You are here

Tracking volcanic ash with social media – Asst Prof Benoit Taisne in interdisciplinary collaboration with SCSE wins Accelerating Creativity and Excellence Award

28 Jan 2019

Congratulations to Gao Cong of SCSE (PI) and ASE’s Asst Prof Benoit Taisne (Co-PI), who have won Prof Subra Suresh’s Accelerating Creativity and Excellence (ACE) Award for a project entitled ‘Detecting and Tracking Volcanic Ash Using Social Media Data’. The ACE Programme has been launched by Prof Subra Suresh to encourage greater interdisciplinary collaboration between the various schools and colleges in NTU. By providing seed funding it aims to catalyze bold and unconventional cross-disciplinary research across colleges.

Professor Gao Cong is a computer scientist with research interests such as geospatial, textual, and mobility data management, large scale data analytics, mining social networks and social media. In this new project he is collaborating with ASE and EOS volcanologist Asst Prof Benoit Taisne, who specializes in volcanic eruptions, including the structure and geometry of the volcanic conduit, characteristics of ash columns and eruption dynamics.

The winning project combines computer science and volcanology to detect and track volcanic ash using machine learning techniques. Volcanic ash consists of fragments of pulverized rock, minerals and volcanic glass, created during volcanic eruptions. During a volcanic eruption, the ash impacts on society by affecting human and animal health, disrupting aviation, and causing disruption to critical infrastructure (e.g., electric power supply systems), primary industries (e.g., agriculture) and buildings. However, the movement of the ash is dependent on complex weather patterns, which makes is very difficult to predict.  

By using social media data, such as tweets, the researchers hope to develop ways to expedite the processing of large data streams, performing real-time geoprocessing of incoming data. They also intend to link external artefacts such as media and internet websites to each social media item, e.g., tweet. The new information will be integrated with traditional sources for volcanic activity to supports and validate the new methods. This project could significantly improve our overall ability to monitor and forecast the distribution of volcanic ash, enabling better prevention of its societal impacts.