Visualization of Volcanic Ash Distribution based on Multispectral Satellite Imagery: A Comparing Method

Abstract

Volcanic ash produced by eruptions has been significantly dangerous towards aviation. The necessity of volcanic ash early warning system distribution is crucial to reduce casualties on aircraft accident. In this paper, some techniques of volcanic ash detection were compared to find the proper algorithm to visualize the volcanic ash distribution. The multispectral image was acquired from the geostationary satellite (Himawari −8 satellite) in specific time observation. The reference data were collected from the MODIS sensor in the Aqua satellite to monitor the volcanic ash distribution at the same time and place. The first method is to generate the value of brightness temperature differences (BTD) at $11\ \boldsymbol{\mu} \mathbf{m}$ and $12\ \boldsymbol{\mu} \mathbf{m}$ wavelengths. The second method is conducted by inserting $3.9\ \boldsymbol{\mu} \mathbf{m}$ information from the product of three-band volcanic ash known as (TVAP). The third method is a combination of the first and second method while the last method utilizes RGB composite color combination from several bands of Himawari −8. The reference data collected by MODIS Observation at 06.00 UTC. The BTD technique unable to detect low-intensity volcanic ash, while combining it with the TVAP method can increase the standard method performance. Based on expert judgment, BTD technique has a good performance for thick volcanic ash although unable to detect thin volcanic ash distribution. Three-band Volcanic Ash Product (TVAP) method could detect thick and thin volcanic ash. The combination of BTD and TVAP method has an excellent result to observe volcanic ash distribution, but the result tends to overestimate like TVAP distribution. RGB Methods from JMA Configuration have the same pattern and distribution of volcanic ash as MODIS observation. Based on the study results, BTD, TVAP, and RGB composite methods can produce good results compared to MODIS imagery for monitoring the volcanic ash distribution.