EVALUATION OF COLOUR CONTRASTS BY MEANS OF EXPERT KNOWLEDGE
FOR ON-DEMAND MAPPING
E. Buard, A. Ruas
IGN
elodie.buard@ign.fr
In the context of maps on demand, we
wish to create maps according to users needs. Keeping in mind that a map is a
creation coming from choices, in particular for data representation and
symbolisation, legends have to be cartographically correct to ensure a good
visualisation and, as a consequence, a better understanding and efficiency. It
means that users’ legends have to be analysed and improved in term of
cartographic correctness and semiology. Elisabeth Chesneau at COGIT Laboratory
[Chesneau, 2006] has developed automatic methods to analyse and improve the
colour contrasts of the symbolised objects in the legend. It does not analyse
the contrasts directly in the legend [Brewer, 1997] but locally at the object
scale. Her model is based on colour contrasts estimations. In order to obtain
coherent results, these estimations have to be reliable. However when it is
come to colours, we need cartographic experts to evaluate the contrasts and to
give them a relevant score. Colours in cartography contain much knowledge and
subjective opinion.
This paper presents our proposal to
undertake a tests protocol for colour contrasts evaluation to give to
cartographic experts. The work is implemented on Maacol [Dadou, 2005], a module
developed at the COGIT Laboratory, helping knowledge acquisition, whatever the
knowledge is, and then analysing it using supervised machine learning. For our
evaluation, we apply Maacol to cartographic knowledge. First tests have been
experimented in choosing specific colours [Jolivet, 2006] representing the most
used colours in risks maps. 20 cartographic experts have evaluated 50 test
samples in comparing two neighbouring colours. However the scores given to the
contrasts were very spread due to a lack of test specifications. That is why we
design an accurate test protocol for colour contrasts. It describes the type
and the range of wanted answers, the relative position of both colours to
analyse, the good visualisation environment for the tests, the tests
explanations and the consultation of visual examples of a minimum and a maximum
score of contrasts.
A second ongoing test is performed
first to validate the test protocol and then to extend the test to a larger
range of colours.
Chesneau, 2006: Model for the automatic improvement of colour contrasts in cartography- Application to risks maps, PhD thesis, 372 p.
Brewer, 1997: Evaluation of a model for predicting simultaneous contrast on color maps, professional geographer, 49 (3), pp 280-294
Dadou, 2005: Helping the capture and analysis of expert knowledge to support generalisation, 8th ICA workshop on generalisation and multiple representation, A Coruna, 9p.
Jolivet, 2006: Analyse des contrastes de couleurs – Mise en
place d’un test sous le logiciel Lamps2, Master carthagéo, ENSG, rapport
de stage réalisé au COGIT, 35 p.