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2021 | OriginalPaper | Chapter

Deep Learning Methods as a Detection Tools for Forest Fire Decision Making Process Fire Prevention in Indonesia

Authors : Dia Meirina Suri, Achmad Nurmandi

Published in: HCI International 2021 - Late Breaking Posters

Publisher: Springer International Publishing

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Abstract

This research examines the collaboration between agencies in policy-making based on hotspot monitoring from satellites. Valid data regarding the number of hotspots from the satellite is needed in decision making because it provides information used to control forest and land fires in Indonesia. For instance, the Ministry of Forestry uses data from the NOAA-18 satellite for analysis, while the BMKG utilizes those from the Agua/Terra. However, the data generated by each satellite has differences in the number of hotspots. Therefore, this research aims to determine the collaboration between the Ministry of Forestry and BMKG in the use of satellite data for decision-makers to determine disaster alert status. This research uses a qualitative approach to analyze secondary data from two popular media sources collected using the Nvivo 12 plus application. The result showed that agencies involved in fire prevention lack collaboration due to institutional designs that lead to a lack of communication and unclear roles for each institution during the decision making process.

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Metadata
Title
Deep Learning Methods as a Detection Tools for Forest Fire Decision Making Process Fire Prevention in Indonesia
Authors
Dia Meirina Suri
Achmad Nurmandi
Copyright Year
2021
Book
HCI International 2021 - Late Breaking Posters

Print ISBN: 978-3-030-90175-2

Electronic ISBN: 978-3-030-90176-9

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-90176-9_24