Represents space discretely:

• Objects delineated using sets of coordinate pairs.
• Linked to descriptive attributes
• Many attributes per object

A point feature is an individual x, y coordinate pair representing a precise location.

• “Zero-dimensional”
• No length, width, or area

Points are great for representing a variety of objects, depending on the scale:

Almost Any Scale
• Trees
• Stop signs
• Fire hydrants

Points are great for representing a variety of objects, depending on the scale:

Almost Any Scale
• Trees
• Stop signs
• Fire hydrants

Smaller Scales
• Cities
• Wild Fires
• Airports

A line feature is a set of connected points. Must have a start and end point. May have middle points (vertices).

• One-dimensional
• Length
• No width or area

Lines are also great for representing a variety of objects, depending on the scale:

Almost Any Scale
• Hiking trails
• Power lines
• Water pipes

Lines are also great for representing a variety of objects, depending on the scale:

Almost Any Scale
• Hiking trails
• Power lines
• Water pipes

Smaller Scales
• Roads
• Rivers
• Storm tracks

A polygon feature consist of a set of three or more vertices connected by line segments (edges) that form an enclosed shape.

• Two-dimensional
• Length & width
• Area

Preferred for many objects depending on scale:

Almost Any Scale
• Climate units
• Lakes
• Political boundaries

Preferred for many objects depending on scale:

Almost Any Scale
• Climate units
• Lakes
• Political boundaries

Larger Scales
• Buildings
• Roads
• Cities

All polygons are an enclosed shape. Some can also have interior rings (holes).

• Each ring is a separate set of vertices and edges within the polygon
• Interior rings cannot overlap

When an object has multiple parts, the vector model allows for:

• Multi-polygons
• Multi-lines
• Multi-points

Data resolution also applies to the vector model:

• Less straightforward than for raster model
• Spacing between vertices
• Smallest resolvable feature
• Higher resolution = larger filed size

Non-spatial data can be stored in an Attribute Table separate from the spatial data.

• Attributes are linked by an index
• The index is a unique identifier
• No two objects can have the same index
• Often labelled as the "FID" in Arc

Non-spatial data can be stored in an Attribute Table separate from the spatial data.

• Attributes are linked by an index
• The index is a unique identifier
• No two objects can have the same index
• Often labelled as the "FID" in Arc
• Ability to store many attributes
• Less redundancy than raster model
• Easy to add new attributes

Similar to the mixed pixel problem, all space within a polygon (or along a line) is treated as homogenous

• What a unit covers multiple values?
• Any variability is lost and the unit is treated as homogenous

Vector overlay operations are more computationally expensive than raster overlay.

• Involves calculating the relative positions of ever point/vertex in every layer to determine overlap, containment, etc.
• Many different operations depending on needs

The tool in Arc for performing calculations in the attribute table

• Fields can be "variables" in linear equations
• Won't update if field values change
• Not always easy to use or intuitive
• Lacks some basic functionality
• Can't calculate the sum of a column without extra steps

The spatial relationships between geographic features.

• An important aspect of network analysis (route finding)
• Google maps uses topology every time you search for directions
• Different rules for different features (pedestrian, car, transit)
• We can specify rules e.g.:
• Polygons (i.e. buildings) cannot overlap
• Points (i.e. fire hydrants) must be attached to lines (i.e. water mains)