CollaGen: Collaboration between automatic cartographic Generalisation Processes - Advances in Cartography and GIScience - page 556

Figure 17: Conflict emergence from CartACom generalisation. (a) ungeneralised data. (b)
emerging conflict areas are detected after generalization. (c) zoom on a conflict area ex-
tended to better solve the conflict. (d) conflicts solved by least squares generalization.
In order to evaluate CollaGen contribution, we used it to generalise the
benchmark dataset from EuroSDR generalisation state-of-the-art project
(Stoter et al. 2009) and compared the results to the best ones obtained dur-
ing the tests with CPT and Clarity™ software ( Figure 18 ) . Although the
seven processes used could be tuned to improve individual results, the
comparison shows the pros of CG and CollaGen, particularly in the south-
west suburban part that has to be generalised differently from the town
area.
Figure 18: A mountainous French dataset from EuroSDR tests (Stoter et al. 2009)
generalized with CollaGen compared to the best results from the tests.