Workshop session supported by Imago: Inequalities from Space

Supported by Imago Data Service for Imagery and QMRG RGS-IBG Quantitative Methods Research Group

In this workshop, learn how complex Earth Observation (EO)-derived data can be transformed into accessible, analysis-ready resources that support evidence-based decision-making. Using data products from Imago Data Service for Imagery, we will provide a guided, practical learning experience built around reproducible geospatial workflows.

This session emphasises the role of GIS in driving meaningful progress for communities and environments. Work directly with real-world datasets and explore how imagery-derived indicators can be integrated with socioeconomic measures to investigate spatial inequalities and inform policy-relevant insights.

You will load spatial boundaries, merge satellite-derived indicators with deprivation metrics, generate summary statistics, and create maps that reveal significant spatial patterns. Accessible statistical techniques—including correlation, regression, and hotspot analysis—will be introduced to support robust interpretation, alongside guided discussion on uncertainty, confounding factors, and the limits of causal inference.

The workshop welcomes those new to EO as well as users experienced with GIS or programming environments such as R or Python. Emphasis is placed on transferable skills, reproducibility, and analytical confidence so you can adapt the workflow to your own research, teaching, or applied projects.

Note: To take part in this workshop, you will need to bring your own laptop.