Automatic detection of volcanic ash from Himawari-8 satellite using artificial neural network

Richard Mahendra Putra, Adhi Harmoko Saputro, Laiza Arazak, Sulton Kharisma

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Volcanic ash is a significant phenomenon towards aviation safety and capacity of influencing climate change. Therefore, accurate information of the volcanic ash spatial distribution in the atmosphere possessed a fundamental role in the community. Polar type satellites such as Terra/Aqua equipped with MODIS sensors are capable of providing vivid imagery of the volcanic ash spatial distribution. However, the deficiency of this satellite is unable to perform optimal imagery for real-time monitoring due to its limitation require to be located above the volcanic ash site. Therefore, a geostationary satellite is a feasible solution to solve this issue hence its capability to observe specified fixed location continuously. Despite its capability, this type of satellite also performs designated weaknesses hence non-absolute perpendicularity observation angles on certain conditions towards the observed objects from the satellite fixed position. The purpose of this study is to create an automatic detection system using Himawari-8 satellite observations data by applying Artificial Neural Network (ANN) with training datasets and utilizing Terra/Aqua polar type satellite with MODIS sensors as validator. The input variation based on previous research references were using three bands, all bands, and four variations of satellite bands. The result of the study justifies the models established using all bands and four variation bands can produce good performances in training data, although less consistent if applied towards other cases. While the single-pixel model with three-band input well suited over Mt. Merapi volcanic eruption event on June 1st, 2018 with 93.71% accuracy.

Original languageEnglish
Title of host publicationInternational Conference on Science and Applied Science, ICSAS 2019
EditorsA. Suparmi, Dewanta Arya Nugraha
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735419537
DOIs
Publication statusPublished - 27 Dec 2019
EventInternational Conference on Science and Applied Science 2019, ICSAS 2019 - Surakarta, Indonesia
Duration: 20 Jul 2019 → …

Publication series

NameAIP Conference Proceedings
Volume2202
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

ConferenceInternational Conference on Science and Applied Science 2019, ICSAS 2019
Country/TerritoryIndonesia
CitySurakarta
Period20/07/19 → …

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