Application of a temporal decorrelation model using Sentinel-1 SAR data to Detect volcanic ash deposits related to the 2020 Taal volcano eruption

NARANJO, CAMILO; EUILLADES, PABLO; TOYOS, GUILLERMO; EUILLADES, LEONARDO; VILLAROSA, GUSTAVO

Remote Sensing Applications: Society and Environment

Elsevier

Año: 2023

2352-9385

Volcanic ash deposits affect buildings, vegetation, and population. After a volcanic eruption, it iscritical to detect the areas affected by ash deposits to achieve an advisable management of theemergency. Optical sensors have been widely used to carry out this task, but they are limited bysolar illumination and weather conditions. As an alternative, Synthetic Aperture Radar (SAR) datais not affected by those limitations. Recently, a Temporal Decorrelation Model (TDM) that usesSAR data was proposed for detecting and mapping ash deposits, but it has only been applied toL-band data. Today there is available a huge quantity of C-band data acquired by the Sentinel-1constellation. In this study we applied the TDM to Sentinel-1 data in order to assess itsperformance for detecting volcanic ash deposits after an eruption. We selected the eruption ofTaal volcano in The Philippines on January 12, 2020, as our case study. We computed more than4,000 interferometric pairs from a dataset of 93 images acquired before, during, and after theeruption. Our results show that TDM can be applied to C-band data, despite the higher temporaldecorrelation suffered by them. Our final probability map is consistent with the field evidencereported by the Philippines Institute of Volcanology and Seismology (PHILVOLCS) and theisopachs map reported in the literature. This new application provides a novel framework for thecoherence exploitation of C-Band data. Also, this approach could be applied to detection andmonitoring of other natural disasters.