Research themes

Our research focuses on analysing spatial and temporal interactions between people, and between people and their environment.

Much of our work examines human mobility/accessibility from different perspectives as a proxy for interactions from local to global scales. ​To do so, we apply novel big data sources and spatio-temporal big data analytics while paying attention to critical thinking and ethical issues.

Our research is divided into three closely interrelated themes: 1) socio-spatial interactions between people, 2) human–nature interactions, and 3) development of methods and tools for utilising big and open data sources to study these interactions.

Socio-spatial interactions

Our dynamic society is shaped by interactions between people, and between people and their surrounding environment, both social and physical. The mobility of people is a key proxy for indicating socio-spatial interactions, and thus for understanding how societies function, and change in time and space. Mobility is linked with the underlying spatial patterns of accessibility, a prerequisite for potential encounters. 

We at the Digital Geography Lab are particularly interested in the use of novel data sources complemented with traditional data to analyse population flows and dynamics, individuals’ mobility and activity spaces, spatial accessibility, and how these change in time. We combine mobility analytics with social media content analysis to enhance our understanding on spatial (in)equalities and integration, cross-border interactions and transnationalism, linguistic landscapes, urban sustainability, and health and wellbeing related questions. Our work contributes to the fields of urban geography and regional studies, transport and spatial planning, tourism, and health research. 

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People–nature interactions

Sustaining good environmental conditions is crucial for the health and wellbeing of both the planet and humankind. The possibility to access, use, and enjoy green areas is also an issue of social justice. At the Digital Geography Lab, we study human-nature interactions from various perspectives: how do people use green areas, how equal are their opportunities for being exposed to nature and how can we ensure a sustainable co-existence of biodiversity and people? We use various big and small data in our analyses, ranging from satellite images to social media data, GPS tracks, street view imagery, expert assessments combined with various environmental data layers such as air quality data and noise pollution data. We apply a wide range of methods including various GIS approaches, spatial prioritization, environmental exposure analysis and expert elicitation. Through our analyses, we address key issues in sustainable land use planning, biodiversity conservation, and environmental health research. 

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Related tools:

Big data and novel methods

The amount of data being collected about individuals and the environment, either actively or passively, is growing exponentially. Open data movement has made many publicly produced datasets easily available for research. Private companies are collecting unprecedented amounts of data on individuals through apps and mobile devices, which we seek to use for the common good. Taking full advantage of the growing body of data resources for increased understanding of spatial phenomena requires novel data mining, analysis and visualisation methods. In our work, we take advantage of the recent advancements in the fields of (geo) data mining, geoinformatics, Artificial Intelligence and visualisation techniques to develop tools and data products that can help to study socio-spatial interactions and human–nature interactions. Whenever possible, we share our tools and data openly. We have extensive global data resources collected from social media platforms (Twitter, Instagram and Flickr) and have published a widely used Travel Time Matrix for the Helsinki region in 2013, 2015 and 2018.  We have also recently published a public Green Paths routing tool for finding pleasant walking and cycling routes in the Helsinki region.

Data and tools:

GitHub:

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