This page presents the procedures to perform a line simplification.
The SPRING presents three algorithm options for line simplification:
IMPORTANT
: All these algorithms use purely subjective criteria, that have impact on the way the tolerances that will be chosen by the user on the SPRING Interface. Therefore, it is adviseble for the users to evaluate the impact of the different tolerances, in each method, on its data. The SPRING suggests certain values considered conservatives for each change attempted. In case of doubt, use the "default" values suggested by the system.Another important aspect is about topology. These simplification methods act on the lines with no special care for the topological relations previously created. For this reason, they must always be succeeded by adjust operations of nodes and polygonization.
Defining the simplification parameters
See also:
It is the most adopted method by geographic information systems. Initially conceived to solve the problem of the excessive number of points resultant of the conversion of graphic data to the digital format, the Douglas-Peucker method is based on the following idea: if no point of the line is further away than a certain vertical distance to the line segment that conects the extremes of the line, so this line segment is good enough to represent the whole line. This method is considered a global technique of generalization, because it analyses each line as a whole. The following image shows the application of the Douglas-Peucker algorithm.
This method uses exactly the same global analysis procedure for each line used on the Douglas-Peucker method. The only difference is on the adoption of the area / perimeter ratio calculated from the tolerance chosen by the user. The use of the area / perimeter ratio allows the triangles formed by three consecutive points that have an acute angle very small on the second point, to be detected in a much more efficient way than on the Douglas-Peucker method.
The accumulated distance method is an adaptation of the vectorial implementation of the Li-Openshaw algorithm which uses as criterion the concept of smallest visible object. This method accumulates the distances as the line is covered until a certain limit, removing all the points accumulated in this sector. It is, therefore, a simple method, but, differently from the two previous methods, does not analyses the line as a whole.
Defining the parameters of line simplification: