Help to use the Mobiliscope

1) Preliminary notes

Initial data come from Origin-Destination surveys (from 2009 to 2019). Once transformed, these data have been used to estimate the ambient population in every district at exact hours (04.00, 05.00 etc.) during a typical weekday (Monday-Friday).

Number and proportion of ambient population aggregated by district and hour are estimation : they are subject to statistical margins of error.

58 city regions (spread over 5 countries) are included in the actual version of the Mobiliscope (v4.2).
To choose the city region you want to observe, please selection the city region in the drop-down menu or use the magnify tool from a search by name.

2) Select a map

In the left-hand menu, you can choose indicator (classified into broad families such as demographic or social profile) and its map representation - eitheir as aof the total population, or number or flows.
To get informations about indicators, click button on the right side.


With flows maps you get number of non-resident people at district level. With links (displayed on mouseover), you can see their district of residence (not available on touch screens).


3) Change hours

At the top of the screen, click play button in the timeline to animate map and graphics according to the 24 hours of the day.


4) Explore a specific district

Select one district by clicking on the map.


Have a look at the chart entitled "In the selected district" where you can follow hourly variations of ambient population (for each group of the selected indicator) in the district under consideration. Colours have the same colour code than in the indicator menu. Here, last transportation mode used by present population in the selected district was coloured in blue for public transportation, in pink for private motor vehicle and in green for soft mobility.


By clicking on 'Unique' mode, you can limit representation of the hourly variations for only one subgroup :


5) Explore spatial segregation

The block of graphs entitled "In the whole region" displays two segregation indices computed from every district of the region for each hour of the day.

Duncan Index (also called Dissimilarity Index) measures the evenness with which a specific population subgroup is distributed across districts in a whole region. This index score can be interpreted as the percentage of people belonging to the subgroup under consideration that would have to move to achieve an even distribution in the whole region.


The example above displays, hour by hour, the Duncan Index (Paris region - 2010) for to ambient population residing in or outside 'Poverty Areas'. Duncan index range from 0 to 1. A Duncan Segregation Index value of 0 occurs when the share of ambient population residing in 'Poverty Areas' in every district is the same as the share of people residing in 'Poverty Areas' in the whole region. Conversely, a Duncan Segregation Index value of 1 occurs when each district gathers only one of the two population subgroups. In our example, Duncan value is found to be higher between 8pm and 7am, indicating a stronger segregation at night (further away from an even distribution): this corresponds to the hours when most of the individuals are at home or in their district of residence. The value of the index decreases during the day: because of their mobility, people residing in and outside of 'Poverty Areas' are more mixed (situation closer to even distribution).

By clicking on the "Moran" button, a second graph is displayed with the Moran index which measures the similarity in the profiles of the ambient population for neighbouring districts.


The Moran index values vary from -1 to +1: the closer its value is to 1, the more similar the spatially close districts are (with same distribution of the subgroup under consideration); the closer its value is to -1, the more dissimilar the spatially close districts are (with different distribution of the subgroup under consideration). When the Moran index value is 0, no similarity/dissimilarity pattern between neighbouring districts appears in the whole region. In our example, the Moran index values are positive and increase during the day: it means that spatial blocks of similar districts (according to the proportion of inhabitants of 'Poverty Areas') are formed during the day. This result does not contradict Duncan's index but complements it: people residing in 'Poverty Areas' visit during the day other districts than their residential district but tend to visit districts close to each other. And the same is true for people residing outside 'Poverty Areas'

It should be noted that in the case of an indicator subdivided into two groups (eg. male/female or people residing in/outside 'Poverty Areas'), Duncan and Moran values are the same for the two groups and therefore the curves are overlapping.

For more information on the two indices used (Duncan et Moran), click help button next to the index name.

6) Change map backgrounds

By clicking on the button in the central map, several layers can be displayed to make it easier to find your way around the interactive map: a simple base map (default layer), a more detailed one and aerial photos.

osm-simple osm-setail satellite

According to the city region under consideration, some other layers can also be displayed such as 'Poverty Areas' in French cities or urban/peripheral rings in Latin American cities.

osm-simple couronne

7) Download data

Data displayed in the Mobiliscope are under open license (ODbL). Mobiliscope data are reusable as they remain under open license and that the sources are mentioned.

By clicking on the button above the central map, you can download data aggregated data by district and by hour. By clicking on the button in the bottom graph, you can also download data about hourly segregation values (Duncan's or Moran's index) computed for the whole region over the 24 hours period.

To go further

To get more information about indicators and data which are currently used and displayed in the Mobiliscope, you can read Data, Indicators or Geovizualisation pages.


In summary

Mobiliscope is a geovisualization platform that allows you to explore the ambient population within cities over a 24 hour period. With the Mobiliscope, we discover how cities, neighbourhood social composition and segregation change around the clock.

58 city regions are included in the actual version of the Mobiliscope: 49 French cities, 6 Canadian cities and 3 Latin American cities.

Behind the Mobiliscope, there is a team of geographers and geomaticians working in Géographie-cités laboratory (Paris, France) and as well as some supporting partners.

To underline how cities and social segregation gain to be observed from a 'daycourse' perspective, we have also introduced and described the Mobiliscope in various papers and communications.

How it works ?

The data comes from recent 'origin-destination surveys' with 968,000 respondents and 2.9 millions of trips.

Present population can be explored over the 24h period of a typical "weekday" (Monday-Friday) according to some personal, household and place indicators.

One central map and two graphs are the key elements of the geovizualisation around the clock.

A multitask tool

Daily mobility data is increasing but remain difficult to handle to explore cities and their daily rhythms. Mobiliscope has been developed to help large audiences to discover how cities change around the clock. It is intended to be used as...

And whatever your profile, you can also play with the Mobiliscope just for fun !

Open science

Working in line with the FAIR principles, we do our best to ensure that our source code as well as the data which are displayed in the Mobiliscope are easy to Find, Accessible, Interoperable and Reusable.

Data displayed in the tool as well as the source code developed to process the initial transportation data and to create the geovisualization interfaceto are in open access. They are freely downloadable and reusable.

The Mobiliscope is constantly evolving. New cities and functionalities are regularly added.

If you use the Mobiliscope or would like to contribute to its development, please let us know (mobiliscope[at]

How to cite Mobiliscope?

To cite actual version:

    Vallée J, Douet A, Le Roux G, Commenges H, Lecomte C, Villard E (2023). Mobiliscope, a geovisualization platform to explore cities around the clock (v4.2). Zenodo. doi: 10.5281/zenodo.7822701

If you re-use open-data downloaded from the Mobiliscope or issued from Zenodo record:

    Vallée J, Douet A, Le Roux G, Commenges H, Lecomte C, Villard E (2023). Mobiliscope, a geovisualization platform to explore cities around the clock (v4.2). [Data set]. Zenodo. doi: 10.5281/zenodo.7822016