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page overview:
  1. impression - illustration of a new city-perception
  2. Introduction - Brief introduction into
  3. maps - Explanation of some map-functions
  4. Text - detailled explanation of the project
  5. map features - practical examples with descriptions
  6. sample maps - Examples
Explanation of some map-functions
boolean urban denCity map types (schematic) users can create their very own, customised urban city maps. choose your categories of interest and shows you where it’s hot and where not.

(click to show highres)
city and regional urbanity

Image 1 divides the city into quadrants of 250 m with a radius of influence of 125 m (the calculated value (~urban index) of the quadrant is influenced by tags within a radius of 125m (diameter = 250m)). If you select five categories (for example entertainment, gastronomy, shopping, transport and service), at least one tag of each category has to exist within this radius to render a value for the quadrant - otherwise its value is zero. The values are then summed up to a relative factor (max. 1 = white for example).

Image 2 also examines the city with a grid of 250 m; though, because of a bigger radius of influence (250 m), tags in adjecent quadrants are considered in the calculation as well. Notice, that some quadrants with a value of zero in figure 1 do have a value now. In a real world example this would mean that a citizen would leave his or her area (the radius of this area is set by the size of the quarant) to use services or infrastructure from another area. The more mobile citizens are, the bigger the radius.

In image 3, the radius is extended once again (500 m). With increasing radius, the quadrant (still 250m) decreasingly needs to offer the necessary infrastructure, but uses the offers of more distant quadrants. By selecting a radius of influence, a user can actually define his mobility (as mentioned above), the area in which he would realistically use existing infrastructure. He then receives an urban map which exactly meets his demands.
The animation at the top of the page shows an actual denCity map with such an increasing radius of influence (two categories were selected).
city resolution

Image 4 shows the city in a resolution of 500 m (gridsize, size of quadrants). The area of influence is equivalent to the the grid size (like mentioned above, all infrastructure must be available in the examined area itself).

In Image 5, we decrease the grid size to 250 m.

Image 6 shows the city in a once again higher resolution: every 125 m, the factor of urbanity is calculated. offers an analysis of urban densities on different levels of resolution. You can interprete every single meter of the city in detail, as well as you can look at bigger, interconnected areas as a whole. With increasing grid sizes, one approaches the model of the regional city (Regionalstadt / Zwischenstadt, Sieverts). The less detailed the analysis, the less individual city centers count and the more city quarters or even whole cities merge in the analysis.
If that all still sounds strange to you, just try it or have a look at the user preset gallery (here you can see the settings, that other users have saved).
0. back to project
© 2005, 2006 Kai Kasugai and Philipp Hoppe