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Advancing conflict research and response through satellite-derived data

2026-09-09 | original

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Why This Matters

This is the methods section of research using satellite radar (Sentinel-1 SAR) plus open building-footprint data to map war damage in Ukraine at the level of individual buildings. It shows how freely available Earth-observation and open-mapping datasets can now produce near-real-time, granular evidence of conflict destruction that traditional on-the-ground reporting cannot match.

Key Takeaways

Coherent change detection on Sentinel-1 SAR data flagged probable war damage across Ukrainian settlements from March 2022 to October 2023.
Damage is resolved to individual buildings by combining 10-m damage grids with 26.7 million Overture Maps footprints sourced from Microsoft ML and OpenStreetMap.
Analysis is contextualized with VIINA control-of-territory data, official Ukrainian population and boundary statistics, and UCDP fatality records.

Worth a Look

Lillesand Remote Sensing and Image Interpretation (Wiley) — If this study's use of Sentinel-1 SAR change detection and building-footprint datasets sparked your curiosity, this classic Wiley textbook walks through the fundamentals behind those methods, from radar imaging to image classification. It's a solid desk reference for anyone learning how satellite data becomes analyzable geospatial information.

See Lillesand Remote Sensing and Image Interpretation (Wiley) on Amazon → Affiliate link — we may earn a commission on purchases, at no extra cost to you. Product picked by AI based on this article; it is not a tested recommendation.

Ukraine data collection

For our analyses of building destruction during the Ukraine war, we draw on three existing datasets.

War damage data

We use war-related damage data from ref. 9, which identifies probable damage across Ukrainian human settlements between March 2022 and October 2023. This dataset was generated using a coherent change detection framework applied to Sentinel-1 SAR data75.

Building footprints

Building footprint data were sourced from Overture Maps, providing a comprehensive dataset of 26,714,652 building footprints in Ukraine. The primary sources for these footprints include Microsoft ML Building Footprints (72.8% of buildings) and OpenStreetMap (27.2% of buildings).

Tessellated geometries

The unit of analysis is tessellated geometries around populated places. We use the polygons provided by the VIINA dataset73, which are based on the GeoNames gazetteer and include 33,141 tessellated geometries in Ukraine.

Boundaries

Spatial data on admin1 and admin2 boundaries, and settlement boundaries for Mariupol and Sievierodonetsk, are from State Scientific Production Enterprise ‘Kartographia’, as provided by the Humanitarian Data Exchange platform74.

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Explore topics: ukraine war sentinel-1 sar overture maps viina dataset openstreetmap