New paper out! Environmental exposure during travel: A research review and suggestions forward

Age Poom, Elias Willberg, Tuuli Toivonen

Our seminal research review paper on environmental exposures during travel is now published in the journal Health & Place! https://doi.org/10.1016/j.healthplace.2021.102584 

Urban travel environments exposure people to a range of environmental conditions, such as traffic noise, air pollution or street-level greenery. These exposures may cause both positive and negative health and wellbeing consequences. Knowledge of the dynamics of environmental exposures during travel, and their social and health outcomes would help improve the liveability and sustainability of our cities through evidence-based transport and urban planning.

We conducted a systematic review of the scholarly literature on environmental exposure during travel. We aimed to understand the state of the art of the research field and identify areas for further studies. We identified 104 relevant peer-reviewed journal articles worldwide. The research field is clearly emerging with increasing number of studies published each year. The distribution of the study areas indicates a global bias in the research field towards western cities, where the research tradition is longer. However, last years have witnessed a rapid increase in the number of studies conducted in China and India. A good global coverage of research supports local planning and governance, and better mitigates the risk of environmental health disparities in all parts of the world.

The number of studies published globally in different year ranges (A), and the spatial distribution of studies in different world regions using the same year ranges for the bars (B). The locations of individual study sites are indicated as points on the map (B). Source: Poom et al. 2021

The review showed that the key methodological challenge of the research field is the spatiotemporal coupling of travel and environmental data. Different travel modes, routes, and times expose people to different environmental conditions. The research field has strongly benefitted from the emerging location-aware sensor technology to capture the dynamics of both travel behaviour as well as environmental conditions. The future research could take the advantage of mobile Big Data to examine travel-related exposure also at the scale of populations.

Environmental exposure during travel is an interplay between people, their travel behaviour, and the surrounding travel environment. Understanding environmental exposures during travel calls for spatially and temporally detailed data on all aspects, on human scale. Source: Poom et al. 2021

The review gave evidence that most of the travel-related exposure research focuses on air pollution. Exposure to other environmental conditions, such as traffic noise or street-level greenery, has received only little scholarly attention. Even less is known about the patterns of multiple and cumulative environmental exposures during travel. More research attention is needed on the associations between travel behaviour, multiple environmental exposures, and resulting health and wellbeing effects. The future research should aim to develop shared and standardised study protocols as well as provide open data sets to make travel-related exposure studies comparable and draw conclusions of health and wellbeing effects through dedicated meta-analyses.

We conclude that there is a need to overcome disciplinary silos and integrate the expertise of exposure and health researchers, environmental scientists, transport and geospatial researchers, and sustainability and welfare scholars to advance the research field. Scholarly emphasis on good travel environments on human scale can advance the designing of just and sustainable cities.

Full reference of the article:

Poom, A., Willberg, E., Toivonen, T. (2021). Environmental exposure during travel: A research review and suggestions forward. Health & Place 70, 102584, https://doi.org/10.1016/j.healthplace.2021.102584.

The Digital Geography Lab at the University of Helsinki is an interdisciplinary research team focusing on spatial Big Data analytics for fair and sustainable societies.

Warm reflections from the course GEOG-326 on accessibility and human mobility research

Time flies – the course “GEOG-326 Quantitative methods for sustainable land use planning I: Accessibility & mobility analyses“, given by the researchers of the Digital Geography Lab, ended already before Christmas 2020. Yet it’s worthwhile to reflect on it!

It is heart-warming to go through the positive feedback from students regarding the course structure and balance between theory and practice, and constructive suggestions for improving the course.

The course aimed at linking the accessibility and mobility of people to sustainability, well-being and social (in)equality perspectives, exploring the potential of big data analysis approach, and studying the ways of implementing these in planning. We also focused on the impact of global crises on human mobility on the example of COVID-19.

Overall, all 35 students did a great job and received high grades, but most importantly, it was rewarding to see students getting motivated and inspired, and developing their skills and ideas during the course.

The final output of the course was an independent group work that was presented in the form of an academic poster. Me, Elias and Tuuli found the final poster presentation session excellent! Thus, we are delighted to share the posters here 🙂

Check out and get inspired!

 

GROUP 1: The change in mobility flows during the first COVID-19 restrictions: A case study for Helsinki (and the sub-region)

 Alisa Redding, Sanja-Riia Collin, Venla Salomaa

 

GROUP 2: Bike-sharing System Support for Public Transportation – studying the temporal aspects of shared bicycle trips in 2019

Emil Ehnström, Olivia Halme, Iivari Laaksonen & Tao Jiaxin

 

GROUP 3: Accessibility and spatial coverage of the bike-sharing systems in the Helsinki Metropolitan Area

Håvard Aagesen, Hanna Hirvonen, Miika Kastarinen, Jussi Torkko

 

GROUP 4: Bike sharing in Finland: A comparison of HSL and Föli city bikes ridership from 2018 2020

Emily Dovydaitis, Kia Kautonen, Matti Moisala, Juho Noro

 

GROUP 5: Impact of COVID-19 on dockless mobility in Austin, Texas

Benedikt Kohl, Tatu Leppämäki, Anna Levlin & Mathew Page

 

GROUP 7: Comparison of bike-sharing data in Helsinki and Espoo from 2019 and 2020 in relation to Covid-19

Matti Hästbacka, Jouko Lappalainen, Klara Lappalainen, Sarah Seidel

 

GROUP 8: Effects of COVID-19 on city bike usage

Emma Piela, Eero Perola, Antti Miettinen & Isaline Coquard

 

GROUP 9: Automating travel time matrix data preprocessing

Hanna Haurinen, Saku Saarimaa, Ekku Keurulainen, Jeanne Leroux

 

GROUP 10: Green Accessibility Index’ in dominant travel areas zonified by transportation mode in the Finnish Capital Region

Bryan Vallejo, Lauri Ovaska, Elli-Nora Kaarto & Miro Mujunen

Etsimme tutkijatohtoria tai tohtorikoulutettavaa!

Briefly in English: We are sharing an announcement for a post-doc/PhD student position at Digital Geography Lab and Ruralia Institute. The position benefits from the knowledge of Finnish language and hence is published in Finnish only.

Ja sitten suomeksi:

Kiinnostaako monipaikkaisuus, aluekehitys ja ihmisten liikkuvuus? Haluaisitko tietää, miten erilaisten digitaalisten aineistojen avulla voi monipaikkaisuutta tarkastella tai miten COVID-19 pandemia on vaikuttanut kakkosasuntojen käyttöä Suomessa?

Ruralia-instituutti ja Digital Geography Lab yhteiistyössä hakee tutkijatohtoria/tohtorikoulutettavaa hankkeeseen ”Monipaikkaisen asumisen rytmit”.

Tehtävät käsittävät digitaalisten massa-aineistojen (mm. rakennusten sähkönkäytön, matkapuhelinverkon ja Twitter aineistoja) hallinnointia, prosessointia ja analysointia. Hakijalta edellytetään riittäviä geoinformatiikan taitoja analyysien tekoon, massa-aineistojen käsittelyyn vaativaa osaamista (Python, R, PostgreSQL) ja tilastollista osaamista. Suurteholaskennan kokemus katsotaan eduksi.

Tarkemmat hakuohjeet löytyvät täältä.

Hakuaika päättyy 22.3.2021, ole nopea!

Lisätietoja saa: akatemiatutkija Olle Järv olle.jarv(at)helsinki.fi ja professori Tuuli Toivonen, tuuli.toivonen(at)helsinki.fi

Two new papers out on cycling!

We have published two new articles on cycling! 

What do trip data reveal about bike-sharing system users‘ was published in Journal of Transport Geography.

Highlights:

    • As cities strive to foster cycling, bike-sharing systems (BSS) have become increasingly common.
    • We used bike-sharing trip data from Helsinki and looked at user profiles and usage patterns. We also focused on the possibilities of BSS trip data.
    • The bike-sharing system in Helsinki has been actively used even in international comparison, but our results point toward challenges in BSS inclusivity in Helsinki in 2017. Most use was contributed by a limited group of ‘super-users’.
    • BSS trip data provides opportunities to understanding BSS user profiles & patterns. By being well available, unlike many other cycling data sources, and automatically collected, trip data can save resources, facilitates longitudinal research and reveals observed behaviour.

Willberg E., Salonen M., Toivonen T. (2021). What do trip data reveal about bike-sharing system users? Journal of Transport Geography. https://www.sciencedirect.com/science/article/pii/S0966692321000247

 

Comparing spatial data sources for cycling studies – a review will be published officially later this year in the NECTAR book ‘Transport in Human Scale Cities’, but we have made it available as a postprint already now.

Highlights:

    • We reviewed various spatial data sources on cycling
    • We built upon the expertise of a broad group of cycling experts and collected their views on the strengths, weaknesses and usability of the data sources.
    • With several reviewed data sources, having data is still a key challenge including difficulties in data collection, lack of suitable data and poor accessibility to it,
    • Data availability could be improved by increased data sharing by planning agencies and researchers. Development of data products to improve access to the data collected by private companies is also needed. However, this development must be carried our responsibly protecting users’ privacy.

Willberg, E., Tenkanen, H., Poom, A., Salonen, M., & Toivonen, T. (2021). Comparing spatial data sources for cycling studies – a review. SocArXiv https://doi.org/10.31235/osf.io/ruy3j

 

Here’s the press release on the articles:

Spatial  data for understanding urban cycling

Cities strive to increase their cycling levels and constantly more information is being collected on cycling. Two recent studies by the Digital Geography Lab group reveal what novel big data tell us about city bike users, for example, and how the availability of information collected about cycling remains a major challenge.

The popularity of cycling is growing, especially in urban areas. Also, as a result of the COVID-19 crisis,  many have switched to cycling. Cycling is one of the ways to promote sustainable mobility in cities. Bike-sharing systems have become one of the most visible measures to promote cycling in Finnish cities, and the reception of the systems has often been enthusiastic. Bike-sharing systems also provide a novel information about cycling.

The Digital Geography Lab group has studied cycling with novel big data. A recently published article considers the possibilities of bike-sharing trip data in cycling research. The information is used to analyze the spatial and temporal usage patterns of the Helsinki bike-sharing system in addition to understanding user characteristics and inclusivity of the system.

Demographics of BSS users (a) and BSS trips (c) compared to the Helsinki population. Bar charts show the comparison in regard to users’ home area (b) and users’ subscription type (d)

Young adult city dwellers are large consumers of urban bikes

“Helsinki bike-sharing system has been popular based on use activity. But in the scientific discussion, bike-sharing systems are often criticized for mainly serving only certain groups of people, ”says doctoral researcher Elias Willberg.

“This criticism made us interested in looking at users of the Helsinki system,” he continues. The aim for the research is to bring new perspectives to the practical design and management of bike-sharing systems in cities.

The study found that despite the high use, the user population in the early years of the bike-sharing system was strongly focused on young adults living within the system area. The survey was conducted with data from 2017, when the system still collected basic data variables on registered users. The study also showed the potential of bike-sharing trip data in understanding user needs and habits of various users.

“It is important to pay attention that bike-sharing systems would serve the widest possible range of different areas and groups of people, so that the systems can effectively support sustainable urban mobility. Data from shared bikes provide useful information for these needs, ”Willberg says.

On weekdays, most cyclists are on the move in the morning and afternoon. On weekends, people cycle less than on weekdays and go cycling throughout the day.

Various sensors and portable devices provide information about cycling to researchers

Another newly completed scientific article by our group involved cycling experts from across Europe and gathered information on the benefits and challenges of various data sources on cycling. The article will be published in the book “Transport in Human Scale Cities”  in the autumn, but it is already available online. “Various sensors and portable devices such as mobile phone apps and sports watches are increasingly storing information also about cyclists. A diverse use of various data sources is essential for holistic understanding of cycling, ”says Tuuli Toivonen, Professor of Geoinformatics, who led the research.

The main message of the study is that the availability of data remains a major bottleneck in cycling research and knowledge-based design. Novel data sources provide tools for understanding cycling and answer questions such as where and when people cycle in urban areas. But they are not a panacea. Automatically collected data from various systems do not provide much for understanding causes of cycling, for example. Such data may also be skewed on active users. In this case, they do not necessarily represent the entire population.

“There is still a lot of work to be done in improving the availability and transparency of cycling data,” Toivonen says. “Despite the great need, access to data must be promoted responsibly, taking into account privacy issues,” she concludes.

Suitability of cycling data sources to various types of questions

WE ARE RECRUITING! Doctoral student with an interest in Big Data analytics, human mobility & social interaction

Are you interested in geoinformatics, big data and social media analytics? Are you curious about the phenomena of human mobility, cross-border mobilities and social interactions of people and transnational people? If yes, check this open four-year doctoral student position at the Digital Geography Lab starting from March 2021 or as agreed with the selected applicant!

We are looking for an enthusiastic, innovative, and highly motivated doctoral student with strong technical knowledge and skills to join our interdisciplinary research group Digital Geography Lab and work in the Academy of Finland-funded project BORDERSPACE – Tracing Interactions and Mobilities Beyond State Borders: Towards New Transnational Spaces.

The doctoral project has three objectives. First, to develop methodologies for quantifying human mobility and activity spaces across country borders based on social media data (Twitter). Second, to develop quantitative methodologies for uncovering activity practices of social media users and their feeling of belonging based on the content of their social media posts. Third, to conduct critical research on dynamic cross-border mobility flows derived from big data, integration of transnational people through their cross-border mobilities and social interactions, and how these are influenced by external factors such as the COVID-19 pandemic.

The successful applicant is expected to have strong fluency in programming (Python or R), experience in advanced spatial analytics and/or social media content analysis, and has worked with big data sources such as mobile phone, smart card and social media data. Prior experience in publishing research in academic journals, participating in research community and having a network of international scholars is an asset.

Read more about the position announcement and apply HERE. The deadline is January 31st 2021.

For further information, please contact Academy Research Fellow Olle Järv, olle.jarv(at)helsinki.fi.

Vuokko’s lectio 9.12.2020

User-generated Geographic Information for Understanding Human Activities in Nature

Lectio Praecursoria, in the public examination of MSc Vuokko Heikinheimo’s doctoral dissertation
the 9th of December 2020

 

Nature contributes to human well-being in countless ways. Many of us enjoy spending time in nature, going for a walk or a picnic and observing species and seasons. Nature-based tourism and outdoor recreation are evident examples of direct benefits of nature to people.

National parks are protected areas that are dedicated to safeguarding biodiversity and providing people the opportunity to enjoy nature.

Urban green spaces include the network of parks, forests and other green areas in the urban structure. Green spaces in cities offer opportunities for contact to nature in our everyday lives while protecting urban biodiversity.

We are also willing to travel far in order to experience and enjoy nature. In many places, visitors of protected areas – both domestic and international – are a significant source of income for park management and local communities. Information about protected area visitors is important for planning and management on regional, national and international scales.

The ongoing pandemic has emphasized the importance of access to green spaces in everyday life.

In Finland and many other countries, national parks and green spaces are attracting record numbers of visitors. However, in many regions, visiting green spaces has become more restricted due to regulations, and international travel has decreased dramatically – at least for now – having an impact on global nature-based tourism.

The global protected area network on land and sea is a key instrument in conserving biological diversity and ecosystem services on Earth. Despite active efforts to protect the global environment, human activities continue to cause significant declines in nature. Understanding how nature contributes to people’s well-being is a key aspect for finding successful solutions that support the protection of biodiversity and sustainable and equitable land-use planning.

In order to understand the interactions between people and the environment on different scales, we need data.

Remote sensing data such as satellite images have revolutionized the collection of data about the natural and built environment.

But how about data on human activities?

Information about visits to protected areas can be collected, for example, using surveys and on-site counters. However, gaps remain even in places with the most advanced visitor monitoring systems and some regions lack such data completely.

More recently, data generated through the interactions of people and location-based technologies (such as mobile phones and GPS-devices) have provided new opportunities for analyzing human activities all around the world. For example, many of us share our observations, activities and even location publicly online through various social media applications. These user-generated data offer new opportunities for understanding spatial and temporal patterns of human activities.

Elements of location-based data, such as geotags, timestamps, text, and images provide new possibilities for studying human activities in nature and can help filling some of the information gaps in this field.

This thesis links to a broader context of understanding human-nature interactions. From a holistic perspective, social and ecological systems are interlinked in complex systems. This thesis zooms into the human side of the system by looking into human activities – human spatial behavior in nature.

Social media, and other user-generated data sources provide information first and foremost about people and their observations and activities. These data can also provide information about the natural environment such as species observations and land cover information. In my thesis, I have mainly focused on people’s movements, activities and values represented in the data.

In this work, I investigated how well user-generated data reflect actual visits to nature. Digital data, in general, provide various perspectives about human-nature interactions beyond actual visits.

By definition, social media are channels for interaction and discussions in addition to platforms for sharing content. It is possible to raise awareness and to show interest in particular regions or animal species online without actually visiting nature.

In my thesis, I focus mostly on those digital data that are potentially linked to actual visits through geotags or other references to location. For example, it is relevant to ask that if someone has geotagged a photograph into a national park, did they actually visit the place?

As a concept, User-generated geographic information refers to data created through interactions of people and location-based technologies. Examples of such data include geotagged social media posts, GPS-tracks from sports applications, mobile network data and other location-based data generated by regular people instead of government authorities or experts.

In the geographic information science literature, the concept of volunteered geographic information and the idea of citizens as censors – introduced by Goodchild in 2007 is often used to refer to geographic data generated by non-professionals.

It is a good concept when describing actively contributed data sets, such as OpenStreetMap which is an open source world map that anyone can edit, or data contributed to citizen science campaigns and applications such as the iNaturalists where everyone can share their nature observations and comment on others’ observations.

However, I would argue that the concept of volunteered data does not perfectly capture all kinds of user-generated data sets.

For example, when analyzing publicly shared content on social media, or data from mobile network operators we are using these data to other purposes than originally intended. From a research point of view, it is important to acknowledge that these data might not be actively volunteered for such purposes. The same applies to new data sets about human mobility that big technology companies have recently released to support analysis related to the COVID-19 pandemic.

In this doctoral dissertation, I have investigated the use of user-generated data sets for studying human-nature interactions. I focused on human activities and preferences in national parks and urban green spaces. Main objectives were to

    1. Describe and critically evaluate the available data sources and to
    2. Discover spatial and temporal patterns of human activities in nature in the study areas.

To achieve these objectives, I investigated the elements of the user-generated data through these questions:

    • Where and when are people visiting national parks and green spaces?
    • What are people doing and valuing in nature? and perhaps why people visit specific places?
    • Who are the users who have shared their data from these areas?

This thesis consists of four articles and a summary section. The first three articles focus on social media data, and the fourth article also includes other sources of user-generated data.

    •  In Aricle I, I reviewed recent scientific literature using social media data in nature conservation research. The article provides an overview of relevant data sources and analysis methods that could further contribute to using social media data in conservation science.
    •  In Article II, I compared social media data and visitor survey data from Pallas-Yllästunturi National Park. We observed similar trends in both data sources regarding popular activities and visited locations.
    •  Article III focused on understanding who the users are. I compared several methods for identifying countries of residence of visitors to the Kruger National Park in South Africa, and evaluated the performance of these methods.
    • Article IV compares social media data, sports application data, mobile phone data and participatory geographic information for investigating the use of urban green spaces.

Extracting meaningful information from user-generated data sets is an iterative process.

In this thesis, I used spatial and temporal analysis methods and visual and textual content analysis approaches in addition to thorough data exploration.
During the analysis workflow, there are several important questions to consider, such as:

    •  Which data sources are best fit for the purpose?
    • What data to collect and store?
    • Does the data contain personal and sensitive information?
    • How to identify irrelevant data?
    • What type of analysis approaches, tools and skills are needed?
    • How to best visualize the results?
    • Can the observed patterns be validated?

So, where and when are people visiting national parks and green spaces? and how can we analyze these patterns based on user-generated data?

    • Results in my thesis show that visitor flows and hot-spots are visible in social media and other user-generated data sets on different scales.
    • These data work best in popular destinations and lack of data does not necessarily mean the absence of visitors.
    • The investigated data sets contains unique information about temporal trends of human activities. For example, these data can fill information gaps in between less frequent surveys.
    • Aggregating data over space and time not only preserves privacy but also often reveals regional and periodical trends even if the original data would be sporadic. For example, relative changes in posting activity can reveal interesting and even surprising patterns.

Content analysis of social media texts and images allows understanding activities and preferences from a new perspective.

    • Manual content analysis in this thesis found that most content shared from national parks and green spaces contained relevant information.
    • Activities detected from social media content reflected surveyed activities
    • This thesis also emphasizes the potential of automated content analysis approaches for acquiring further insights from large quantities of textual and visual content.

Finally, understanding who have shared their data from national parks and green spaces is important but challenging.

    • In this work, I identified approaches for deriving information about the users through further spatial and temporal analysis as well as content analysis.
    • For example, information about users’ places of residence can have a decisive importance for the meaningfulness of the entire analysis.
    • Data comparisons from national parks highlight that social media does not represent all visitor groups.

Main challenges related to using user-generated geographic information include data quality, limited access to data and privacy issues.

    • Limited access to data affects the repeatability of the analysis and the execution of longitudinal research projects.
    • Privacy issues cannot be neglected when analyzing data where individual people can be identified.
    • Minimizing the amount of data analyzed, and aggregating the results (for example, over time and to larger geographical units) helps using these data in a privacy-preserving way.

Overall, researchers, practitioners and decision-makers need to consider several limitations if aiming to extract meaningful information from user-genereated data sources.

Different sources of user-generated geographic data complement
each other in answering questions related to where, when, what, why and who.

In this thesis I propose that social media mostly captures being in nature covering leisure time activities, while sports tracking data and mobile phone data reflect moving through parks and green spaces (including daily commuting patterns and sports activities). Participatory geographic information (such as map-based surveys) can be used to acquire more in-depth information related to values and preferences.

Social media and other user-generated sources of geographic information are not able to fill in all information gaps related to understanding human activities in nature. However, if we understand the limitations of these data, they offer additional layers of geographic information to complement existing data sources and may inform further data collection efforts in less monitored areas.

The data used in this thesis represent time before the coronavirus pandemic, but the presented approaches and outlined limitations continue to be relevant for analyzing the ongoing changes in visits to national parks and green spaces.
This thesis contributes to understanding how to extract meaningful information about human activities in nature from the huge volumes of available data. User-generated data sets might be messy and unpredictable making their analysis challenging. At the same time, one of the strengths of these new data sources is the potential to discover emerging patterns and trends efficiently.

Even imperfect data, if understood as such, can contribute to integrating the value of nature into decision-making processes on different scales.

Data comparisons from national parks and green areas presented in this thesis provide insights about the properties of user-generated geographic information also to other fields of research.

Despite many limitations, there is a lot of potential to extract meaningful knowledge based on user-generated data sets for the benefit of people and the environment.


Vuokko Heikinheimo, MSc, defended her doctoral thesis entitled ‘User-Generated Geographic Information for Understanding Human Activities in Nature’ on 9 December 2020 at 10.00 at the Faculty of Science, University of Helsinki.

Professor Catherine Pickering from Griffith University, Australia, served as the opponent and Professor Tuuli Toivonen as the custos.

Vuokko completed her doctoral thesis in the Digital Geography Lab research group under the Social Media Data for Conservation Science project, which has received funding from the Kone Foundation.

PhD defence 2020
The Custos (Professor Tuuli Toivonen) and the Doctoral Candidate (MSc Vuokko Heikinheimo) in front of Athena building at Siltavuorenpenger on the 9th of December 2020.

 

Inaugural lecture by Professor Toivonen

Tuuli Toivonen is now a full professor in geoinformatics at the Faculty of Science!

Newly appointed  professors at the University of Helsinki are celebrated twice a year. As part of these celebrations, the professors hold an inaugural lecture.  This autumn, all festivities were (understandably) held online which allowed everyone interested to watch these lessons online.You can watch Tuuli’s lecture in here (Finnish audio, Finnish and English subtitles available):

Congrats once more to Tuuli!

Joelin lektio 27.11.2020

Alueiden suojeluarvottaminen kaupunki- ja maakuntatason maankäytön suunnittelun tueksi

FM Joel Jalkasen Lectio praecursoria -puhe 27.11.2020
Public defence of Joel Jalkanen's PhD thesis
The opponent (Professor Niina Käyhkö), the custos (Professor Tuuli Toivonen) and the doctoral candidate (MSc Joel Jalkanen) in Athena hall 107 on 27th of November 2020

Arvoisa kustos, arvoisa vastaväittäjä, hyvät kuulijat

Me ihmiset aiheutamme toimillamme paraikaa massasukupuuttoa, joka uhkaa suurta osaa maailman elämästä. Tällä hetkellä selkeästi suurin uhka maapallon lajistolle on se, että ihmiskuntamme tuhoaa elinympäristöjä omien tarpeidensa alta.

Eri lähteistä toistuva viesti on selkeä ja kiistaton: tapamme käyttää maata on kestämätön.

Kuvaamani ongelma kilpistyy hyvin oheiseen kuvaan. Luonto esiintyy paikassa, ja samoin ihmisten intressit esimerkiksi ruuantuotantoon tai kaupunkien rakentamiseen kohdistuvat usein paikkaan. Siellä, missä toinen haluaisi perustaa luonnon puolesta suojelualueen, näkee toinen hyvän paikan uudelle asuinalueelle.

Tätä ristiriitaa ratkotaan maankäytön suunnittelulla. Siinä sovitellaan erilaisia paikkoihin kohdistuvia tarpeita ja intressejä ja tarkastellaan, miten niitä voidaan saavuttaa rajallisen fyysisen tilan puitteissa.

Kaupunkiseuduilla tämä erilaisten tarpeiden ristiriitaisuus kilpistyy erityisen voimakkaasti, sillä kaupungit ovat rikkaita ja monimuotoisia niin luonnon, ihmisten käytön, virkistyksen ja sosiaalisten tarpeiden, kuin rakentamistarpeiden ja erilaisten taloudellisen toimeliaisuuden näkökulmasta.

On siis selvää, että maankäytön suunnittelu hyötyisi työkaluista, joilla edellä mainittuja ristiriitoja voisi ratkoa systemaattisesti ja analyyttisesti.

Parasta olisi, jos työkalut tuottaisivat selkeitä karttoja, jossa eri alueet olisi laitettu arvojärjestykseen, ja joita olisi suhteellisen helppo tulkita. Tästä tavoitteesta lähdin aikanaan tekemään väitöskirjaani.

Hyvin pian ymmärsin kuitenkin, että oleellista eivät ole nämä kartat vaan se, miten niihin päädytään. Väitöskirjassani pyrinkin selvittämään, miten alueiden suojeluarvottaminen voisi tukea ekologisesti kestävämpää ja vastuullisempaa maankäytön suunnittelua, erityisesti kaupungeissa.

Kuten väitöskirjani nimi vihjaa, hyödynnän työssäni alueiden suojeluarvottamista tai hieman anglistisemmin spatiaalista priorisointia. Se on systemaattisen luonnonsuojelusuunnittelun alaan sisältyvä tieteenala, joka yksinkertaistaen pyrkii vastaamaan kysymykseen: missä kannattaisi suojella luontoa?

Alueiden suojeluarvottamisessa on varsin laskennallinen ote, ja menetelmään on kehitetty erilaisia optimointiohjelmia. Alueiden suojeluarvottaminen on otettu parin viime vuosikymmenen aikana laajalti käyttöön luonnonsuojelusuunnittelussa ja sitä on hyödynnetty erilaisissa tapauksissa ympäri maailmaa. Menetelmä on kuitenkin ollut vähemmässä käytössä kaupunkialueilla ja yleisen maankäytön suunnittelun kontekstissa.

Suojeluarvottamisen laajempi prosessi sisältää aina tavalla tai toisella samanlaiset työvaiheet:

Aluksi pitää määrittää analyysin tavoitteet: mistä oikein ollaan kiinnostuneita? Onko arvotusanalyysin tavoitteena esimerkiksi tunnistaa tärkeimmät alueet uusiksi luonnonsuojelualueiksi vai löytää ekologisesti vähäpätöisimmät kohteet, joissa uusi rakentaminen heikentäisi luontoa vähiten?

Seuraavaksi tulee määrittää, mitkä asiat ovat tärkeitä juuri kyseisten tavoitteiden näkökulmasta. Keskitytäänkö lajeihin vai onko mielekästä huomioida myös luontotyypit? Keskitytäänkö vain luontoarvoihin vai tuleeko ihmisnäkökulma sisällyttää analyyseihin?

Seuraava työvaihe, yleensä työläin, on kartoittaa edellisessä vaiheessa tunnistetut tärkeät asiat. Missä paikoissa lajit esiintyvät, mitä viheralueita käytetään virkistykseen ja niin edelleen.

Kun alueellinen paikkatieto edellä mainituista tekijöistä on kerätty, voidaan eri alueet arvottaa keskenään laskennallisesti erilaisia paikkatietopohjaisia arvottamistyökaluja ja –ohjelmistoja hyödyntäen.

Lopuksi tulee tulosten tulkinta, johtopäätösten sekä suositusten tekeminen maankäytön suunnittelun kannalta.

Käytännössä alueellinen suojeluarvottaminen vaatii usein monipuolista yhteistyötä erilaisten asiantuntijoiden, sidosryhmien ja loppukäyttäjien kesken.

Väitöskirjassani hyödynsin alueiden suojeluarvottamista neljässä osatyössä tavoilla, jotka tuottavat maankäytön suunnittelua hyödyttävää tietoa eri näkökulmista:

Ensimmäisessä työssä tutkin, miten kaupunkiluonnon monimuotoisuutta kannattaa käsitellä suojeluarvottamisessa. Tapaustutkimukseni käsittää Suomen pääkaupunkiseudun.

Toisessa työssä tarkastelen samoja viheralueita ihmisnäkökulmasta, saavutettavuuden tasa-arvon kannalta.

Kolmas ja neljäs työni liittyvät Uudenmaan maakuntakaavoitukseen, jossa suojeluarvottamista hyödynnettiin kaavoituksen taustatietona.

Kolmannessa työssä käsitellään kokemuksia arvotusanalyyseistä yleisen maankäytön suunnittelun kontekstissa.

Neljännessä työssä käytin suojeluarvottamista laajojen ekologisten verkostojen ja yhteyksien tunnistamiseen maakuntakaavoituksen tueksi.

Olen käyttänyt kaikissa töissäni Zonation-tietokoneohjelmaa varsinaisiin laskennallisiin arvotusanalyyseihin.

Zonation on Helsingin yliopistossa kehitetty ohjelmisto, joka pyrkii arvottamaan alueita systemaattisesti ja kustannustehokkaasti muodostaen näin eräänlaisen synteesin luontoarvoista suuren paikkatietomäärän perusteella.

Zonation noudattaa komplementaarisuus- eli täydentävyysperiaatetta, eli sen tunnistamat arvokkaat alueet voivat turvata hieman eri asioita; lajeja, luontotyyppejä ja niin edelleen.

Yhdessä, toisiaan täydentäen, arvokkaimmat alueet turvaavat luonto- tai muita arvoja mahdollisimman kattavasti ja tehokkaasti.

Zonationin tulokset tulevat karttamuodossa. Zonation arvottaa aina kohdealueen liukuvasti nollasta ykköseen. Mitä lähempänä alueen arvo on ykköstä, vasemmanpuoleisessa kuvassa tummansinistä väriä, sen arvokkaampi alue on suojelun kannalta. Selkeyden vuoksi käytän samaa väriskaalaa kaikissa esitykseni kartoissa.

Kuvaa luetaan niin, että jos poliittisesti päätettäisiin, että vaikka 20% kohdealueesta suojellaan, niin tämän analyysin perusteella kyseiset 20% olisivat juuri nämä keskimmäisessä kuvassa näkyvät alueet, jotka suojelemalla turvattaisiin luontoarvoja kaikista eniten.

Zonation-karttoja tulee tulkita aina yhdessä niin sanottujen suoriutuvuuskäyrien kanssa, joiden avulla voi haarukoida, paljonko eri prioriteettitasot turvaavat luontoarvoja. Oikean kuvan kuvaajasta nähdään, että keskimmäisen kuvan mukaiset parhaan 20 prosentin alueet turvaavat noin 40% lajin a tunnetuista levinneisyysalueista, noin 35% lajin b levinneisyysalueista ja noin 5% lajin c levinneisyysalueista.

Zonationin avulla voidaan siis arvottaa koko kohdealue paremmuusjärjestykseen tavalla, joka on suhteellisen helppo tulkita maankäytön näkökulmasta. Esimerkiksi ensimmäisessä työssäni arvotin pääkaupunkiseudun viheralueet sen perusteella, miten ne tukevat kaupunkiluonnon monimuotoisuutta.

Kaupunkisuunnittelussa tulisi pyrkiä välttämään arvokkaimpia alueita ja suuntaamaan lisärakentaminen alueille, joiden luontoarvo on vähäisintä.
Tuloksia tulkitessa nähdään myös esimerkiksi, että kaupunkiluonnon monimuotoisuuden turvaaminen mahdollisimman kattavasti edellyttää erilaisten elinympäristöjen säästämistä. Paitsi vanhat metsät, myös erilaiset ihmisvaikutteisemmatkin ympäristöt, kuten merenrantaniityt tai kasvitieteelliset puutarhat, ovat tärkeitä kaupunkiluonnolle, sillä ne tukevat erilaista lajistoa täydentäen näin toisiaan kaupunkien viherrakenteessa.

Toisaalta tuloksia tulkitessa on yhtä tärkeää pitää mielessä se, mitä tulokset eivät kuvaa…

…sillä kun samoja viheralueita tarkastellaan ihmisnäkökulmasta, saavutettavuuden perusteella, aivan erilaiset alueet muodostuvat tärkeimmiksi.

Käytännön maankäytön suunnittelua tukevassa suojeluarvottamisessa korostuu riittävän ja kattavan luontotietopohjan kerääminen, tulosten tulkinta ja esitystapa sekä arvottamisen sisällyttäminen laajempaan, olemassaolevaan kaavoitus- ja päätöksentekoprosessiin.

Toisaalta ekologinen kytkeytyvyys eli se, miten elinympäristöt pidetään yhtenäisinä lajien elinmahdollisuuksien turvaamiseksi, on tärkeä kysymys maankäytön suunnittelussa. Kaavoituksessa asiaa käsitellään usein erilaisilla yhteystarvemerkinnöillä. Maankäytön suunnittelussa olisi kuitenkin tärkeää tunnistaa lisäksi laajat ja yhtenäiset elinympäristökokonaisuudet, joiden yhtenäisyys tulisi turvata.

Väitöstutkimukseni perusteella uskallan todeta, että alueiden suojeluarvottaminen voi tuottaa tietoa, joka hyödyttää ja edistää ekologisesti kestävää maankäytön suunnittelua, mutta se edellyttää analyysien tekijöiltä ja käyttäjiltä huolellisuutta ja osaamista.

Suojeluarvottaminen on tapa tunnistaa keinoja turvata luonto- ja muita arvoja kustannustehokkaasti maankäytön suunnittelussa. Eri alueiden ja arvojen tarkastelu systemaattisesti takaa parhaimmillaan suunnitteluun tasapuolisuutta ja avoimuutta – myös silloin, kun systemaattisen analyysin tuloksista halutaan syystä tai toisesta poiketa varsinaisissa maankäyttöpäätöksissä.

Priorisointi ei voi eikä yritäkään voida poistaa subjektiivisia valintoja ja arvoja, mutta se voi tehdä ne näkyvämmäksi. Analyysien yksityiskohtien suunnitteleminen, siis sen päättäminen ja sanoittaminen ääneen millaisia asioita analyysiin sisällytetään, miten eri tekijöitä painotetaan suhteessa toisiinsa ja niin edelleen on itsessään arvokasta suunnittelun ja päätöksenteon avoimuuden ja läpinäkyvyyden kannalta.

Koska maankäytön suunnittelu on luonteeltaan hyvin poliittista ja koskettaa hyvin monenlaisia intressejä, analyysien tulisi pyrkiä sisältämään monipuolisesti erilaisia näkökulmia – ja ainakin tulee olla avoin siitä, mitä kaikkea laskennalliset analyysit eivät sisällä. Tämä taas edellyttää sitä, että analyysit suunnitellaan ja tuloksia tulkitaan avoimesti ja läpinäkyvästi erilaisia sidosryhmiä osallistaen.
Suojeluarvottamisen voi siis nähdä toimivan alustana kestävälle maankäytön suunnittelulle ja katalyyttinä siihen liittyville keskusteluille.

Kun nämä asiat on saatu järjestettyä, suojeluarvottamisen avulla voidaan määrittää jokseenkin eksaktisti kolmenlaisia alueita, jotka yhdessä tukevat toisiaan kestävämmän maankäytön saavuttamisessa.

Ensinnäkin suojeluarvottamisen avulla voidaan tunnistaa uusia suojelualueita nykyiseen tapaan, joiden pääasiallinen tarkoitus on luonnon suojelu.
Toisaalta voidaan määrittää alueita, joissa ihmistoimintaa ja –käyttöä voidaan toteuttaa, kuitenkin säädellysti tavalla, joka turvaa myös paikallisia luontoarvoja.
Kolmanneksi on myös tärkeää tunnistaa alueita, jossa luontoarvoista ei tarvitse välittää, ja jonne luonnon kannalta haitallinen ihmistoiminta voidaan keskittää. Esimerkiksi kaupunkiseuduilla voitaisiin tunnistaa sopivimpia uusia rakentamisalueita, joissa yksittäisistä luontoarvoista ei tarvitsisi välttämättä välittää. Lähtökohtaisesti tällaiset alueet olisivat ekologisesti ja esimerkiksi virkistysarvon kannalta vähäpätöisimpiä alueita.

Kaikki tämä vaatii dataa luonto- ja muista arvoista.

Suojeluarvottaminen vaatii menetelmänä taustalleen paikkatietoa luonnosta, virkistyskäytöstä ynnä muusta, ja arvotusanalyysien tulokset ovat vain niin laadukkaita ja käyttökelpoisia kuin niiden tausta-aineistokin.

Suojeluarvotus ei siis voi, eikä se saa, korvata varsinaisia luontoinventointeja ja muun tiedon keräämistä luonnosta ja viheralueista.

Suojeluarvottamisen suurimpia rajoitteita on käytännön vaatimus siitä, että lähtöaineistojen tulisi kattaa koko kohdealue samalla tarkkuudella, mikä tuottaa haasteita ylikunnallisten, maakunnallisten, valtiollisten sekä toki kansainvälisten analyysien toteuttamiselle. Vetoan vahvasti päättäjiimme, jotta Suomessa saataisiin resurssit kerätä paljon kattavammin ja systemaattisemmin luontotietoa niin, että laajojen alueiden systemaattiset paikkatietotarkastelut olisivat mahdollisia.

Tulee muistaa, että ekologisesti vastuullinen maankäytön suunnittelu vaatii joka tapauksessa kattavaa luontotietoa, käytettiin alueiden arvottamisessa laskennallisia työkaluja tai ei.

Luonnollisesti myös kaupunkiviheralueiden käyttöä ja arvostusta kuvaavan datan keräämistä ja tutkimusta tulee kehittää.

Havaintodatan lisäksi tarvitaan asiantuntijatietoa. Olen väitöskirjatutkimuksessani nojannut laji- ja luontoasiantuntijoihin, eikä työni olisi ollut mahdollista ilman heidän tietotaitoaan. Luonnonsuojelu perustuu perinteisesti hyvin vahvasti asiantuntijatyöhön, eikä suojeluarvottaminen sitä sinällään muuta.

Asiantuntijanäkemyksiä tullaan suojeluarvottamisen tapauksessa tarvitsemaan esimerkiksi analyysirakenteiden suunnittelussa ja tulosten tarkastelussa.
Yhtä lailla tulee muistaa, että suojeluarvottaminen parhaimmillaankin vain tukee suunnittelua ja tuottaa suunnitteluun taustatietoa. Laskennalliset analyysit eivät koskaan korvaa varsinaista suunnittelua eivätkä poista suunnittelijoiden tai suunnittelijuuden tarvetta. Laskennallisista, systemaattisista analyyseistä vasta alkaa varsinainen priorisointi.

Korostan, että olen tehnyt väitöskirjani Zonation-asiantuntijan näkökulmasta, en maankäytön suunnittelijan roolissa. Monet suunnitteluun ja suojeluarvottamisen jalkauttamiseen liittyvät poliittiset, teknistaloudelliset, juridiset, päätöksentekoon liittyvät ja monet muut seikat jäävät vielä vastausta vaille.

Kaikesta huolimatta voidaan sanoa, että hyvin toteutettuna alueiden suojeluarvottaminen voi tehdä ekologisesti vastuullisempien suunnitelmien ja maankäyttöratkaisujen tekemisestä helpompaa ja selkeämpää. Erityisen hyödyllinen menetelmä on silloin, kun suunnittelussa pitää huomioida samanaikaisesti hyvin monenlaisia luontoarvoja – suunta, johon maassamme ja maanosassamme ollaan enenevässä määrin kulkemassa.

…sillä kattavaan ekologiseen tietoon perustuva suunnittelu ja päätöksenteko voi edesauttaa viisaiden ja ekologisesti kestävämpien ja vastuullisten maankäyttöpäätösten tekemistä. Ja kovin paljoa muuta ei biodiversiteettikriisin ratkaisemiseen tarvitakaan.

Seuraavaksi lausun muutaman sanasen väitöskirjatyöstäni englanniksi Arvoisan Opponentin luvalla.

Then a few words in English for the international audience.

Humans are responsible for the current mass extinction wave. This is most of all caused by habitat destruction, which is a result of our clearly unsustainable way of using land and space on Earth.

Therefore,

we must start accounting for biodiversity and socioecological values of areas much more thoroughly in our land-use planning, including urban areas. This in turn would require tools that would help land-use planners in mitigating the various conflicting land-use interests in a systematic way.

Spatial conservation prioritization, a method falling under the field of systematic conservation planning, could be such a tool if used properly.

And that is what my thesis is about.

Ja nyt, pyydän Teitä, Arvoisa Opponentti, tiedekunnan määräämänä vastaväittäjänä esittämään ne huomiot, joihin katsotte väitöskirjani antavan aihetta.


Joel Jalkanen, MSc, defended his doctoral thesis entitled ‘Spatial Conservation Prioritization for the Benefit of Urban and Regional Land-use Planning’ on 27 November 2020 at 12.00 at the Faculty of Science, University of Helsinki.

Associate Professor Niina Käyhkö from the University of Turku serevd as the opponent and Professor Tuuli Toivonen as the custos.

Joel completed his doctoral thesis in the Digital Geography Lab at the University of Helsinki and in the Spatial Planning of Urban Biodiversity and Ecosystem Services project that received funding from the KONE Foundation.

New paper out: Spatial prioritization for accessibility of urban parks

In our recent paper published in Applied Geography, we combine travel time modeling with spatial conservation prioritization to identify green areas that best serve the recreational use. We consider equitable access between urban dwellers, the need for various types of parks, and the use of various transport modes. The paper puts together approaches from conservation planning and accessibility research to support land-use planning decisions.

Green areas are important for urban residents. But how to prioritize between them? (Image by Angelo Giordano from Pixabay.com)

 

 

Spatial (conservation) prioritization is a way to identify “less” to “more important” places for conservation or other land uses based on multiple criteria. The outputs of the prioritization can be useful for locating optimal places for protection, for instance, or in our case, recreation. One of the major principles in spatial prioritization is complementarity, i.e. the attempt to secure the existence of all species and habitats (or, whatever is used as input data) in the prioritization process.

A spatial prioritization software Zonation, developed at the University of Helsinki, works as follows: It first takes the full study area under examination and checks how widely-distributed different input features are (be it multiple species, for example). It then takes away a small bit of the area; namely, the bit that corresponds the least to the total biodiversity in the area. Such areas would only harbor few species that are generally widely distributed. Zonation repeats these steps, checking the distributions and removing the least valuable areas, until the entire target area is completely ranked. The prioritization process is based on a ‘Robin Hood algorithm’ that always tries to take away from those species that have the most available areas at the corresponding iteration. This principle of complementarity results in high coverage of protected features compared to more traditional hotspot approach.

What we realized was that this principle applies directly to the goal of maintaining equality in urban greenspace provision!

The importance of green spaces is often measured as the number of people living in the vicinity. Albeit useful for many purposes, this approach misses the fact than a certain park can be the only accessible one for a small number of people and thus irreplaceable at the whole-city level. Zonation and its complementarity-principle, on the other hand, could be used to identify sets of greenspaces that jointly cover maximal recreation possibilities to all urban districts, not just for the most populated ones. Now we only needed some information about how accessible all green areas are from the point of view of all city districts in the Helsinki Metropolitan area…

But we do! We took the MetropAccess Travel Time Matrix and calculated the travel times (by walking and biking) from each district to all urban green areas in the region. In addition, to demonstrate that the method can account for different types of green spaces, we also calculated the travel times to large recreational forests at the urban fringe. Travel times to parks were calculated separately from the point of view of every district in the region.

An example of travel time layers: accessibility of urban parks for the residents in the Pitäjänmäki district. Image from the original article.

That information was put into Zonation, and as a result, we got a priority rank map that shows how “critical” different green areas for the balanced, i.e. equitable, provision of accessible greenspaces for every district.

Zonation rank maps. Not only the most central parks are the most important to ensure, but there are important sites at the urban fringe as well. This effect remains even when green areas are weighted according to the population living within the vicinity (right). See the full image in the original article.

This information is very useful for urban planners in the region and offers an important piece in holistic urban prioritizations that balance between e.g. urban biodiversity and recreation possibilities of residents.

Guess what we´ll be doing next 😉

xxx

Joel Jalkanen, Henna Fabritius, Kati Vierikko, Atte Moilanen & Tuuli Toivonen (2020) Analyzing fair access to urban green areas using multimodal accessibility measures and spatial prioritization.  Applied Geography, 124: 102320

Our codes and Zonation input and output files can be found in Zenodo and GitHub.

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.

 

Reflections on the 8th Nordic-Baltic Migration Conference

The second panel ”New Challenges in Cross-Border Mobility, Nordic-Baltic Region” in the Nordic-Baltic Migration Conference in Tallinn, Estonia

Olle Järv from the Digital Geography Lab attended as an expert panellist in the Nordic-Baltic Migration Conference “Cross-border Mobility in the Nordic-Baltic Region organized by the Nordic Council of Ministers’ Office in Tallinn, Estonia on September 18, 2020. Olle participated in the second panel ”New Challenges in Cross-Border Mobility, Nordic-Baltic Region” together with Uffe Palludan (Palludan Fremtidsforskning), Jonas Wendel (Nordic Council of Ministers’), Rolle Alho (Uni Helsinki), and Saara Pellander as a moderator (Migration Institute of Finland). In the panel, Olle briefly introduced his BORDERSPACE research project on cross-border mobility and transnational people, and how these research topics benefit from novel data sources such as social media and mobile phone data.

In conclusion, the panellists’ discussion highlighted several (new) challenges in the cross-border mobility and interaction in the Nordic-Baltic region:

  • Cross-border mobility and interactions as well as transnational people are taken for granted. In reality, we don’t know much about transnational people, their cross-border practices and how these influence the broader society.
  • We should treat transnational people more than just migrants or tourists. Their daily lives are not confined to only one country, but take place in several countries.
  • We need to acknowledge transnational people and consider them better in policymaking in both sides of the border. The COVID-19 crisis with the closed country borders in spring 2020 showed how poorly transnational people are considered in political decision-making.
  • Developing only infrastructure (e.g. Öresund Bridge between Denmark and Sweden) is not enough for promoting cross-border collaboration and transnational functional regions. We also need political will and collaboration to promote cross-border interaction, and to benefit from existing cross-border infrastructure.
  • One main challenge is the ability of envisioning and executing long-term plans, both from the infrastructure and policy perspective, for developing cross-border interaction and collaboration in the Nordic-Baltic region.

Check out the conference video HERE.

Read the summary about the second panel HERE (in English) and HERE (in Estonian) by the Nordic Council of Ministers’ Office in Estonia.

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.

BORDERSPACE project led by Academy Research Fellow Olle Järv focuses on cross-border mobilities and interactions, transnational people, and functional transnational spaces. The novelty of the project stems from the use of novel big data sources to provide valuable insights for cross-border research and practice.