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AI-Enhanced Remote Sensing for Forest Fire Mitigation: Integrating UAV and Satellite Imagery to Strengthen Indonesia's National Security

  • Anggi Pradikti Purna Dewi1*
  • Asep Adang Supriyadi2
1 Sekolah Tinggi Intelijen Negara
2 Indonesia Defense University image/svg+xml
* Corresponding Author: Anggi Pradikti Purna Dewi

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.

Keywords

Remote sensing Forest fire Early detection UAV AI National security

How to Cite

Citation Format
Purna Dewi, A. P., & Supriyadi, A. A. (2026). AI-Enhanced Remote Sensing for Forest Fire Mitigation: Integrating UAV and Satellite Imagery to Strengthen Indonesia’s National Security. International Journal of Management Science and Information Technology, 6(1), 568-577. https://doi.org/10.35870/ijmsit.v6i1.6981

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Author Biographies

Anggi Pradikti Purna Dewi, Sekolah Tinggi Intelijen Negara

Intelligence Studies, Sekolah Tinggi Intelijen Negara, Bogor Regency, West Java Province, Indonesia

Asep Adang Supriyadi, Indonesia Defense University

Sensing Technology Study program, Faculty of Science and Technology, Universitas Pertahanan Republik Indonesia, Bogor Regency, West Java Province, Indonesia

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Copyright (c) 2026 Anggi Pradikti Purna Dewi, Asep Adang Supriyadi

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This work is licensed under a Creative Commons Attribution 4.0 International License.

This is an open-access journal distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, reproduction, and adaptation in any medium (even commercially), provided appropriate credit is given to the original author(s), a link to the license is provided, and any changes made are indicated. Authors retain copyright without restrictions and grant the journal the right of first publication as well as non-exclusive publishing rights for archiving, indexing, and scholarly dissemination.

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