Empowering Social Science Research through Satellite Insights

Harnessing satellite technology to transform social science research, SESAC delivers innovative analytics that deepen understanding of societal trends and enable impactful decision-making.

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Turning Global Pixels into Social Intelligence

For decades, satellite technology has revolutionized our understanding of the physical world, tracking climate change, deforestation, and weather patterns. Yet, the potential for these ‘eyes in the sky’ to explain human behavior and societal trends remains largely untapped.

SESAC was established to bridge this divide. Funded by the Swedish National Space Agency, we are a national hub dedicated to integrating high-resolution Earth Observation (EO) data with advanced social science methodologies. By combining satellite imagery with Sweden’s world-class socio-economic registers and AI-driven analytics, we provide a new lens through which to view our most complex challenges.

Our Core Pillars

SESAC operates at the intersection of advanced technology and societal needs. Our work is built upon three strategic pillars designed to foster innovation, democratize data access, and create lasting impact. By integrating Earth Observation into the social science toolkit, we empower a new generation of researchers and decision-makers to address global challenges with unprecedented spatial precision.

Building National Competence

We are committed to lowering the barrier to entry for satellite-based analysis. We provide the educational infrastructure needed to turn researchers into geospatial experts.

Open Workflows: Publishing transparent, reusable code and methodologies.
Training & Education: Offering short courses and webinars tailored for social scientists and students.
The Knowledge Hub: A central repository of resources for using EU Copernicus data in a Swedish context.

Co-Creative Collaboration

Innovation doesn’t happen in a vacuum. We bridge the gap between academia, public authorities, and the private sector to ensure our research solves real-world problems.

Stakeholder-Driven: Working directly with stakeholders to define high-impact research questions.
Hackathons & Workshops: Rapidly prototyping solutions for urban planning, sustainability, and crisis management.
A Distributed Network: Uniting the unique strengths of Lund, Chalmers, LiU, and KaU into one national engine.

Research Impact & Innovation

We push the technical boundaries of what is possible by combining “Big Data” from space with Sweden’s unique societal data.

AI & GeoAI Integration: Leveraging deep learning to automate the detection of socio-economic patterns.
Data Fusion: Fusing satellite imagery with detailed population registers for deep longitudinal studies.
Policy Support: Transforming complex analytics into clear decision-support tools for public health and inclusive growth.

Real-World Impact Proving the Concept

Explore how our team uses Earth Observation to solve societal challenges.

Urban Inequality Through “Local Eyes”

The Problem: Traditional maps often miss how people actually feel about their neighborhoods and their quality of life in deprived areas.

The Satellite Solution: We trained AI to look at satellite imagery and predict “deprivation scores” that match the actual perceptions of local citizens.

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Tracking Food Security in Conflict Zones

The Problem: When conflict breaks out, it becomes challenging to send researchers to the ground to check if people have enough food or if farms are being abandoned.

The Satellite Solution: By analyzing satellite time-lapses, we tracked agricultural activity in areas seized by ISIS to understand the long-term impact of war on food production and security.

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Measuring the Economy from the “Night Lights”

The Problem: In many developing regions, official economic data (GDP) is either unreliable or completely missing at the local level.

The Satellite Solution: We combined “Night Light” luminosity data with land-cover maps to estimate economic growth for any administrative area, no matter how small or remote.

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Predicting Poverty with Next-Gen AI

The Problem: Traditional poverty surveys are expensive and slow to produce, often taking years to update.

The Satellite Solution: We tested if Large Language Models (like ChatGPT) with vision capabilities can “rank” the poverty levels of villages just by looking at satellite images, with accuracy matching human experts.

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