ESPON HyperAtlas is a tool for Multiscalar Territorial Analysis: several indicators on the basis of the ratio of two initial geographical indexes can be derived, according to different spatial contexts.
Multiscalar Territorial Analysis is based on the assumption that it is not possible to evaluate the situation of a given territorial unit without taking into account its relative situation and localization. Regions belong to territorial and spatial systems. Indeed, from a policy point of view and in a social science perspective, contrasts and gradients are of much more interest than absolute values. Furthermore, aggregating and disaggregating territorial units allow to see how local values add up to form territorial contexts and regional positions.
Whatever the indexes used for political decisions, they have to be evaluated in relative terms. This may be done according to various territorial contexts. Thus one spatial organization may be examined from three different viewpoints that are three territorial contexts. They are differentiated according to the scale of political intervention or action they are referring to and that have a sense for the questioning: a global one, a medium one and finally a local one. Thus what is represented is the deviations to the three reference values associated to these different levels.
Let us take the example of the European union as a set of 25 countries, at the level of the region (NUTS2 for instance), and let the observed index be the wealth per resident in the regions (GDP/inh.). It is possible with ESPON HyperAtlas to consider the level of wealth of the regions relatively to three territorial contexts, and not only from an absolute point of view. The chosen contexts may be for instance respectively:
the whole European Union;
the country;
the neighborhood defined by contiguous regions.
ESPON HyperAtlas proposes for such an indicator a set of maps and charts that will be furthermore described in MTA parameters and Tools:
First maps show the selected study area, both the parent distributions as disc maps (here, wealth and population) and their ratios, that is to say the chosen index’s one.
Then, three maps show the relative deviations to the three chosen contexts as choropleth maps. For the above example: the deviation of a region to the European reference area, the deviation of a region to its national reference area, and in the third place the deviation of a region to the local reference area.
Then, two synthesis maps allow to evaluate the different combinations of the three previous relative deviation maps.
More advanced users are also provided a set of new tools like the maps of redistribution, the Lorenz curve and a chart of spatial autocorrelation.
Here are some political justifications about the contextual and multilevel mapping, based on the European example:
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