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

In French cities, you can display official statistics zonings (Zonage en Aires Urbaines - ZAU de 2010 ; zonage en Aires d'Attraction des Villes AAV de 2020)

zau aav

or some institutional zonings such as 'Poverty Areas' (QPV) or those related to 'Action Coeur de Ville' (ACV) or 'Petites Villes de Demain' (PVD) programs.

qpv acv pvv
A tool can be used to list the French Mobiliscope areas according to their location in these three institutional zonings (ACV, PVD, QPV).

In Latin American cities, map backgrounds about municipalities and centre/periphery rings are available, as well as TransMilenio in Bogotá.


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.

8) Partager une vue particulière

By clicking on the button , you can copy the URL of your map or share it directly by email or on social networks. The URL records your choice of indicator as well as the district and hour selected.

To go further

You can also visit the information pages of the website to learn more about our methodology and Geoviz process, as well as the codes and data available in open access.

Reproductible papers

The Mobiliscope has given rise to a number of scientific articles (see list). Making Mobiliscope data available as open data also gives the opportunity to publish fully reproducible papers.

Intersectional approach of everyday geography


In a paper published in the journal Environment and Planning B: Urban Analytics and City Science (preprint sur arXiv et HAL), Julie Vallée and Maxime Lenormand use Mobiliscope data to explore hour-by-hour variations in spatial distribution of gender, age and social class within cities.

Hour-by-hour variations in spatial distribution of gender, age and social class within cities remain poorly explored and combined in the segregation literature mainly centred on home places from a single social dimension. Taking advantage of 49 mobility surveys compiled together (385,000 respondents and 1,711,000 trips) and covering 60% of France’s population, Julie Vallée and Maxime Lenormand use Mobiliscope data to study variations in hourly populations of 2572 French districts after disaggregating population across gender, age and education level. They first isolate five district hourly profiles (two ‘daytime attractive’, two ‘nighttime attractive’ and one more ‘stable’) with very unequal distributions according to urban gradient but also to social groups.

Intersectional approach of everyday geography

Taking as reference the dominant groups (men, middle-age and high educated people) known as concentrating hegemonic power and capital, the authors then explore the intersectional forms of these everyday geographies. They analyze specifically whether district hourly profiles of 'dominant' groups diverge from those of the others groups. It is especially in the areas exhibiting strong increase or strong decrease of ambient population during the day that district hourly profiles not only combine the largest dissimilarities all together across gender, age and education level but are also widely more synchronous between dominant groups than between non-dominant groups (women, elderly and low-educated people). These intersectional patterns shed new light on areas where peers are synchronously located over the 24-hour period and thus potentially in better position to interact and to defend their common interests.

To go further


Vallée J, Lenormand M (2024). Intersectional approach of everyday geography, Environment and Planning B: Urban Analytics and City Science, 51(2), 347-365. doi:10.1177/23998083231174025. Preprint arXiv & HAL

Other reproducible papers will be published soon!