New sources of information for characterising mobility

New sources of information for characterising mobility

Characterising the mobility of a city or a territory has always been a difficult task. The movements of people are different, just as we as people are different, and“photographing” so much diversity is never easy.

However, it is essential to do so because it is the only way of properly planning the resources Administrations and Transport Operators will use in order to efficiently satisfy mobility demands.

Traditionally, surveys have been the main source of information for finding out about mobility in a place. It is the way in which it is possible to collect the most complete information, as it is possible to ask the most specific questions and therefore obtain the most exact responses.

Despite this, the Achilles heel of these techniques has always been volume, that is to say, the limited number of people that the survey can be carried out on. In addition to this difficulty, others have emerged, such as the increasing problems of carrying out household surveys (we are less likely to open the door to strangers), the difficulty of finding people at home (whether with a face-to-face or phone survey), the difficulty of finding mobile telephone numbers, increasing data protection laws, etc.

The results of the survey were expanded via capacities (automatic or manual), cordon surveys, the data on people getting on and off public transport, etc.

However, at present, technology and the digital work enable us to avail of other sources of information that provide data for characterising mobility. Thus, mobile telephony, Operation Support Systems (OSS), monetics (payment on public transport using contactless cards), on board navigations systems… provide us, some in real time, with information about the movement of people.


The question is, what does one do with such a vast amount of information? Well, firstly, you need to know what its virtues and deficiencies are. Just as we find out the strengths and weaknesses of surveys, we need to be clear about what the different sources can tell us, and what they cannot tell us. We should not ask the impossible.

With mobile data, for example, we can ask it to tell us from where to where a large number of people within a city, or a territory go throughout a day. But, we cannot get it to tell us how they have done so (in public transport, in a private vehicle, by bike, walking).

With browsing systems, we can ask about travel speeds, but not the total number of people who come and go.

With an OSS we can ask for information about the offer of public transport, its quality, about whether the services are on time or not, but we cannot find out how many people have embarked.

With monetics, we can ask for information about demand, find out what stops users get on and off at, but we cannot find out where they came from or where they were going, or why they were travelling.

Because, if we want to find out why they were travelling, we need to return to the survey, in order for people to say how and why out loud. And thus, we can close the circle.


It is said that good chefs are the ones that take the ingredients they have to hand and prepare the best stew with them. What we have to do here is very similar to that.

Now that we know what to ask from everyone, we need a recipe in order to get the most out of every ingredient, and be able to combine them. To do so, we will need to analyse what the volume of information is that we can obtain from each source according to the reality that we encounter (characterising a very dense city is not the same as a rural province, and nor will we have the same availability of data), the time and budget that we have, etc.


In any case, there is a nuance that we need to take into consideration. Previously, surveys offered us an image, the photograph of a specific place at a specific time. Now, thanks to sources of data that supply with information continuously, that photo can be turned into a film, that is to say, a series of photos that, when viewed at enough speed, show us living images, in movement. And thus, we can have a revamped image of mobility without the need to survey again, just by using data which, in many cases, we already have, or that is much easier (and cheaper) to obtain.

Thanks to that, we will have an updated vision of mobility, and we can thus implement planning in a more efficient manner, with a better knowledge of reality and optimising resources.

Do you remember what was one of the first films of all time? It was called Arrival of a train at La Ciotat, and it showed just that, a train arriving at a stain. It is time to move beyond the photo camera, let´s make our own cinema.

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