Satellite imagery encodes features predictive of regional mortality and life expectancy

Background Increasingly accessible satellite imagery provides scalable measures of the built and natural environment relevant to population health. However, whether such imagery can capture subnational variation in mortality and life expectancy remains unclear. We therefore assessed its predictive value for regional mortality and life expectancy across OECD regions. Methods We conducted an ecological, cross-sectional prediction study using 2023 data from OECD Territorial Level 3 (TL3) regions. Annual cloud-masked composites from the Harmonized Landsat and Sentinel-2 collection were processed in the Google Earth Engine, tiled at 224 x 224 pixels, and encoded with the pretrained Prithvi foundation model to derive region-level satellite embeddings. For each outcome, we trained LightGBM regressors for a country-only baseline, a satellite-only model, a combined model (country + satellite), and a final contextual model that additionally included prespecified socioeconomic and environmental c