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 present population in every district at exact hours (04.00, 05.00 etc.) during a typical weekday (Monday-Friday).

Number and proportion of present 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 (v4.1).
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.

accordeonmenu

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).

oursins

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.

timeline

4) Explore a specific district

Select one district by clicking on the map.

select-secteur

Have a look at the chart entitled "In the selected district" where you can follow hourly variations of present 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.

graph-empile

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

graph-simple

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.

duncan

The example above displays, hour by hour, the Duncan Index (Paris region - 2010) for to present people 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 present people 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 of the profiles of the population present for the neighbouring districts.

moran

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 present subgroup under consideration); the closer its value is to -1, the more dissimilar the spatially close districts are (with different distribution of the present 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.

Enjoy!

Data

There are 58 city regions (in France, Canada and Latin America) included in the actual version of the Mobiliscope.

Origin-destination surveys

The data comes from large 'Origin-Destination' surveys

In the 'Origin-Destination' surveys, every trip made on the day before the survey was reported by respondents. The following variables were available for each trip: precise localisation of place of departure and place of arrival, time of departure and time of arrival (with exact minutes), trip purpose, and mode of transportation used. In the Canadian surveys, time of arrival was not requested from every respondent. These missing values have been replaced either from trip duration of comparable trips or from GIS computation.

Hourly district location

The Mobiliscope team has transformed the trip dataset into location dataset:

  • 24 hourly time steps were defined to get 24 cross-sectional pictures of respondents' locations at exact hours (04.00, 05.00 etc.). Short locations in the interval between two exact hours are then not registered in district hourly dataset.
  • Only trips occurring during the week (Monday-Friday) are considered to estimate hourly location during a typical weekday
  • Transportation periods were also not considered except if respondents reported to use an 'adherent' mode of transportation (i.e. walking or cycling). In this case, half of the trip was considered as located in the district of origin and the other half as located in the district of destination. In the (rares) cases where 'adherent' trip symmetrically straddling an exact hour, location at this very hour was chosen to be in the district where respondent stayed the shortest time (because the longest duration taking place in the other district has a high probability to be registered at another hour).

Hourly location (which do not allow the re-identification of respondents) are displayed in the Mobiliscope. For French cities, theses hourly location data are freely downloadable and reusable, as they remain under open license (ODbL) and the sources are mentioned. Data can be downloaded by clicking the button above the central map.

Studied population

Only respondents aged 16 years and over (or aged 15 years and over in Canadian cities) are taken into consideration.

Measures displayed in the Mobiliscope have been estimated taking into account weighting coefficients to grant the same distribution and the same population size than observed in population census.

  • In French cities, weighting coefficients are based on household profile (size and housing type) and on individual profile (age, sex, and for the Paris Region, occupation and socioprofessional group).
  • In Canadian cities, weighting coefficients are only based on sex and age of participants.
  • In Bogotá, weighting coefficients were adjusted on the number of households enumerated by the census. In Santiago, weighting coefficients are based on household profile (size and vehicle equipment) and on individual profile (age, sex). In São Paulo, we do not have all the elements.

Districts

In the Mobiliscope, cities have been subdivided into districts. Districts are smaller in inner cities and larger in the peripheral areas. In every city region, there is roughly the same number of surveyed residents by district. District was the smallest unit in which it is relevant to aggregate data when it comes to not only ensuring sufficient sample size for statistical analysis but also protecting confidentiality of personal data for the provision of open data.

  • In French cities, districts (called 'secteurs' in French 'Origin-Destination' surveys) are the primary sampling units. They correspond to large neighbourhoods in urban areas and to a 'commune' (or a group of communes) in suburban/peripheral areas. When more than three communes are included in one district, only the names of the three more populated are displayed on mouseover.
  • In Canadian cities, districts correspond to municipalities.
  • In Bogotá, districts correspond to the primary sampling units (named UTAM). Nevertheless, the map backgrounds used in the Mobiliscope are those reworked by Florent Demoraes as part of the ANR MODURAL project, allowing the large, very sparsely populated sectors to be readjusted to the contours of the areas actually inhabited and surveyed.
  • In Santiago, districts were defined by the Mobiliscope team based on the spatial units defined by the Origin-Destination survey, the zonas, according to an objective in terms of the minimum number of residents surveyed aged 16 and over (at least 100) and by preserving as much as possible the coherence of the administrative divisions and their social composition.
  • For São Paulo, districts were also defined by the Mobiliscope team and correspond to the Distritos within the municipio of São Paulo and, outside the municipio, to the zonas defined by the Origin-Destination survey.

More methodological details can be found in the paper Social segregation around the clock in the Paris region (France).

Survey description for every city region

Respondents aged 15 yrs. and over in Canada or aged 16 yrs. and over in the other cities

City region Year Number of respondents Number of weekdays trips Number of locations Number of districts District size in km². Median area (min-max) Number of respondents per district. Median (min-max) at 3am Number of respondents per district. Median (min-max) at 3pm
Albi region 2011 2,339 9,171 10,518 15 7 (1.3-54) 155 (148-160) 119 (77-290)
Alençon region 2018 6,520 30,315 31,728 46 145 (1.9-435) 140 (131-154) 118 (78-231)
Amiens region 2010 7,097 30,933 33,241 45 13 (0.8-410) 145 (127-238) 128 (76-443)
Angers region 2012 3,983 18,399 18,908 28 17 (2-111) 138 (124-160) 111 (63-258)
Angoulême region 2012 2,684 11,300 12,463 18 14 (1.5-151) 146 (139-172) 130 (76-249)
Annecy region 2017 4,953 22,944 23,472 34 27 (0.9-486) 143 (130-172) 124 (84-246)
Annemasse region 2016 5,905 26,700 25,307 42 36 (0.8-232) 137 (121-213) 97 (66-162)
Bayonne region 2010 7,387 28,716 32,684 50 20 (0.8-642) 147 (129-171) 122 (88-437)
Besançon region 2018 3,980 17,568 18,679 28 5 (0.5-191) 142 (127-157) 104 (75-451)
Béziers region 2014 4,212 18,661 19,719 30 52 (1.2-822) 138 (130-153) 118 (82-205)
Bogotá region 2019 49,767 127,405 152,725 133 4 (0.8-15) 365 (46-729) 323 (70-1454)
Bordeaux region 2009 13,793 60,641 67,282 95 10 (0.4-1206) 142 (124-216) 127 (61-294)
Brest region 2018 6,519 29,237 31,323 46 13 (0.9-236) 139 (125-161) 116 (74-301)
Caen region 2011 10,000 43,194 48,466 67 15 (0.5-647) 151 (125-165) 123 (70-486)
Carcassonne region 2015 2,891 11,915 13,393 19 36 (0.8-246) 153 (140-159) 119 (90-306)
Cherbourg region 2016 4,207 18,978 21,388 28 42 (1.3-231) 150 (142-158) 125 (88-337)
Clermont-Ferrand region 2012 8,052 34,182 37,639 56 39 (0.7-471) 144 (130-159) 112 (71-374)
Creil region 2017 4,581 18,956 19,471 31 16 (1-144) 146 (140-153) 104 (60-199)
Dijon region 2016 4,372 18,685 20,035 30 6 (0.7-241) 142 (126-179) 120 (67-341)
Douai region 2012 5,344 23,883 22,973 38 8 (1-54) 139 (127-160) 110 (64-214)
Dunkerque region 2015 4,537 22,491 22,585 32 9 (1.1-117) 140 (128-154) 114 (71-290)
Grenoble region 2010 13,834 63,336 67,131 97 14 (0.2-834) 139 (124-273) 107 (50-473)
Paris region 2010 26,312 124,258 130,329 109 26 (3-1324) 235 (129-420) 204 (86-746)
La Réunion region 2016 13,801 53,363 57,813 99 11 (0.6-275) 139 (121-159) 124 (72-321)
La Rochelle region 2011 2,902 12,203 13,847 19 8 (1.3-40) 153 (137-164) 120 (75-403)
Le Havre region 2018 6,540 29,029 30,608 43 25 (0.7-256) 141 (127-262) 108 (72-436)
Lille region 2016 7,950 38,180 39,031 57 5 (1-56) 138 (123-156) 118 (76-324)
Longwy region 2014 3,347 13,178 13,589 22 32 (2.2-200) 152 (145-160) 108 (79-156)
Lyon region 2015 24,072 99,585 107,667 169 10 (0.4-346) 140 (121-251) 122 (68-445)
Marseille region 2009 19,380 87,031 93,970 137 18 (0.3-342) 141 (117-165) 118 (67-402)
Martinique region 2014 4,179 14,005 16,152 24 36 (4.7-129) 156 (129-283) 146 (110-296)
Metz region 2017 6,492 31,131 31,320 44 13 (1.1-176) 142 (129-238) 112 (70-414)
Montpellier region 2014 11,433 52,387 55,662 80 10 (0.3-547) 140 (126-236) 115 (71-421)
Montréal region 2013 155,854 404,563 510,016 113 36 (1-762) 1069 (116-4551) 862 (109-9657)
Nancy region 2013 9,657 40,664 43,563 68 17 (0.6-407) 142 (124-163) 111 (57-542)
Nantes region 2015 17,358 81,924 85,372 123 21 (0.6-331) 138 (113-195) 118 (66-389)
Nice region 2009 14,989 58,239 65,860 104 5 (0.4-505) 143 (128-163) 126 (65-389)
Nîmes region 2015 4,519 18,598 19,271 31 8 (0.3-152) 144 (132-168) 114 (75-327)
Niort region 2016 2,869 12,705 13,895 19 15 (1.1-156) 150 (142-160) 130 (83-226)
Ottawa-Gatineau region 2011 48,767 149,147 180,842 26 58 (2.6-1278) 1792 (400-4367) 1568 (338-4702)
Poitiers region 2018 4,106 17,305 18,586 28 51 (1.1-228) 140 (127-255) 104 (60-450)
Québec region 2011 48,663 135,788 168,394 69 16 (1.5-697) 666 (301-1553) 529 (179-2416)
Quimper region 2013 4,696 17,291 20,382 30 57 (2.5-260) 152 (142-200) 130 (96-285)
Rennes region 2018 9,317 44,004 45,964 68 55 (0.8-466) 136 (118-159) 106 (64-381)
Rouen region 2017 8,905 38,146 40,260 63 15 (1.1-231) 140 (118-166) 108 (59-295)
Saguenay region 2015 13,942 41,229 50,038 21 26 (3.2-616) 667 (456-760) 601 (326-1200)
Saint-Brieuc region 2012 3,570 14,556 16,190 22 8 (1.1-35) 152 (146-245) 124 (71-377)
Saint-Étienne region 2010 8,525 38,576 40,284 52 30 (1.2-345) 156 (137-220) 127 (78-333)
Santiago region 2012 29,733 75,733 93,088 185 3 (0.7-855) 156 (93-412) 121 (58-1130)
São Paulo region 2017 71,866 152,975 203,777 259 11 (1.3-522) 146 (60-1540) 162 (40-1870)
Sherbrooke region 2012 19,909 58,361 70,571 28 22 (1.7-357) 668 (533-1245) 505 (329-1518)
Strasbourg region 2009 10,052 46,935 48,815 67 35 (0.6-581) 145 (128-225) 123 (78-284)
Thionville region 2012 3,609 15,676 15,585 22 7 (0.6-62) 164 (155-173) 106 (80-246)
Toulouse region 2013 11,141 48,919 53,524 66 11 (0.9-237) 154 (128-331) 128 (66-530)
Tours region 2019 7,624 33,388 36,137 54 43 (0.5-637) 139 (122-160) 120 (78-279)
Trois-Rivières region 2011 18,936 50,687 63,028 28 62 (1.9-305) 562 (422-1514) 428 (284-1444)
Valence region 2014 5,143 23,230 24,159 36 41 (1.3-477) 142 (127-163) 122 (72-326)
Valenciennes region 2019 5,647 46,441 23,662 41 12 (0.9-51) 137 (125-150) 112 (75-256)