Green Paths -reittiopas edistää terveellistä ja aktiivista matkustamista

Age Poom, Joose Helle, Tuuli Toivonen

Uusi Green Paths -reittiopas auttaa valitsemaan hiljaisemman ja ilmanlaadultaan parhaan pyöräily- ja kävelyreitin.

Pääkaupunkiseudulla toimivan reittityökalun suositukset perustuvat reaaliaikaiseen tietoon ilmanlaadusta sekä kaupungilla tehtyihin melutasomittauksiin. Sovelluksen avulla liikkuja välttää vilkkaasti liikennöidyt kadut, mutta pääsee silti perille kohtuullisessa ajassa.

Helsingin yliopiston Digital Geography Lab -tutkimusryhmä on kehittänyt Green Paths -reittityökalun auttamaan jalankulkijoita ja pyöräilijöitä löytämään miellyttävimmät reitit. Nyt julkistettu sovellus on prototyyppi, joka toimii Helsingin, Espoon, Vantaan ja Kauniaisten alueella.  Näissä kunnissa on saatavilla sovelluksen tarvitsemaa dataa.

Yleensä reittioppaat tarjoavat nopeimpia tai lyhimpiä reittejä, mutta miellyttävyyttä ja terveellisyyttä ei huomioida. Ohjaamalla pyöräilijät ja kävelijät miellyttävämpään matkaympäristöön reittiopas pyrkii edistämään kaupunkiliikkujien terveyttä ja hyvinvointia. Tutkimusryhmämme toivoo reittioppaan edistävän myös ilmastollisesti vastuullista ja kestävää kaupunkiliikennettä.

Kätevintä on tarkastella vaihtoehtoisia reittejä ennakkoon matkapuhelimesta ja tietokoneelta. Erityisesti kävelijä voi myös seurata hieman mutkikkaampaa reittiä matkan aikana. Sovelluksen saa myös puhelimen avausnäyttöön sekä iOS- että Android -puhelimissa.

Green Paths -reittiopas auttaa valitsemaan hiljaisemman ja ilmanlaadultaan parhaan pyöräily- ja kävelyreitin pääkaupunginseudulla.

Green Paths -reittiopas nojaa ajallisen ympäristöaltistumisen arvioinnin käsitteeseen. Osana Helsingin kaupungin koordinoimaa HOPE-hanketta kehitetty työkalu optimoi reittien valinnan ympäristöaltistuksen kustannusten ja matkan keston perusteella. Tämän perusteella se tarjoaa joukon reittejä lyhimmästä pitempiin, mutta terveellisempiin. Reittiopas hyödyntää avoimia ympäristötietoja. Työkalussa käytetään reaaliaikaista ilmanlaatua koskevaa tietoa, jonka tuottamista Ilmatieteen laitos parhaillaan kehittää. Melutietojen osalta käytetään Suomen ympäristökeskuksen ja kuntien tuottamaa tieliikenteen keskimääräistä mallinnettua melutasoa. Katu- ja polkuverkosto reittioptimointiin haetaan joukkoistamalla tuotetusta OpenStreetMap-aineistoista.

Reittioppaan lähdekoodi on julkaistu avoimesti GitHubissa. Työkalu sisältää myös ohjelmointirajapinnan, jonka avulla ympäristön kannalta optimoituja reititystuloksia voidaan viedä muihin sovelluksiin. Lähdekoodin saatavuus auttaa muita kehittäjiä ottamaan ympäristökustannustekijät huomioon matkasovelluksissaan.

Tähän mennessä, Green Paths-reittiopas on kehitetty prototyyppinä ja uusia ominaisuuksia tulee saataville sitä mukaan kun kehitystyö etenee. Reittioppaan tarkoitus on ennen kaikkea havainnollistaa ympäristöaltistumisen huomiovaa reititystä ja sen osalta täytyy siis huomioida, ettei työkalun toiminta välttämättä ole taattua kaikkina aikoina.

Tulevaisuudessa reittioppaaseen tullaan esimerkiksi uutena ympäristöaltituksena sisällyttämään matkanaikaisten vihernäkymien kertymä melu- ja ilmanlaatualtistusten rinnalle. Myös katutasoisten ilmanlaatu- ja melukarttojen tarjoaminen osana reittiopasta kuuluu tulevaisuuden kehityskohteisiin.

Green Paths tool: street level noise
Green paths -reittiopas näyttää keskimääräiset melutasot tieverkostossa

Green Paths -reittiopas löytyy mobiilikäyttöiseltä verkkosivustolta https://green-paths.web.app/, sekä suomeksi että englanniksi. Lisätietoja löytyy verkkosivustolta https://www.helsinki.fi/en/researchgroups/digital-geography-lab/green-paths. Käy siis tutustumassa!

Green Paths -reittioppaan sovelluskehittäjä on Joose Helle. Sovellus on valmistunut Helsingin yliopiston Digital Geography Lab tutkimusryhmässä osana Helsingin kaupungin Elinkeino-osaston koordinoimaa  Urban Innovation Action HOPE –  Healthy Outdoor Premises for Everyone -hanketta. Hankkeeseen osallistuu tutkimusryhmästämme Joose Helle, Age Poom, Tuomas Väisänen ja Tuuli Toivonen.

Healthy Outdoor Premises for Everyone HOPE on Euroopan aluekehitysrahaston Urban Innovative Action-ohjelman rahoittama Helsingin kaupungin koordinoima hanke, jonka tavoitteena kehittää uutta ilmanlaadun täsmätietoa ja edistää sen innovatiivista hyödyntämistä kaupunginosa- ja asukastasolla Helsingissä.

Digital Geography Lab on monitieteinen tutkimusryhmä, joka hyödyntää paikkatietoanalytiikkaa ja isoja aineistoja edistääkseen kestävyyttä ja reiluutta yhteiskunnassa. Pyrimme ymmärtämään ihmisten, yhteiskunnan ja ympäristön välisiä alueellisia ja ajallista vuorovaikutussuhteita eri mittakaavatasoilla paikallisesta globaaliin.

Green Paths routing tool encourages healthy and active travelling

Authors: Age Poom, Joose Helle, Tuuli Toivonen

The new Green Paths routing tool helps pedestrians and cyclists to choose urban commuting routes with less air and noise pollution. The tool is a proof of concept of exposure-optimised routing. It functions in the Helsinki capital region where the necessary environmental data is available.

This novel routing tool suggests a set of routes to the user-defined destination that are less polluted than the shortest, often busy main road. This is different from the traditional routing concept that considers only distance or travel time for route choices.

The users of the Green Paths routing tool can follow their own preferences in making the final route choice that is quieter, has fresher air and feels more pleasant. As such, the user becomes an active decision-maker, empowered to choose the most appealing route with only a modest increase in travel time. The new Green Paths routing tool indeed aims to improve travel satisfaction. A pleasant travel experience makes commuters more likely to walk or cycle regularly. In this way, commuters using the Green Paths tool contribute to a more sustainable city with cleaner air.

Green Paths routing tool
Examples of the user interface of the Green Paths routing tool for air and noise pollution optimised cycling and walking routes in the Helsinki capital region.

The Green Paths routing tool leans on the concept of travel-time environmental exposure assessment. It optimises route choice based on both environmental exposure and trip duration, separately for air pollution and noise. For that, it deploys open-source environmental data. The tool applies real-time and spatially explicit air quality information from the ENFUSER modelling system that is being developed by the Finnish Meteorological Institute. In particular, Green Paths tool utilises Air Quality Index, which reflects the state of air pollution in the Helsinki capital region on an hourly level. For noise data, the tool applies average noise levels from road, rail and air traffic. The modelled data is provided by the Finnish Environmental Institute and local municipalities. Data for the underlying street and path network originates from OpenStreetMap, which is a collaborative open-source geodata project. The user can change the underlying map style by choosing either the street network or satellite image display option.

To ensure transparency and support the advancement of related methods and tools, the Green Paths routing tool is an open-source development (check the repositories in GitHub). The platform provides also an API that enables the export of environmentally optimised routing results to other applications. By providing the open code, the team encourages other developers to consider environmental cost factors in their active travel-oriented applications.

As an end-user application, Green Paths routing tool is publicly available via a mobile-friendly website https://green-paths.web.app/, in both Finnish and English. The user can pre-check suitable routes from a computer or then navigate in real travel situations with the help of a smartphone interface. To grant a smooth daily use, the user can add the browser link of the tool to his/her smartphone home screen that enables the use of the tool similarly to any other smartphone application. All users are encouraged to give feedback on the usability of the tool via a link found in the information modal of the tool.

For now, the Green Paths tool is developed as a proof of concept with advancements of the features and functionalities in time. It should be considered as a demonstration of exposure-optimised routing based on spatially explicit and advancing open access data sets, and it is not guaranteed to work smoothly at all times. In the future, the tool will incorporate routing based on green views the users experience in the travel environment. The works in progress involve, among others, showing street-level maps on air and noise pollution.

Green Paths tool: street level noise
The Green Paths tool shows average traffic noise levels in the street network.

Start using the Green Path tool on your next trip in Helsinki region! More information about the tool is available at https://www.helsinki.fi/en/researchgroups/digital-geography-lab/green-paths.

The software and user interface is developed by Joose Helle. The Green Paths team involves Joose Helle, Age Poom, Tuomas Väisänen and Tuuli Toivonen from the Digital Geography Lab of the University of Helsinki. The tool is developed within the framework of the Urban Innovation Action HOPE – Healthy Outdoor Premises for Everyone, and is co-financed by the European Regional Development Fund. UIA HOPE aims to produce more comprehensive air quality monitoring network that gives citizens air quality information on places where they live and they travel in the city. UIA HOPE project is led by the Economic Development Division of the City of Helsinki.

Digital Geography Lab at the University of Helsinki is an interdisciplinary research team focusing on spatial big data analytics for fair and sustainable societies. The group aims to understand spatial interactions between people, and between people and their environment, from local to global scales.

COVID-19 is spatial: Ensuring that mobile Big Data is used for social good

Authors: Age Poom, Olle Järv, Matthew Zook and Tuuli Toivonen

We have just published our commentary regarding human mobility, mobile Big Data and the responses to COVID-19 pandemic in the Big Data & Society journal (see also the journal’s blog).

This commentary was motivated by our previous experience with mobile Big Data and recent work on changed human mobility derived from mobile phone data during the COVID-19 outbreak in Finland (e.g. Järv et al. 2020a; Järv etal. 2020b). It also draws from the knowledge and experiences of our peers around the globe.

In short, the mobility restrictions related to COVID-19 pandemic have resulted in the biggest disruption to individual mobilities in modern times. The crisis is clearly spatial in nature, and examining the geographical aspect is important in understanding the broad implications of the pandemic. We can benefit from the avalanche of mobile Big Data that makes it possible to study the spatial effects of the crisis with spatiotemporal detail at the national and global scales. Yet, the current crisis also highlights serious limitations in the readiness to take the advantage of mobile Big Data for social good, at large, regarding technological, administrative and legislative aspects.

Drawing on the Finnish and Estonian experiences, and the practices of global platform companies (e.g. Google) during the early phases of COVID-19 pandemic, we argue that we need to re-evaluate the public-private relationships with mobile Big Data and propose two strategic pathways forward.

First, we call for transparent and sound mobile Big Data products that provide relevant up-to-date longitudinal data on the mobility patterns of dynamic populations.

Second, there is also a need to develop trustworthy platforms for collaborative use of raw individual-level data. Secured and privacy-respectful access to near real-time raw data is needed for developing and testing sound methodologies for the above-mentioned data products. This would help to bridge the Big Data digital divide, enable scientific innovation, and offer necessary flexibility in responding to unanticipated questions on changing locations and mobilities in the case of crises. To be clear, we do not view this as simple to achieve, particularly as we weigh what kind of institution might best fill this role without jeopardizing personal privacy and democracy, or how is “social good” defined and operationalized in practice. However, addressing these issues via public debates and academic discourses will leave us better prepared for the next crisis.

To conclude:

  • We need harmonized and representative data about human mobility for better crisis preparedness and social good in general;
  • Methodological transparency about mobile Big Data products are vital for open societies and capacity building;
  • Access to mobile Big Data to develop feasible methodologies and baseline knowledge for public decision-making is needed before the next crisis occurs;
  • Recognizing the fundamental spatiality of the current COVID-19 crisis and crises more generally is the most relevant of all.

Digital Geography Lab is an interdisciplinary research team focusing on spatial Big Data analytics for fair and sustainable societies. We aim to understand spatial interactions between people, and between people and their environment, from local to global scales.

Mobility research in areas with seasonal population changes

In the end of 2019, SYKE, the Finnish Environmental Institute, arranged a miniseminar on mobility research in urban, rural and touristic settings. The seminar addressed mobility research interrelations with spatial planning and governance, stakeholder engagement in spatial and transportation planning, sustainable mobility challenges in remote and touristic settings, and various methods for acquiring, processing and analysing mobility data.

The seminar was held in Helsinki and was part of the InterReg Baltic Sea-funded project MARA. The overall aim of the project is to address mobility and accessibility challenges in rural areas. Project activities and the perspectives and challenges of various mobility data were presented in the seminar by Kari Oinonen (SYKE), Age Poom (Digital Geography Lab, University of Helsinki & Mobility Lab, University of Tartu), Daniel Brandt and Tobias Heldt (both from CeTLeR, Dalarna University). SYKE researchers introduced their studies on GIS use in urban and rural planning (Ville Helminen), rural mobility, accessibility and travel related to second homes (Antti Rehunen), public participatory GIS (Elina Nyberg) and the architecture of spatial data infrastructure in SYKE (Kaisu Harju).

Spatial planning and governance require data on people’s mobility for smart decision-making: on local and regional, daily and seasonal, regular and irregular spatial behaviour. Countries that conduct national travel surveys collect data on regular travel patterns of local residents. This information is very powerful for addressing a number of goals, as also demonstrated by Antti Rehunen, SYKE, in the seminar. However, it tends to uncover travel that takes place occasionally, such as seasonal leisure travel. Remote touristic areas may face temporary population flows that reach the magnitude of a mid-sized city in spatial conditions that have not been optimised for serving such an amount of people smoothly and sustainably.

Several remote touristic areas such as Nordic ski resorts are facing the above-mentioned problem. Within MARA project, they find out ways how to gain more meaningful data on mobility needs as well as on current mobility patterns in their region. The project also looks into the question on how to better manage local temporary travel flows. This involves both transportation as well as service infrastructure covering the full mobility behaviour of tourists, for example accessibility to cultural and natural amenities, sport facilities, accommodation, dining facilities or stores.

Currently, most regions lack explicit information on domestic and foreign tourist flows and their detailed mobility within the destination region. Apart from official statistics from accommodation service providers, traveller counts in local airports or data on ticket sales from touristic hotspots, questionnaires have been a convenient approach to address the mobility or activity of tourists in a region (Heldt and Mortazavi 2016). Spatiotemporally more explicit method is arranging GPS-supported tourist tracking campaigns during their stay in the region (Shoval and Ahas 2016). As GPS campaigns may be costly and require large managerial effort, other geocoded data collection methods such as use of destination card (Zoltan and McKercher 2015) or public participatory GIS (Kantola et al. 2018; Salonen et al. 2018) are used in tourism studies. The latter method was also applied in the MARA project within the Kymeenlaakso regional survey of non-resident population (Vierikko et al. 2019). Subject to the survey design, the above-mentioned methods may reveal individual activity locations and times, mobility chains and travel modes, as well as semantic meaning and reasons behind individual mobility decisions. At the same time, a drawback with these methods is that they cover either rather small number of volunteering visitors or involve sample biases due to sample management and enrolment issues.

To cover larger population flows in the region, other digital mobility data sources would be handy. There is an increasing body of studies applying social media (Toivonen et al. 2019) or mobile phone data (Ahas et al. 2014) in tourism related research. Passive mobile phone data has proven to be a rich data source for analysing the spatiotemporal behaviour of large anonymous population groups. The University of Tartu has extensive experience in applying mobile phone data also in tourism studies (Ahas et al. 2007; Nilbe et al. 2014; Raun et al., 2016; Saluveer et al. forthcoming). In the seminar, Age Poom gave insights to mobile phone based research conducted in Estonia. The MARA project involves development of a Population Mobility Monitor that among other data sources applies mobile phone data to visualise regional population flows.

There are many regulatory and operational issues to be solved before passive mobile phone data can be used in research, for example to secure privacy protection of individual subscribers who serve as anonymous data providers. As mobile phone data becomes more and more accessible elsewhere, including Sweden (Östh et al. 2016) and Finland (Bergroth 2018), there are strong perspectives of using it also in the mobility management of remote touristic areas.

Disclosure: The blog post is adjusted based on the original post published on the MARA project website.

References:

Ahas, R., Aasa, A., Mark, Ü., Pae, T., Kull, A. 2007. Seasonal tourism spaces in Estonia: Case study with mobile positioning data. Tourism Management, 28(3), 898–910. https://doi.org/10.1016/j.tourman.2006.05.010

Ahas, R., Armoogum, J., Esko, S., Ilves, M., Karus, E., Madre, J.-L., Nurmi, O., Potier, F., Schmücker, D., Sonntag, U., Tiru, M. 2014. Feasibility Study on the Use of Mobile Positioning Data for Tourism Statistics Report 3a. Feasibility of Use: Methodological Issues. https://ec.europa.eu/eurostat/documents/747990/6225717/MP-Consolidated-report.pdf

Bergroth, C. 2018. The 24-h population dynamics of the Finnish Capital Region uncovered! https://blogs.helsinki.fi/accessibility/2018/10/09/the-24-h-population-dynamics-of-the-finnish-capital-region-uncovered/

Heldt, T., Mortazavi, R. 2016. Estimating and comparing demand for a music event using stated choice and actual visitor behaviour data. Scandinavian Journal of Hospitality and Tourism, 16(2), 130–142. https://doi.org/10.1080/15022250.2015.1117986

Kantola, S., Uusitalo, M., Nivala, V., Tuulentie, S. 2018. Tourism resort users’ participation in planning: Testing the public participation geographic information system method in Levi, Finnish Lapland. Tourism Management Perspectives, 27, 22–32. https://doi.org/10.1016/j.tmp.2018.04.001

Nilbe, K., Ahas, R., Silm, S. 2014. Evaluating the Travel Distances of Events Visitors and Regular Visitors Using Mobile Positioning Data: The Case of Estonia. Journal of Urban Technology, 21(2), 91–107. https://doi.org/10.1080/10630732.2014.888218

Östh, J., Reggiani, A., Schintler, L. 2016. Resilience in Spatial and Urban Systems 2. Presentation at Advanced Brainstorm Carrefour (ABC): ‘Smart People in Smart Cities’ Matej Bel University, Banská Bystrica, Slovakia (August, 2016). https://www.slideshare.net/regionalscienceacademy/resilience-in-spatial-and-urban-systems-2

Raun, J., Ahas, R., Tiru, M. 2016. Measuring tourism destinations using mobile tracking data. Tourism Management, 57, 202–212. https://doi.org/10.1016/j.tourman.2016.06.006

Salonen, M., Broberg, A., Kyttä, M., Toivonen, T. 2014. Do suburban residents prefer the fastest or low-carbon travel modes? Combining public participation GIS and multimodal travel time analysis for daily mobility research. Applied Geography, 53, 438–448. https://doi.org/10.1016/j.apgeog.2014.06.028

Saluveer, E., Raun, J., Tiru, M., Altin, L., Kroon, J., Snitsarenko, T., Aasa, A., Silm, S. n.d. Methodological framework for producing national tourism statistics from mobile positioning data. Annals of Tourism Research.

Shoval, N., Ahas, R. 2016. The use of tracking technologies in tourism research: the first decade. Tourism Geographies, 18(5), 587–606. https://doi.org/10.1080/14616688.2016.1214977

Toivonen, T., Heikinheimo, V., Fink, C., Hausmann, A., Hiippala, T., Järv, O., Tenkanen, H., Di Minin, E. 2019. Social Media Data for Conservation Science: a Methodological Overview. Biological Conservation, 233(January), 1–18. https://doi.org/10.1016/j.biocon.2019.01.023

Zoltan, J., McKercher, B. 2015. Analysing intra-destination movements and activity participation of tourists through destination card consumption. Tourism Geographies, 17(1), 19–35. https://doi.org/10.1080/14616688.2014.927523