• Relationships stored in relationship classes.
• One property of a relationship is its
  cardinality, which describes how many features in
  the coverage are related to how many records in
  the other attribute table.
• Simple and composite relationships.

17
Relationship Classes

• Relationships between two or more objects in the
  database that exist independently of each other.

18
Relationship Classes

• Create permanent instructions showing what
  feature classes can be related.
• Called storage of a relationship.
• Between feature classes and tables.
• Appear in the Catalog tree.

19
Summary of Analysis Methods

• Spatial to non-spatial.
• Joining, relating tables.
• Spatial joins distance, containment,
  intersection, adjacency.
• Spatial to spatial.
• Dissolve, merge, clip, intersect, union, buffer.