2. Vector Data

Duration: 9 minutes and 14 seconds

Country: United Kingdom

Language: English

License: CC - Attribution Non-commercial No Derivatives

Genre: Instructional

Producer: Chief Directorate: Spatial Planning & Information, Department of Land Affairs, Eastern Cape, South Africa

Views: 247 (48 embedded)

Posted by: giacomo on Mar 30, 2010

Understanding of vector data models as used in GIS. Vector data provide a way to represent real world features within the GIS environment. A feature is anything you can see on the landscape such as houses, roads, trees, rivers, and so on. Each one of these things would be a feature when we represent them in a GIS Application. Vector features have attributes, which consist of text or numerical information that describes the feature. In this worksheet we explore the different geometry types used to represent vectors.

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Hi, my name is Marcelle.
Welcome to the next topic in our Gentle introduction to GIS tutorial series.
This topic will cover vector data.
Vector data provide a way to represent real world features in a GIS application.
Imagine you are looking out over a landscape from the top of a hill.
Looking out, you see houses, ...
... trees ...
... rivers ...
... and roads ...
... and so on.
Each of these things is a feature you can represent in a GIS application.
Features have attributes which describe them.
For example a road might have a 'width' attribute that describes how wide the road is.
Features also have geometry. Geometry defines the position and shape of a feature.
GIS applications use three basic geometry types: ...
... points, polylines and polygons.
A point is a feature that has attributes and a single vertex for its geometry.
What kinds of features are represented in a GIS Application as points?
Trees, lamp posts, sample sites for pollution monitoring, ...
... named places and accident sites are all features that can be represented using points.
The geometry of a point is usually specified as a longitude (or x) ...
... and latitude (or y) coordinate.
The attributes of a point describe the point. For example, ...
... for tree features, the attributes might describe what kind of tree each point represents.
A polyline is a sequence of vertices that are connected.
Examples of polyline features are rivers, roads, railways, contour lines and so on.
Each polyline feature also has attributes.
For example a 'path' feature may have an attribute 'name' which tells us the path's name ...
... and a description which tells us more about it.
Like a polyline, a polygon is a sequence of vertices that are connected.
However a polygon will always form an enclosed area.
Examples of polygon features are: ...
... a school boundary, a dam, an area of land where pollution has occurred and so on.
Because it always forms an enclosed area, a polygon has a minimum of four vertices.
The last vertex is always at the position of the first, so enclosing the polygon.
By now you might be wondering where vector data comes from?
Vector data is captured using a process called digitising.
For example, we can trace roads visible on a satellite image like this ...
We will look at digitising more closely in an upcoming topic.
Vector data can also be obtained from devices such as GPS receivers.
Vector data can have problems associated with it.
One thing to be aware of is the scale of the vector data.
Vector data always has a scale associated with it.
Small scale maps (that cover a large area) are normally not as useful at large scales.
This is because for small scale maps, fewer and less accurate ...
... vertices are used to define polylines and polygons.
Let's show you an example.
Here we have a vector layer (in red) that was captured at a scale of one to one million.
You can see the boundaries look good at a small scale, but ...
... when we zoom in it becomes less useful ...
... the lines do not follow the coast in our satellite image very well.
If we use a vector layer capture at a large scale - like this one in yellow captured at 1 to 50 000, ...
... you will see the coastline is much more closely matched by the vector layer.
Sometimes vector data can have errors caused by problems in the process used to digitise it.
For example, polygons can have small gaps or slivers between them ...
... which only become apparent at large scales.
Undershoots occur when two line features don't quite connect.
This can be a problem if you are trying to create a road map and the roads don't connect!
Overshoots occur when instead of connecting; a line feature runs past another ...
... creating a small segment that doesn't exist in reality.
Once vector data has been created it can be loaded and viewed in a GIS application.
One of the advantages of a GIS application is that we can create personalised maps.
When vector layers are first added to the map view, the GIS will use a random colour and style.
For example when we add this 'trees' layer, ...
... a basic symbol and colour are automatically used.
We can change the default symbol used to one more suitable ...
... like using tree icons for this tree layer.
Let's summarise what we learned in this topic!
We have looked at the different kinds of vector data ...
... points, polylines and polygons.
We learned that points are features with a single vertex.
And that polylines are features with a geometry made up of a sequence of vertices.
Polygons are features with a sequence of vertices that form enclosed areas.
Vector features have attributes and geometry.
In the next topic we will look more closely at attribute data.
Thank you for watching!

2. Vector Data

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