Detecting short-term volcanic pre-eruption anomalies

• Main Author: Chee, Denny Jian Hao
• Other Authors: Benoit Taisne
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Earth and Environmental Sciences; Himawari-8; Moderate resolution imaging spectroradiometer; Brightness Temperature difference; Kolmogorov-smirnov test; Land surface temperature
• Online Access: https://hdl.handle.net/10356/174817
• Institution: Nanyang Technological University

Multi-sensor Remote Sensing can be employed to image and monitor volcanic processes in South-East Asia (SEA). In Indonesia and the Philippines alone, it is estimated to have more than 75% of the global volcanic threat. To further delve into these hazards, this study uses the Japanese Aerospace and Exploration Agency’s (JAXA) Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite and the National Aeronautics and Space Administration’s (NASA) Moderate Resolution Imaging Spectrometer (MODIS) onboard the Terra satellite to develop short-term imaging and monitoring of potential anomalous volcanic thermal outputs prior to an eruption in the SEA region. The satellites’ raw data from the thermal infrared bands are subjected to different methods of data analysis such as the Kolmogorov-Smirnov test, land surface temperature algorithms, time series analyses, and exploration of the relationship between Brightness Temperature (BT) and the elevation of a volcano. The time series analysis of the raw data showed signs of an increase prior to Sinabung’s 2019 eruption compared to other methods of analysis. The raw data, which lack a cloud cover mask, and the potential saturation temperature restricting data acquisition, are potential sources of limitations and uncertainties that can be reduced with further data processing. The findings from this research have the potential to significantly enhance the forecasting capabilities of volcanic processes in the SEA region, playing a vital role in hazard risk mitigation and improving disaster response workflows.