SPF: Sun Probability Framework
This training is in development. Check back soon, or open an issue if you’d like to be notified when it’s ready.
What is SPF?
Sunlight exposure shapes human behaviour, health, and wellbeing — from mood and physical activity to the price of houses. Yet researchers and policymakers have lacked accessible, high-resolution data on local sunlight conditions. Existing approaches either rely on regional aggregates that are too broad, or on sun-angle calculations that are computationally expensive and difficult to apply at scale.
The Sun Probability Framework (SPF) addresses this gap. It translates complex satellite cloud mask data into simple measures of sunlight probability at the geographic scales researchers already work with — small areas, neighbourhoods, and administrative units.
The underlying dataset is openly available: Cloud probability statistics per small area in 2024 (v1.0).
What you’ll learn
This research-track training walks through working with SPF data in R or Python.
Planned content:
- What SPF measures and how it’s derived from satellite cloud masks
- Loading and exploring the small-area cloud probability dataset
- Aggregating sunlight probability to your own geographies of interest
- Visualising spatial patterns of sunlight exposure across the UK
- Linking SPF to other indicators — health, housing, behaviour