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.
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” , an association of researcher and practitioners, who joined forces for the sake of further pushing the current bicycling boom and making knowledge available.
The world’s biggest bicycling summit – Velo-city – 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 , 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 , 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” are launched and supported.
After Martin, Andrea Weninger from Rosinak & Partner 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 ) 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 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 .
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 presented two projects, each with a spatial optimization component: the EMILIA project 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 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 or e-mail anytime.
Since the VeloCity conference took place in Vienna in 2013, the Institute of Transportation (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” . 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.
OpenStreetMap 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 helps a lot, but it is not binding.
Another particularity of OpenStreetMap is the data model. Coming from a GIS background I was taught to represent spatial networks 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 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 and published an approach that deals with attributive heterogeneity in OSM data. Later I joined forces with Stefan Keller from the University of Applied Sciences in Rapperswil, Switzerland and presented our work 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!
The service can be accessed via osmaxx.hsr.ch . 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 ).
However, the rest of the service is just perfect. After “Hollywood has called” the processed data set can be downloaded from a web server.
The 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 . 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 . 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 ) for this “intelligent” export service.
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.
Earlier this year we published a very detailed spatial (and temporal) analysis of bicycle crash data from Salzburg (Austria) in Transport Geography . In this paper we demonstrated the additional benefit of an explicit spatial perspective on crash reports. However, one of the major objections was, that meaningful conclusions from such an analysis can only be drawn when an exposure variable is introduced. This objection stems from the well established methodology of risk calculation in bicycle safety analysis (the quality of commonly used exposure variables is a whole different story as I’ve exemplified in an earlier post ).
Because of the lack of sound exposure variables on the local scale – this is the scale I’m especially interested in – most bicycle risk analyses are done on a highly aggregated level. Last year we were, at least partly, successful in overcoming this shortcoming. With an agent-based simulation model (Wallentin & Loidl 2015 ) we estimated the traffic flow for every road segment in an urban road network. This model allowed us to take the final step now: bicycle risk estimation on the local scale.
Theoretically we are able to calculate incident rates (commonly used synonymously with “risk”) for each and every road segment. However, thanks God, bicycle crashes are relatively rare; and officially reported ones are even rarer. Consequently the statistical robustness of calculated incident rates is weak, leading to analysis results that are potentially biased by random effects. Thus, we defined and investigated different spatial reference units, which served as spatial aggregation levels:
Whenever point incidents are spatially analyzed, two well-known and still challenging phenomena need to dealt with: spatial heterogeneity and the modifiable areal unit problem (MAUP).
Although the Geography literature on these two implications is full, they are hardly ever anticipated in (bicycle) crash analyses. We therefore regard our paper not only as a presentation of our analysis results, but also as an example for how to adequately deal with geo-located data.
Here is the abstract of the paper (full text ), which was published in a special issue of the OA journal “Safety” :
Currently, mainly aggregated statistics are used for bicycle crash risk calculations. Thus, the understanding of spatial patterns at local scale levels remains vague. Using an agent-based flow model and a bicycle crash database covering 10 continuous years of observation allows us to calculate and map the crash risk on various spatial scales for the city of Salzburg (Austria). In doing so, we directly account for the spatial heterogeneity of crash occurrences. Additionally, we provide a measure for the statistical robustness on the level of single reference units and consider modifiable areal unit problem (MAUP) effects in our analysis. This study is the first of its kind. The results facilitate a better understanding of spatial patterns of bicycle crash rates on the local scale. This is especially important for cities that strive to improve the safety situation for bicyclists in order to address prevailing safety concerns that keep people from using the bicycle as a utilitarian mode of (urban) transport.
With this analysis we have successfully demonstrated that mapping bicycle risk patterns on the local scale reveals relevant information for policy makers and authorities, which aggregated approaches would not have been able to uncover. To our current knowledge this is the first study, which calculates crash rates on the local scale. However, with the increasing amount of available data and improved (spatial) models, we are quite sure that many more analyses like this one will follow – for the good of bicyclists and building blocks for evidence-based safety strategies.
As the number of geographers dealing with bicycle safety and crash analysis is rather small, I’d be more than happy to read from you. Do you have any questions, ideas for further studies, data or just a comment – feel free to leave your note below, connect on Twitter or get in touch with me via the contact form.
The twin conferences AGIT and GI-Forum took place in Salzburg three weeks ago, complemented by the German language FOSSGIS conference. This fully packed conference week had a lot to offer (see my Twitter diary ) and definitely was an inspiring week. With a short time lag in between I’d like to reflect on a topic that popped up at various occasions and is very relevant to my PhD project: geography’s contribution to mobility and transport (research).
To make it very short, these are my key take home messages:
- The geo-space is very powerful in integrating various data/information layers and facilitating holistic approaches for research, planning and operation.
- Technology driven arguments are annoying. It’s always about people.
- Geography supports system thinking, which is required in any mobility and transport topic.
Harvey Miller from Ohio State University opened the GI-Forum conference with his keynote on “Big Data for Healthy Places”. Referring to Pollocks article in Nature , Harvey made a strong case for how the built environment affects mobility and subsequently public health. In his keynote Harvey identified two major challenges in the context of healthy cities: firstly, cities, which are human systems, are complex systems and secondly, policy interventions can have unclear or even counter-intuitive outcomes. In order to tackle these challenges, Harvey proposed what he termed Geographical Information Observatories (GIO), which facilitate opportunistic GIScience. A GIO is a way to constantly monitor certain areas or phenomena and link the sensed data to other data or information sources. Here, the geographical coordinate plays a central role as common denominator for all data or information layers (‘spatial index’). So called urban dashboards (such as CURIO ), which are fueled by GIOs, are the basis for opportunistic GIScience, a framework for spatial science which is able to adapt to spontaneous events, combine real-time with historic data and to simulate planned interventions in a virtual environment. This way, complex systems can be studied, monitored and influenced in a naturalistic setting and intended measures can be tested for their effect on the whole system prior to implementation.
Some of the keynote’s topics had already been discussed before in an interesting panel discussion on the relation between GIScience and Data Science, organized by Peter Mandl . Besides Harvey, Petra Staufer-Steinnocher and Josef Strobl discussed as panelists.
Peter argued for the integration of recent developement in GIScience, namely linked data, open data and semantics, into “Spatial Data Science”.
Harvey made two crucially important points: Data scientists tend to go for correlations (predicting and control paradigm) instead of focusing on causalities in complex systems; for the latter domain experts are needed who interpret correlations in the respective (spatial) context and transform data into information. Conceptually related to this observation, Harvey pointed to the fact that not all decisions should be made quick and purely data- or algorithm-based (the reference to the Jevons paradox is highly interesting in this context). This critical statement is often missing in Smart Cities debates!
gicycle (@gicycle_) July 06, 2016
Similar to Harvey, Josef made a few conceptual statements, which are often overlooked in “data-positivistic” discussions. In his opinion, correlations and pattern detection are only ways to make sense of massive data (streams); they have little value for themselves but act as filters and hypothesis generators. Again, he underpinned the role of domain experts, who are indispensable when exploratory studies are lifted to explanatory ones. In analogy to this conceptual difference and referring to the relation of GIScience and Data Science, Josef stated, “Data leads to explorations, science leads to findings”.
Being affiliated with the Vienna University of Economics, Petra put a focus on Business Analytics (which has, of course, a lot in common with Data Science!) and called for a tight coupling of data driven approaches to theory-based science. In her opinion, Business Analytics is currently too often only about dehumanizing people (clients) and turning them into data.
On Wednesday Anita Graser kicked-off the German language AGIT conference with her keynote on “OpenSource, OpenData and OpenScience”. In the afternoon I first attended a session on Urban Geoinformatics (I co-authored one of the presented papers ), which was nicely wrapped up by Joao Porto . He stated very clearly that Urban Geoinformatics is the intersection of people (urban), technology (informatics) and place (geo). This rather simple definition is blanked out ways to often in current discussions!
After that, this year’s special session on GIS-T (“Spatial perspectives on transport systems” ) took place with three excellent presentations and lots of discussion. The session was opened with a session keynote by Harvey Miller, who provided an overview of the role of GIS in transport (research). Referring to his article from 2015, Harvey talked about the fast changing environment of our discipline (presentations slides are available here ):
- Data availability and computational power have been increasing constantly over the last years.
- Despite the predicted abolition of space through the Internet, progressive urbanization is changing the human sphere radically (urban metabolism ).
- The success of the smart phone, which is constantly connected to the Internet, facilitates new applications, methods for data capturing and business models; most of them are location-based.
The other two contributions to the session were rather technical: Mario Dolancic, the winner of this year’s student paper award, presented an approach for lane detection from floating car data. Mario’s motivation for his work, which is part of the LaneS project, was humorous, “I’m a student and don’t have the money. But I want a realistic road graph.”
gicycle (@gicycle_) July 06, 2016
Anita Graser provided insights in current algorithms for realistic pedestrian routing across open spaces and presented an efficient approach for OpenStreetMap data (for more information visit the PERRON project website).
Thursday was like a roller coaster ride. The day started and closed with sessions on authoritative spatial (transport) data. I had never expected to attend a GIP forum where the majority of contributions discussed how authoritative data can be made available to the public. The digital road graph can be completely downloaded via data.gv.at . This rich dataset can be nicely coupled with national address data that were made available just recently. In the afternoon OGD strategies on various administrative levels were discussed in a GeoTalk (the presentation slides have been made available on the organization’s website , scroll to GeoTalk #10), organized by the local GIS cluster.
In between these sessions I attended a special forum on autonomous driving. Although some of the contributions where innovative and relevant (for instance Benno Bock’s presentation on car sharing patterns ), the forum was dominated by automotive lobbyists who demonstrated a very narrow perspective on mobility. It was a bit frustrating to see how much money is put into R&D with an exclusive focus on the car. There is little effort to completely re-think mobility as a system. Here is just one example: Graham Smathurst from VDA was asked how to understand BMW’s slogan “Freude am Fahren” (pleasure in driving) in times of autonomous vehicles. His answer spoke volumes: On Monday when he drives to work and roads are congested (!) he prefers the autonomous mode, while on a sunny Sunday afternoon he enjoys to drive himself. There was not a single trace of rethinking commuting patterns or mobility behavior. Nothing. Similarly, Christian Kleine from Here presented the company’s ambitions and technology, illustrated with a picture of a self driving car in a massive congestion.
The sessions I attended on Friday nicely demonstrated the potential of the spatial perspective and GIS technology in models, applications and participatory planning processes:
- Enrico Steiger gave an update of the excellent OpenRouteService .
- Nikolaus Krismer gave a presentation on his PhD project about multimodal isochrone calculation.
- Stefan Herbst demonstrated the Mobility Optimizer , a multi-layer information and analysis tool for evidence-based (planning) decisions.
- In the very last presentation of the conference, Dennis Groß presented his thesis where he combined bio-physical sensor data with locations and produced maps of increased stress for cyclists.
What all these contributions have in common, is the added value of an explicit consideration of spatial information. And because transport systems and mobility are spatial by their very nature, geography has a lot to contribute to a better understanding of these complex and dynamic systems. This is why we will definitely organize another GIS-T session for the GI-Forum conference next year. It would be great if you could consider this in your publication and dissemination plans for 2017 (the CfP will be published in December 2016).