A recent publication of the national klimaaktiv program caught my attention last week. Following this report, 55% of all kids in Austria are brought to kindergarten by car. The share of kids cycling to kindergarten is below 5%.
As the figures are for Austria, I don’t know if they are representative of my home town. Unfortunately, I haven’t found any statistics for Salzburg. My personal experience is that the number of kids on bicycles is very low – at least in my kids’ kindergarten. Most of the time we are the only one coming by bike.
Independently from the availability of statistics, open (government) data allowed me to do a bit of spatial analysis on the accessibility of kindergartens in Salzburg. The results are striking: there is virtually no need to bring kids to kindergarten by car in terms of distance or travel time. However, the environment of kindergartens is not always pedestrian- and bicyclist-friendly and of course, this impacts the mode choice for bringing and picking-up kids.
For the analysis I used the following data and settings:
- Address data are available from the federal Bundesamt für Eich- und Vermessungswesen. The dataset can be downloaded from their website .
- The location of kindergartens are published as OGD by the city administration. The most direct way to the data is to use this WFS . I need to add a disclaimer here: I’m not sure whether all kindergartens are included in this data set. Probably, not all private facilities are on the list.
- For the network analysis I used authoritative road data (GIP ), published as OGD and enriched this dataset with additional information, which is also available via the national OGD portal .
- I used the routing engine from ArcGIS Desktop 10.4 for performing the network analysis.
For the optimization of bicycle routes I employed the impedance model we have developed a few years ago for a bicycle routing service (see here and here for details). An average speed of 15 km/h (which might be a little bit too high) and global turn impedance at intersections were used as input parameters. For the pedestrian routes the shortest path was calculated and an average walking speed of 0.8 m/s was assumed.
- The walkability and bikeability index were modelled in the context of the GISMO research project; details are going to be published soon.
The average walking time to the next kindergarten, considering all address points in Salzburg is 8.14 minutes with a standard deviation of 6.10 minutes. The median is 6.86 minutes. 74% of all address points (16,741 of 22,694) are within 10 walking minutes from the next kindergarten. This means that 3 out of 4 kids could walk to kindergarten within a reasonable time.
These figures are even more striking when kids cycle to kindergarten. The average travel time is 2.90 minutes (!) with a standard deviation of 2.21 minutes. The median is 2.42 minutes. From 89% of all address points in Salzburg the next kindergarten could be reached in less than 5 minutes. This figures rises to incredible 98% for a maximum travel time of 10 minutes. Plotted on a map these figures look like this:
Although these numbers are striking, obviously, there are good reasons for parents not to let their kids walk or bicycle. Interestingly, the scientific evidence on influential factors on the mode choice for kindergarten-related trips is weak (not to say nonexistent). Studies of school pupils’ commuting trips reveal a significant impact of parent’s perception of the suitability of the environment on the mode choice (see for example Timperio et al. (2004) or Bringolf-Isler et al. (2008) ). The impact of parents’ perception and behavior might be even bigger for kindergarten kids. In any case, the quality of the environment needs to be high in terms of pedestrian- and bicyclist-safety if active mobility should be further promoted. That this is currently not always the case, becomes obvious in the following maps:
Last year, results of a large study on the relation of urban environments and level of physical activity were published in the prestigious medical journal The Lancet . The authors found that approximately 50% of the WHO recommendation of 150 minutes physical activity per week can be stimulated by an adequate environment.
Thus, the provision of safe and comfortable infrastructure has a huge effect, far beyond kids walking or cycling to kindergarten. Usually, this effect is quantified in terms of health, environment or economy. But apart from these important dimensions there is another one when it comes to kids. As Moran et al. (2017) proved earlier this year, the mode choice influences navigation skills and (spatial) knowledge of the neighborhood. As a geographer I’m tempted to conclude that these findings are a sufficient argument for further promoting active commuting to kindergarten and school!
Today, I had the honour to chair another special session that dealt with GIS and mobility research at this year’s GI-Forum conference . The session “Spatial Perspectives on Active Mobility” was the third in a series (see here for a review of the 2016 and here for the 2015 session).
Of course, we will have a “Spatial Perspectives on …” session in 2018 again – the call will be published in December this year. So, consider this as an option for your publishing and dissemination strategy (by the way, the GI-Forum journal is open access!)
This year’s special session was a paper session with four speakers, who all went through a rigorous review process. The diversity of the contributions was high, demonstrating the wide range of mobility research where GIS plays a crucial role:
- Irene Fellner from Vienna University of Economics and Business opened the session at the very local scale. She presented her work on landmark-based indoor navigation. Although the applied ILNM (“indoor landmark navigation model”), an extended version of Duckham’s et al. (2010 ) LNM, performed well, Irene pointed to two major challenges: first of all, the ILNM requires very detailed data, which are not always available and secondly, the visibility of landmarks from the perspective of the user is not always given or unknown.
Irene’s paper emerged from her master thesis at the University of Salzburg, where she successfully finished the UNIGIS MSc study program. Dr. Gudrun Wallentin, UNIGIS program director, regarded this special session as perfect stage to hand over the UNIGIS International Association (UIA ) award for excellent master theses. Congratulations!
- Ulrich Leth (Vienna University of Technology) presented the findings of a recent study where they investigated the impact of a bike sharing system on public transit ridership in the city of Vienna, which is famous for its extensive and well-performing public transit system. In total, Ulrich and colleagues analysed 1 million Citybike trips from 2015. Different to the expectation the title provoked, they found that the bike sharing system virtually has no impact on PT ridership, simply because of the huge difference in size and capacity. However, some details in their results were interesting and probably of relevance for other BSS: a) Citybike trips primarily substitute short and inconvenient PT trips, b) most bike sharing trips are made when the travel time ratio compared to public transit is 0,5 and c) the most popular OD relations are typical student trips (between transport hubs and university and student dormitories and transport hubs or universities).
- Tabea Fian, a student from Georg Hauger’s (lead author of the paper) group, also from Vienna University of Technology, presented a spatial analysis of urban bicycle crashes in Vienna. Interestingly, the data were very similar to those I’ve extensively used in my PhD (see this paper ). In a purely exploratory study design Georg has tried to identify blackspots in the network and tested for their significance. However, as it became evident in the discussion, final conclusions are hard to draw without a statistical population.
- The last presentation was given by Anna Butzhammer from RSA iSpace. She presented parts of her excellent master thesis, in which she analysed the inter-modal accessibility of central places. For this, she developed a model that facilitates door-to-door travel time calculations with different modes. Her findings are especially important for planning and optimizing public transit systems, which can be regarded as backbone for sustainable mobility.
Tomorrow, the German-speaking sister conference, AGIT , will host a special forum on autonomous driving and on Friday I will chair another session on advances in GIS-T. Well, there will be a lot to discover, learn and discuss; if you don’t have the chance to be there physically, follow me on Twitter and stay updated.
Our colleagues from Salzburg Research (SR) are very active in the field of floating car data generation, management and analysis. Among others, this real-time traffic status service is fed by their data.
In order to establish a community of researchers, authorities and companies around the topic of floating car data, SR hosts the annual “FCD Forum” in Salzburg. This year, I had the honor to contribute to the program . Since we have been working a lot with bicycling data over the last years, I was asked to evaluate the potentials of a conceptual transfer from FCD to “Floating Bicycle Data”. Well, a very fundamental finding in my research is that the term “Floating Bicycle Data” is not established yet in the scientific literature. Thus, the term is to be regarded as a word game derived from the forum’s agenda. However, I think it makes perfectly sense to invest some efforts in this context.
In my presentation , I started my argumentation from the fact that a) bicycle traffic is a relevant element of urban mobility, b) the modal share is likely to increase in the next years and c) a sound evidence base is required for future investments in bicycling infrastructure.
Currently, very little is known about the spatial and temporal distribution of bicycle traffic within cities. Comparably few permanent counting stations, sporadic, punctual counting campaigns and irregular mobility surveys do not provide sufficient and reliable data to support evidence-based policies on the local scale level. On the other hand, the popularization of the “humans as sensors” concept (Goodchild 2007 ) has opened new possibilities to acquire data on bicyclists’ movements in urban networks. When talking about floating bicycle data, I used it as a catchy term, which summarizes all kind of geo-located movement data from bicyclists; they don’t need to be necessarily in real-time.
As I’ve shown in my presentation, there a numerous application examples where floating bicycle data would make perfectly sense. However, there are several conceptual challenges, which need to be considered (most of them are also relevant for floating car data):
- When floating bicycle data are harvested through crowd-sourcing applications the data are not necessarily representative for the entire population. I referred to participation inequality or the 90-9-1 rule (see Nielsen 2006 ) in this context. Additionally, different apps are used for different purposes. Thus, the data might be biased for example towards leisure trips (as it is the case with Strava data in Salzburg).
- Currently, there is no common data standard and the heterogeneity of bicycle mobility data is huge. Good news in this context were published earlier in this year by the European Commission (see this report from the COWI project).
- Since there is no obligation to register bicycles, the (spatial distribution of the) total population is unknown. Consequently, it is hard to estimate the total bicycle traffic volume from samples. In contrast to that, cars are registered and at least the car holders’ address is known.
- In order to further process movement data (GPS trajectories), a sound and very detailed reference graph is required for map matching. In most cases network graphs are not available at this level of detail (this holds true for authoritative data as well as for OSM). Consequently, GPS trajectories can only be matched to center lines at the moment.
Although this selection of challenges might be regarded as obstacle for a broader engagement (I prefer to interpret them as research opportunities), I expect the topic of floating bicycle data to emerge in the coming years for a simple reason: the market for floating bicycle data is definitely smaller than for floating car data. But, bicycle traffic is already a major element in urban traffic and its share will become even more substantial in the next years. As a consequence, cities need to invest in adequate infrastructure and these investments will hardly be made without a sound evidence base. Floating bicycle data could close a significant gap in this regard.
If you are already working with floating bicycle data (but haven’t used the term yet), have ideas on how to further push the topic or simply want to comment on the concept, please do not hesitate to contact me! I’m happy to learn from your expertise.
For those who are about to write a thesis in this or a related context, have a look at this proposal .
After several months of setting the stage and doing lots of preparatory work, we are currently entering the ‘core phase’ in two research projects at the GI Mobility Lab . In this context we provide the opportunity to Master’s students to participate in the projects and write their thesis in GIScience (or related fields).
Our part in the FamoS project is, among others, to develop an agent-based bicycle flow model for an entire city. In this context we offer two topics:
- Behavior to space (description )
- Exploring geoprocessing, geovisual analytical and mapping functionalities of GAMA (description )
Experts from sports medicine, GIScience and transport planning and management are collaborating in the GISMO research project in order to provide a sound evidence basis for the promotion of active commuting. Part of the research is a clinical study, in which we document the subject’s mobility by different means. For the analysis of this data we offer the following two topics:
- Analysis of movement data from fitness watches (description )
- Linking travel diaries and GPS trajectories (description )
Originally, this blog was intended to document the progress of my PhD research. Mhm, this goal has been successfully reached yesterday …
I finished my doctoral studies with a thesis on Spatial Information and Bicycling Safety and yesterday’s defense. The thesis is based on five peer-reviewed, published papers and aims to strengthen the spatial perspective in bicycling safety research.
The thesis is motivated by the fact that bicycling safety research is dominated by non-spatial domain experts, e.g. with backgrounds in trauma medicine, psychology, bio-mechanics, sociology, epidemiology, engineering, planning, law and some more. Interestingly, the spatial perspective on bicycling safety is hardly ever considered in these domain-specific approaches. This holds especially true for bicycle crash analyses, where basic geographical concepts, such as nearness, spatial autocorrelation and topology, are hardly ever considered.
Neglecting location as a co-determining attribute of safety is remarkable for a very simple reason. Mobility of people – and thus bicycling – as such is spatial by its very nature. Consequently, bicycling safety (from the physical environment to crashes to individually experienced safety threats) has spatial facets, which can be modeled and analyzed accordingly in order to gain relevant information for safer bicycling.
The primary hypothesis of my doctoral thesis is that spatial models and analyses contribute to a better understanding of certain aspects of bicycling safety and provide relevant results, which support measures to mitigate safety risks for bicyclists. Specifically I argued that:
- Geographical Information Systems (GIS) facilitate holistic approaches for improving the bicycling safety situation. The spatial perspective is relevant for virtually all stages of the implementation of bicycling safety strategies.
- Model-based approaches have a great potential in safety assessment and can form the basis for a number of applications – from status-quo analysis to planning and route optimization.
- The spatial analysis of bicycle crashes reveals significant and safety-relevant patterns and particularities, which remain hidden in common, non-spatial or highly aggregated approaches.
- The spatial perspective is crucial for advanced (simulation) models, which are necessary for reliable risk estimations on the local scale. Furthermore, the spatial implications of risk mapping on the local scale must be made explicit.
The thesis is structured in three elements. The first paper demonstrates the contribution of GIScience to bicycling safety research and is intended to set the stage for the remaining papers. Two of them primarily deal with spatial models in the context of road space assessment and transport modeling, while the rest is about spatial analysis of bicycle crashes.
Although the completion of my doctoral studies is a huge, personal milestone, there is still a lot of research work in this context to be done. Besides the further development of the spatial models, the applied statistical methods and analysis routines, I see research gaps in the context of data (from static to dynamic real-time data and data streams), information (e.g. what are the effects of information provision on decision process or on individual and collective behavior?) and cross-domain collaboration.
The amount of work that still lies ahead motivates me to further blog on some of our research activities and to connect with anyone who is interested in spatial information, bicycling safety, urban mobility etc. I’m looking forward to learning, reading and hearing from you in virtual and – even more preferably – in face-to-face communication!
150 participants from 23 countries gathered on November 30th in Rotterdam to attend the VeloCittà bikesharing conference, which was held in conjunction with the annual POLIS conference (450 participants, according to the organizers). While the VeloCittà conference was exclusively dedicated to bikesharing, the POLIS conference offered a broader perspective on sustainable transport. I was in Rotterdam primarily for the POLIS conference because I had a presentation, but it was also a great opportunity to get an impressive update of recent bikesharing practice and research. Lot’s of what I’ve learned can be directly linked to our current involvement in the planning of a bikesharing system in Salzburg, Austria.
All presentations of both conferences can be found on the respective websites. Thus, I will focus only on two topics I’ve found especially relevant for our research and project work.
Success factors for bikesharing systems
In a very interesting session at the POLIS conference on sharing systems, Sebastian Schlebusch from Nextbike gave some insights into the company’s history. Several years they were treated quite harshly by public transit operators who feared for their business. However the break through of bikesharing systems (BSS) came. In accordance with Sebastian’s talk the following success factors occurred in various presentations at both conferences:
- Political support. Obviously this seems to be the most decisive factor for successful BSSs in any country.
- Integrated systems. An increasing number of cities regard bikesharing systems as an element of public transit services. This is reflected in the planning of the network, pricing and promotion. Cologne’s BSS is a good example for a large, integrated system.
- Robust business models. This factor becomes important when initial subsidies fade out. Alberto Castro , one of the keynote speakers at VeloCittà, demonstrated how fast BSSs without sound financial (and operational) basis disappear .
- Appropriate planning. Nicole Freedman, keynote speaker at VeloCittà, made a compelling case for the importance of realistic projections and tailored BSS design. Cities are comparable only to a certain degree and thus, BSSs cannot be simply transferred. Specific (mobility) characteristics of cities, from PT service level to topography, need to be taken into account.
- User-tailored, easy solutions. The needs and expectations of users must be addressed in every aspect: from intuitive interfaces for initial registration to the ease of handling the hardware.
To know and consider people’s reasons for not using BSSs is especially valueable when systems should be improved. In many cases the barriers for BSS usage can be lowered or removed with small adaptions.
- Visibility in public space. In order to raise awareness for bikesharing it is necessary that the system is visible in public space. This visibility can be achieved by an appropriate station design, but also with art in public space.
- Make it beautiful. Directly associated to the latter point Nicole Freedman strongly argued for aesthetically pleasing, beautiful bikes and infrastructure. Way too often BSSs are shaped by technicians and technology. With a good design of hard- and software people can be made curious; once they are attracted to the system, the possibility is high for turning prospective into active users.
At both conferences lots of case studies were presented. At least two of them were really remarkable:
Krakow (~ 760,000 inhabitants) initially launched a system with 30 stations and 300 bikes, which turned out to be not that successful. Thus, the city relaunched the entire system under a new name (Wavelo ) and with 1,500 bikes at 150 stations, which is above the average bikes per people ratio in Europe (ref. OBIS handbook)!
A much smaller, but very successful BSS can be found in Pisa (CICLOPI ). Marco Bertini presented the city’s strategy to make people in Pisa love their bikesharing system: “Bikesharing is note a service for citizens, but part of the community.” With this approach Pisa achieved impressive key figures: 5-8 rides per bike and day, virtually no vandalism and not a single bike stolen in 4 years.
More people are killed in road crashes than by malaria or tuberculosis, according to a recent OECD report that calls for a paradigm shift in road safety. Before this background and with a special focus on the role of large cities the International Transport Forum (ITF ) launched the Safer City Streets project, which was presented by Alexandre Santacreu. The aim of this project is to provide an environment for exchange of data, experience and knowledge. What I regard as an asset of this project is the drive to publish data as OGD.
Alex pointed to the difficulty of comparing data from various sources, especially when crashes of vulnerable road users are investigated (different reporting procedures, classification, under-reporting etc.). Of course, this is nothing new, but my impression is that the limited comparability of data is mostly neglected in analyses of global data (I’ve demonstrated an aspect of this in this post ).
While the Safer City Streets project operates on the global scale, the Netherlands have launched a national project where cities can learn from each other with respect to crash prevention and safety measures. Charlotte Bax from SWOV presented this benchmarking project that is built upon the three elements comparing – learning – improving. Two aspects caught my attention: (1) None of the data are made public because the involved city administrations fear the pressure that might be put on them after publishing crash details. (2) Even in the Netherlands’ city administrations struggle to make use of their data; Charlotte referred to cases where responsible departments were not able to tell how many kilometers of bicycle infrastructure they had.
Benchmarking on the very local level was at the core of Eric de Kievit’s presentation on the development of a compound road safety assessment. For this, two approaches were combined. Firstly, a network safety index, which consists of an enormously detailed description of the road space (every 25 meters the road profile was investigated based on street view photos). And secondly, a safety performance indicator that focuses on road user’s behavior. Both perspectives are then used as basis for targeted infrastructure measures, law enforcement, education and communication campaigns.
My own contribution to the session on road safety was about spatial analysis of bicycle crashes on the local scale level. The presentation was a synthesis of two of my latest journal papers (JTRG and Safety ):
In both conferences it became evident that there are lots of innovative and creative solutions for promoting sustainable mobility in urban environments. However, there is no philosopher’s stone that solves all problems immediately, but cities all over Europe have to work hard to make progress.
I have the strong impression that the discussion and collaboration across domains and institutions is a key for sustainable solutions for cities. Urban environments are complex and thus require multifaceted strategies. In any way, we are ready to contribute spatial expertise for the good of our cities and their citizens.
Although the impact of information on mode and route choice is disputed, the number of bicycle routing and navigation applications is constantly growing.
For this year’s International Cycling Safety Congress (ICSC ) we have investigated 30 current bicycle routing portals with a specific focus on “safety”. The study is limited to web applications with a desktop version and without obligatory registration. Mobile apps, which are increasingly standalone products (or environments) were not considered.
The central hypothesis of our study was that existing bicycle routing portals don’t address prevalent safety concerns explicitly. We further argue that bicycle routing portals might contribute to the promotion of safe(r) routes and consequently to an overall perception of the bicycle as safe mode of transport.
With this study we take a first step towards a better exploitation of information applications’ potential to promote (utilitarian) bicycling. Based on our evaluation, bicyclists’ expectations and the role of routing information in their mobility routines should be investigated in more detail. This would allow for the formulation of design guidelines for future information products for bicyclists.
However, we are totally aware of the fact that information as such can never improve the safety situation – this can only be done by adequate infrastructure. But we see the potential of bicyclist-specific (routing) information to bridge the gap between the current, mostly sub-optimal safety situation and a perfect environment. Geographical Information Systems (GIS) allow for the identification of optimal routes in terms of safety. Depending on the infrastructure, recommended connections might not be perfect, but the best possible solution in the given situation. We have made quite good experiences in this regard with the bicycle route planner we have developed for Salzburg (see Radlkarte.info ).
I know of many highly innovative bicycle routing and navigation applications and I’d be more than happy to learn from your experiences and expertise. I guess we could make a step forward and provide better, user-tailored information if we joined forces. As an invitation to further work on this topic we make the data of our study fully available. You can access the evaluation spread sheet via this link . So let’s get started …