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Tuscany: large-scale ground hazard monitoring using Sentinel-1 imagery

We are excited to share this interesting case study that demonstrates how the European Earth Observation Programme “Copernicus” can trigger operational projects, which in turn can increase safety and provide useful information to decision makers and citizens.

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Regional monitoring of Toscana
The case involves a collaboration of three different entities: the Regione Toscana, the University of Florence, and TRE ALTAMIRA, our EO value-added service company. The group is working together to make surface deformation data that is gathered from space, into a unique and reliable data source for a decision-support system for civil protection at regional scale.

The service. In 2016, TRE ALTAMIRA and The Earth Science Department (DST) of the University of Florence were requested by the Regional Government of Toscana (Italy) to provide a risk mapping service over the entire region using satellite radar data that would be updated on a regular basis. DST is an “expertise centre” for the Italian Civil Protection Department, having extensive experience in landslide mapping and monitoring, as well as in civil protection procedures.

The service takes advantage of Sentinel-1 imagery, provided by ESA, in the framework of the Copernicus programme. Sentinel-1 A and B are two twin satellite platforms mounting synthetic aperture radar (SAR) sensors specifically designed for ground deformation monitoring over large areas by means of interferometric data processing (InSAR).

By applying SqueeSAR™ – TRE ALTAMIRA’s proprietary InSAR algorithm – to Sentinel-1 archive images, our engineers have identified millions of measurement points over Tuscany, which are now used as a “virtual geodetic network” for measuring any surface displacement. The displacement time-series describing the motion of these “radar benchmarks” are regularly updated with every new satellite acquisition. InSAR bulletins highlighting areas affected by accelerations or, more generally, abrupt trend variations are then delivered to all regional municipalities. To this end, a new algorithm, designed specifically for this application, can automatically select all points exhibiting any anomalous behaviour. Finally, DST staff integrates InSAR data with other information layers (e.g. high resolution DTM, geological maps, landslide inventory data, etc.), and provides recommendations for risk mitigation.