Tag: big data

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BorderRegion_KDE – A tool to capture cross-border regions from mobility

Authors: Michaela Söderholm & Olle Järv

One of the objectives of the BORDERSPACE project is to empirically capture functional border regions, and transnational spaces in general, from the perspective of people – their mobility and social interactions across country borders. Our first studies showed how novel big data sources can reveal cross-border mobilities of people (Järv et al. 2023), and how that enables to map functional cross-border regions (Aagesen et al. 2023).

To scale up our approach and focus on all functional border regions in Europe, we needed a tool to automate multiple border region calculations. Thus, we developed BorderRegion_KDE – a program to automatically calculate a geographical Kernel Density Estimation (KDE) polygons derived from cross-border mobility, and visualize them.

Read more from our story map (HERE or click the map, below).

Interested in our project?

Read more from our project page: BORDERSPACE and get in contact! The project focuses on studying 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. The project is carried out at the Digital Geography Lab — an interdisciplinary research team focusing on spatial Big Data analytics for fair and sustainable societies at the University of Helsinki.

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The MOBI-TWIN project kick-started!

Mobi-Twin logo

 

What is it about

The Horizon Europe funded MOBI-TWIN – Twin transition and changing patterns of spatial mobility: a regional approach – sets out to redefine regional attractiveness in the context of significant global transition processes such as the green and digital transition. The project aims to analyze the changing drivers of spatial mobility and examine the effects of twin transitions on regional attractiveness and human (im)mobility.

The twin transition presents both opportunities and challenges for regions across Europe. As certain areas become more alluring due to the emerging prospects brought forth by the green and digital revolution, others risk being left behind. By utilising advanced information and computer modeling techniques, MOBI-TWIN seeks to comprehensively understand the impact of these changes on different regions of Europe and develop innovative policies that promote balance and inclusivity by harnessing the positive effects of Twin Transition.

A primary focus of MOBI-TWIN is to unravel the underlying factors that influence individuals’ decisions to relocate and how these factors may evolve in response to global changes. By analyzing various types of moves, including permanent relocations, commuting patterns, and temporary stays, the project aims to gain insights into the intricate dynamics and implications for different European regions.

How we do it

Taking a step further, MOBI-TWIN employs a specialised computer model to simulate the potential outcomes of people’s mobility in the face of the Twin Transition. This includes assessing the potential influx of individuals into specific locations, the types of jobs they may acquire, and the subsequent impact on regional populations, social structures, welfare system, and labour markets. By leveraging these findings, MOBI-TWIN aims to propose policies that harness the positive aspects of these changes and maximise the benefits for different areas. Of particular importance is the examination of how the disruptions caused by the COVID-19 pandemic and Brexit have affected freedom of movement between EU regions.

Continue reading “The MOBI-TWIN project kick-started!”

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Join our special session at ECTQG’23 in September

Olle Järv (University of Helsinki) and Ate Poorthuis (KU Leuven) organize a special session focusing on how dynamic mobility flows form functioning systems like communities, urban networks and regions at the European Colloquium on Theoretical and Quantitative Geography 2023. The ECTQG’23 takes place 14.–17. September 2023 in Braga, Portugal.

Join us and submit your abstract HERE. Abstract deadline: 15th May 2023. We plan to organize a special issue in a peer-reviewed geographical journal in 2023 and look forward to your contribution on the scope, in addition to our ongoing research in BORDERSPACE project. See our session description, below:

Special Session “From dynamic mobility flows to functional systems: Communities, urban networks, and regions”

The analysis of functional systems through spatial interactions has been a long-standing interest in quantitative geography. While traditional approaches often focused on single cities or countries, limited themselves to specific kinds of mobility (e.g. commuting or migration), or a single point-in-time, new (big) data sources and computational methods have opened up new avenues. By not only providing new insights on temporal rhythms of functional systems, these systems can also be investigated at larger global and cross-country scales, and capture for more heterogeneous types of mobility (e.g. cross-border commuting, multilocal living, recreation and social networks). This can shed new light on, for example, border regions from different countries forming one functional system regarding peoples’ daily practices or the temporal rhythms of urban networks.

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MSc thesis on studying multi-local living in Finland using mobile phone data and electricity consumption data

Author: Iivari Laaksonen

Why is the study relevant?

Multi-local living can be defined by individuals or families having access to more than one residence in their everyday lives. It is a complex social phenomenon causing weekly and seasonal changes in population numbers as people move between regions. This means that the phenomenon is tightly connected to human mobility. In prior research, multi-locality has been mainly studied using official statistics that fail to capture the dynamic nature of people’s mobilities and dwelling. To address this in my thesis, I utilized spatially and temporally accurate big data sources − mobile phone and electricity consumption data − to capture people’s presence and mobility. More accurate information about multi-local living can be useful for local businesses and regional planning in rural areas.

How was the research done?

In my thesis, multi-local living was studied in Finland and in the county of South Savo, which has the highest proportion of second homes/free-time residences in the country. The study was done by analyzing spatiotemporal changes in people’s presence (mobile phone data from Telia Crowd Insights) and by examining how the changes relate to the number of second homes (official statistics) in different areas with correlation analyses. In addition to monthly comparisons, analyses were conducted separately for workdays and weekends to assess how people’s multi-local practices differ between weekdays. The study period of the thesis was from November 2018 to August 2019.

Mobile phone data also contains information about people’s origins (previous night location). This allowed to assess the proportions of origin counties of people visiting South Savo. Moreover, mobile phone data was used to assess the results of second home occupancy in South Savo gained from electricity consumption data which had been previously calculated in the MOPA research project.

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Digital Geography Lab presented the latest research at Mobile Tartu 2022

It was our honour and pleasure to attend the 8th Mobile Tartu conference organized by the Mobility Lab of the University of Tartu, Estonia. The event was once again scientifically fruitful and socially rewarding — exactly the way how the founder of the conference, the late professor Rein Ahas had envisioned it!

The members of the Digital Geography Lab were well represented in organising PhD workshops, presenting latest research from various projects, chairing sessions and moderating a panel discussion.

 

Olle Järv and Oleksandr Karasov organized a PhD workshop on “Social media sources as a tool to monitor cross-border mobility”, and Christoph Fink and Tuuli Toivonen together with our former group member Age Poom organized a PhD workshop on “Data and tools for environmental exposure assessment during urban mobility”.

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Two new studies on revealing cross-border mobility and border regions

One of the goals of the BORDERSPACE project at the Digital Geography Lab is to examine whether and how social media data such as geo-located Twitter data can reveal cross-border mobility of people and provide new insights for understanding border regions. We demonstrate the feasibility of using Twitter data in two different recently published studies – the first study from the Greater Region of Luxembourg and the second study from the Nordic countries.

 

Study #1: “Revealing mobilities of people to understand cross-border regions: insights from Luxembourg using social media data”

Published in European Planning Studies

Authors: Olle Järv, Håvard W. Aagesen, Tuomas Väisänen & Samuli Massinen

Conceptually, our approach was to make big data small and meaningful by: 1) using a bottom-up concept of activity space (e.g. Järv et al., 2014); 2) using mobility as a tool to capture individual activity spaces; and 3) contextualizing mobility from the border perspective.

Figure 1. The conceptual framework of data collection and data enrichment using the activity space approach to reveal cross-border mobilities and its motives from an individual perspective.

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OptiSS 🧐 — A tool to optimize spatial joining of social media data

Authors: Bryan Vallejo, Olle Järv

We developed the OptiSS tool to optimize geodetic spatial joining for assigning geographical attributes to social media data in the BORDERSPACE project at the Digital Geography Lab. The tool has a user-friendly local app, yet its Python script can be easily used in any workflow.

Why we developed the tool?

In the BORDERSPACE project, we need to assign hierarchical spatial attributes (municipality, region, country) to each geo-located tweet. Mostly, geo-located tweets obtained from Twitter’s API already have geographical information such as an administrative unit and a country, in addition to exact coordinates. Yet, not all tweets have such information and, most importantly, some tweets are not located on land – some are just off the coast or somewhere at sea (Figure 1). However, geodetic spatial joining requires computational resources and is time consuming, especially when we have 100+ million geo-located tweets to handle. Thus, we created the OptiSS tool to make computation more efficient. The tool works for any social media data that have at least geographical coordinates.

Figure 1. The OptiSS tool assigns geographical attributes like municipality or country efficiently to social media posts. This is useful particularly when posts are not only located on land, but also off the coast (highlighted in red circles). Continue reading “OptiSS 🧐 — A tool to optimize spatial joining of social media data”

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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.

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