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specific lighting map); there may be one for a specific group of people like
colour blind users. It may be justified by special map-making procedures
(for example, low cost map-making, specific media or energy saving
e-maps).
On the other hand, on-demand map-making has become increasingly easier
because tools are cheaper and cheaper; they are increasingly simple to
use. Finally, data is more and more easily accessible, for example, trekking
information (trails, difficulty level, length...) that may be added to base
maps as thematic information. Indeed, everybody can make maps.
However, the result is often poor quality maps. There are two main rea-
sons. Firstly, the graphic semiology rules are badly interpreted. Secondly,
inexperienced people misuse map-making rules which may clash on their
actual maps, for example, information volume versus map readability.
In this context, an important issue is to define both the relevant data on a
map and its symbolisation, in order to adapt maps to specific needs. We
propose a map-making approach based on a users' survey. In this article,
maps suitable for trekking - more precisely walking, road cycling and
cross-country biking - are defined. The approach and methods that have
been developed are introduced in section 2. The results, such as the differ-
ent suggestions of trekking maps, are shown in section 3. The conclusions
and future perspectives are proposed in section 4.
2- Approach and methods: analysis based on survey
The approach adopted is based on textual statistics, statistical linguistics
and statistical analysis of textual data. Statistical linguistics (Yule 1944,
Guiraud 1954, Muller 1968, Herdan 1964) makes it possible to compare
the text to be studied and the reference text on the basis of the frequency of
terms used. Information on semantic content of the text to be studied is
deduced from the differences in word frequency between the two texts.
Statistical analysis of textual data was established by (Benzécri et al.
1973). Benzécri wants to describe a reasoning based on observation with-
out a priori assumption; thus he defines an inductive reasoning from con-
sequences to principles and develops a suitable tool: correspondence factor
analysis (Benzécri 1992).
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