Active mobility at GI-Forum conference

Today, I had the honour to chair another special session that dealt with GIS and mobility research at this year’s GI-Forum conference internet. The session “Spatial Perspectives on Active Mobility” was the third in a series (see here internet for a review of the 2016 and here internet 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 internet 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 internet from Vienna University of Economics and Business opened the session at the very local scale. She presented her work internet on landmark-based indoor navigation. Although the applied ILNM (“indoor landmark navigation model”), an extended version of Duckham’s et al. (2010 internet) 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 internet) award for excellent master theses. Congratulations!
  • Ulrich Leth internet (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 internet 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 internet (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 internet). 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 internet 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 internet, will host a special forum on autonomous driving internet 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 internet and stay updated.

Cycle Competence Austria @Velocity2017

Take all relevant research institutions, planners and consulters, interest groups, authorities and manufacturers that are engaged in bicycling – voila, what you get is “Cycle Competence Austria” internet, an association of researcher and practitioners, who joined forces for the sake of further pushing the current bicycling boom and making knowledge available.

Klick on the picture to open a short Storify summary of the session.

The world’s biggest bicycling summit – Velo-city internet – takes place in Arnhem-Nijmegen, in the Dutch province of Gelderland these days. Today the Cycle Competence Austria had the nice opportunity to present bicycling knowledge “Made in Austria” to a broad audience.

Being a nation with still a lot of potential for a larger bicycle mode share, but quite exhaustive experiences and a growing body of knowledge, Austria can serve as front runner for so called climbing nations. In this session, six members of the Cycle Competence network presented their respective contribution to a prospering bicycling environment.

Martin Eder, the national bicycle advocate internet, started the series of presentations with an overview of national activities for bicycle promotion. He paid special attention to the second edition of the national masterplan internet, in which the official goal of 13% in the modal split by 2025 is published. In order to reach this, several national initiatives, such as the research funding program “Mobility of the Future” internet are launched and supported.

After Martin, Andrea Weninger from Rosinak & Partner internet shared here extensive experience in bicycle masterplan creation processes. She came up with a list of six points, which she regards to be essential for successful planning processes. Two of these success factors are to go for user-tailored masterplans (instead of copy-pasting elements from elsewhere), which are inspired by locals.

Andreas Friedwagner (Verracon internet) went on with a GIS-based analyses of accessibility and travel time analysis in the federal state of Vorarlberg. His beautiful maps clearly indicate which areas are well-served in terms of bicycle infrastructure and where improvements need to be made in order to motivate people to switch from car to active mobility. Interestingly, Andreas found in his studies that speed limits for cars (30 km/h within residential areas) have the most direct impact on overall bicycling safety.

Currently we are in an interesting transition phase from data scarcity in bicycle promotion to a data deluge (one of Andrea’s argument was that not everything that could be measured really contributes to a better understanding). However, the colleagues from BikeCitizens internet with their CEO Daniel Kofler do a great job in packing routing and navigation, promotion with gamification components and bicycle intelligence into a single app: the BikeCitizens app internet.

The session was completed by two contributions from research institutions. First I gave an overview of three current research project and argued that the spatial perspective facilitates joint efforts across domain boundaries:

After my presentation, Markus Straub from AIT internet presented two projects, each with a spatial optimization component: the EMILIA project internet seeks, among others, to optimize parcel deliveries in cities. In order to so the last miles from central distribution hubs to the consumer should be done by cargo-bikes. Markus and his colleagues have developed a route optimization algorithm for the delivery bicyclists. In the BBSS project internet a spatially explicit planning tool for optimizing the location of bike sharing stations was developed. This tool allows planners to estimate the potential demand for any location in a city.

Got interested in what happens in Austria in terms of bicycling research and promotion? Leave a comment here, visit the Cycle Competence Austria association booth at Velo-city or you can use Twitter internet or e-mail internet anytime.

Floating Bicycle Data

Our colleagues from Salzburg Research (SR) internet are very active in the field of floating car data generation, management and analysis. Among others, this real-time traffic status service internet 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 internet. 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 internet, 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 internet) 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):

  1. 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 internet) 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 internet data in Salzburg).
  2. 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 internet from the COWI project).
  3. 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.
  4. 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 internet.

Topics for GIScience master theses

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 internet. 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).

FamoS
Our part in the FamoS internet project is, among others, to develop an agent-based bicycle flow model for an entire city. In this context we offer two topics:

  1. Behavior to space (description internet)
  2. Exploring geoprocessing, geovisual analytical and mapping functionalities of GAMA (description internet)

GISMO
Experts from sports medicine, GIScience and transport planning and management are collaborating in the GISMO internet 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:

  1. Analysis of movement data from fitness watches (description internet)
  2. Linking travel diaries and GPS trajectories (description internet)

The topics are primarily offered to local internet and UNIGIS internet students. However, I’m also open to any other form of supervision and collaboration, given we find a sound format for it.

Lecture series “Active Mobility”

Since the VeloCity internet conference took place in Vienna in 2013, the Institute of Transportation internet (Vienna University of Technology) hosts an annual lecture series on bicycling and active mobility in general.

This semester, 80-100 students from various planning domains (urban, transport, regional planning) are attending the weekly lecture on “Active Mobility” internet. Yesterday I had the privilege to present parts of my current research and provide an overview of potential contributions of spatial information to an enhanced bicycling safety situation (slides in German language):

Although some of the students have already worked with GIS, none of them employe GIS in the context of mobility or transport research (at least nobody raised his/her hand when I was asking). Thus, I was happy to serve an appetizer for introducing the spatial perspective to a rather “technical” planning community.

Spatial information and bicycling safety

Originally, this blog was intended to document the progress of my PhD research. Mhm, this goal has been successfully reached yesterday …

Successfully defending my doctoral research (pictures by R. Wendel)

I finished my doctoral studies with a thesis on Spatial Information and Bicycling Safety and yesterday’s defense. The thesis internet 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.

Structure of the thesis

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 internet and – even more preferably – in face-to-face communication!

OSMaxx: the easy access to OSM data

OpenStreetMap internet is much more than a free map of the world. It’s a huge geo-database, which is still growing and improving in quality. OpenStreetMap is a great project in many respects!
But because it is a community project, where basically everyone can contribute, it has some particularities, which are rather uncommon in authoritative data sets. There, data is generated according to a pre-fixed data standard. Thus, (in an ideal world) the data are consistent in terms of attribute structure and values. In contrast, attribute data in OpenStreetMap can exhibit a certain degree of (semantic) heterogeneity, misclassifications and errors. The OSM wiki internet helps a lot, but it is not binding.
datamodel_networkAnother particularity of OpenStreetMap is the data model. Coming from a GIS background I was taught to represent spatial networks internet as a (planar) graph with edges and nodes. In the case of transportation networks, junctions are commonly represented by nodes and the segments between as edges. OpenStreetMap is not designed this way. Without going into details, the effect of OSM’s data model internet is that nodes are not necessarily introduced at junctions. This doesn’t matter for mapping, but for network analysis, such as routing!

In 2014 I presented internet and published internet an approach that deals with attributive heterogeneity in OSM data. Later I joined forces with Stefan Keller internet from the University of Applied Sciences in Rapperswil, Switzerland and presented our work internet at the AAG annual meeting 2015 in Chicago.
Since then Stefan and his team have lifted our initial ideas of harmonized attribute data to an entire different level. They formalized data cleaning routines, introduced subordinate attribute categories and developed an OSM export service, which generates real network graphs from OSM data. The result is just brilliant!

osmaxx

Two maps with very different scale made from the same data set.

The service can be accessed via osmaxx.hsr.ch internet. There, a login with an OSM account is required. Users can then choose whether they go with an existing excerpt or define an individual area of interest. In the latter case the area can be clipped on a map and the export format (from Shapefiles to GeoPackage to SQLite DB) and spatial reference system can be chosen. The excerpt is then processed and published on a download server. At this stage I came across the only shortcoming of the service: you don’t get any information that the processing of the excerpt takes up to hours (see here internet).
However, the rest of the service is just perfect. After “Hollywood has called” the processed data set can be downloaded from a web server.

OSMaxx interface.

OSMaxx interface.

osmaxx-downloadThe downloaded *.zip file contains three folders: data, static and symbology. The first contains the data in the chosen format. In the static folder all licence files and metadata can be found. The latter is especially valuable, because it contains the entire OSMaxx schema documentation. This excellent piece of work, which is the “brain” of the service is also available on GitHub internet. Those who are interested in data models and attribute structure should definitely have a look at this!
The symbology folder contains three QGIS map documents and a folder packed full with SVG map symbols. The QGIS map documents are optimized for three different scale levels. They can be used for the visualization of the data. I’ve tried them for a rather small dataset (500 MB ESRI File Geodatabase), but QGIS (2.16.3) always crashed. However, I think there is hardly any application context where the entire content of an OSM dataset needs to be visualized at once.

Of course, OSMaxx is not the first OSM export service. But besides the ease of use and the rich functionality (export format, coordinate system and level of detail), the attribute data cleaning and clustering are real assets. With this it is easy, for example, to map all shops in a town or all roads where motorized vehicles are banned. Using the native OSM data can make such a job quite cumbersome.
I have also tried to use the data as input for network analysis. Although the original OSM road data are transformed into a network dataset (ways are split into segments at junctions), the topology (connectivity) is invalid at several locations in the network. Before the data are used for routing etc., I would recommend a thoroughly data validation. For the detection of topological errors in a network see this post internet. Maybe a topology validation and correction routine can be implemented in a future version of OSMaxx.

In the current version the OSMaxx service is especially valuable for the design of maps that go beyond standard OSM renderings. But the pre-processed data are also suitable for all kinds of spatial analyses, as long as (network) topology doesn’t play a central role. Again, mapping and spatial analysis on the basis of OSM data was possible long before OSMaxx, but with this service it isn’t necessary to be an OSM expert and thus, I see a big potential (from mapping to teaching internet) for this “intelligent” export service.