Theme 3: Advances in Sensors, Networks and Processing

One of many geophysical methods used during on-site inspections: Ground penetrating radar to analyze shallow ground structures.
Hydrophone recording of the tsunami that struck Japan

The methods allowed for an on-site-inspection may cover areas of up to 1,000 square kilometres for specific sites of interest. The methods used must be capable of detecting observables related to an event that triggered the on-site inspection, especially those related to a nuclear test, if any. These can include geophysical anomalies from several metres to several hundred metres in depth or radioisotope traces emanating from the surface, and other relevant features.

This Theme focuses on advances in sensors, networks and data processing for monitoring and inspection. Advances may come from the adaptation of methods already in use by specialists in other areas, such as satellite photography, or from the evolution of novel approaches within the CTBT scientific community that may spin off to other techniques. Many elements of the current monitoring effort are also used in other contexts, for example in the characterization of earthquakes, climate change studies, the measurement of atmospheric transportation, or the monitoring of releases from nuclear power plants.


  • The design of monitoring networks
  • Improving maintainability, reliability, and efficiency of systems and operations
  • Comparison and integration of global, regional and on-site operational systems
  • Integrated processing of disparate monitoring or inspection data (data fusion)
  • Commercial and scientific applications with relevance to CTBT on-site inspections
  • Data structures suitable for a machine learning approach for large data volumes
  • Pathways for integrating scientific innovations into operational data processing
  • Technology foresight over the horizon: future sensors, networks, data communications and data processing for global monitoring and on-site inspections
  • Education, capacity building and knowledge transfer