Line Generalisation Algorithms

digital generalisation

Digital generalisation can been defined as "the process of deriving, from a data source, a symbolically or digitally-encoded cartographic data set through the application of spatial and attribute transformations". The generalisation of digital spatial data is done for various reasons including:

to minimise the amount of data to be processed;

to filter out errors and consolidate trends;

to produce maps at a variety of scales (from the one source); and

to remove & graphically modify features for effective cartographic communication & aesthetics.

The many forms of generalisation that can be applied to vector-format data are grouped into the following five categories:

point
line
polygon (area)
volume
holistic feature

There are a variety of different algorithms available in GIS to handle all of these processes, however for the purposes of this module we are only interested in the basic techniques available for line generalisation.

In general, up to 80% of the information on a digital map consists of lines, giving rise to the extensive list of generalisation operators that exist - including simplify, smooth, displace, merge, enhance and omit. For simplicity and clarity, this module focuses on two line generalisation operators: Line Simplification and Line Smoothing. For performing each of these operations there are numerous generalisation algorithms in use, however this module will only cover two in detail (one for each of the operators).

Each of the links below will take you to a page comprising the background theory for that particular line generalisation operator and also links to the relevant interactive lessons (which can also be accessed from the main menu).

It doesn't matter whether you begin with Line Simplification or Line Smoothing, as all theory pages are fully inter-linked. The 'download' link at the bottom of this page will allow you to save all of the theory you are presented with in this module.

Line Simplification

Line Smoothing

Click here to download all theory presented in this module

references

digital generalisation Digital generalisation can been defined as "the process of deriving, from a data source, a symbolically or digitally-encoded cartographic data set through the application of spatial and attribute transformations". The generalisation of digital spatial data is done for various reasons including:
to minimise the amount of data to be processed;
to filter out errors and consolidate trends;
to produce maps at a variety of scales (from the one source); and
to remove & graphically modify features for effective cartographic communication & aesthetics.
The many forms of generalisation that can be applied to vector-format data are grouped into the following five categories:
point line polygon (area) volume holistic feature
There are a variety of different algorithms available in GIS to handle all of these processes, however for the purposes of this module we are only interested in the basic techniques available for line generalisation. In general, up to 80% of the information on a digital map consists of lines, giving rise to the extensive list of generalisation operators that exist - including simplify, smooth, displace, merge, enhance and omit. For simplicity and clarity, this module focuses on two line generalisation operators: Line Simplification and Line Smoothing. For performing each of these operations there are numerous generalisation algorithms in use, however this module will only cover two in detail (one for each of the operators).

Each of the links below will take you to a page comprising the background theory for that particular line generalisation operator and also links to the relevant interactive lessons (which can also be accessed from the main menu). It doesn't matter whether you begin with Line Simplification or Line Smoothing, as all theory pages are fully inter-linked. The 'download' link at the bottom of this page will allow you to save all of the theory you are presented with in this module.
Line Simplification	Line Smoothing

Click here to download all theory presented in this module
references