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p-Index From 2021 - 2026
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All Journal International Journal of Management Science and Information Technology (IJMSIT)
Purna Dewi, Anggi Pradikti
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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AI-Enhanced Remote Sensing for Forest Fire Mitigation: Integrating UAV and Satellite Imagery to Strengthen Indonesia's National Security Purna Dewi, Anggi Pradikti; Supriyadi, Asep Adang
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.6981

Abstract

Forest fires pose a significant ecological and national security threat, with increasing frequency and intensity driven by both natural and anthropogenic factors. Remote sensing technology has emerged as a strategic solution for early detection and mitigation of forest fires in high-risk areas. This study employs a qualitative literature review method, analyzing more than 15 recent scholarly articles focusing on the use of satellite imagery, UAVs, and machine learning integration in fire monitoring systems. The data were examined to assess the effectiveness of remote sensing in prediction, active detection, and post-fire management. Findings indicate that remote sensing technology, especially those utilizing multispectral imagery and surface temperature sensors, can improve fire detection accuracy to over 90%. AI-based segmentation systems and UAV imagery have proven effective in accelerating real-time wildfire response. Additionally, spatial data contributes to mapping fire-prone zones and planning strategic mitigation efforts. In conclusion, the integrative use of remote sensing strengthens early warning systems and decision-making processes in forest fire management, while safeguarding ecosystem stability and national security.
Co-Authors Supriyadi, Asep Adang